From 745d99e5af09722f13668a7654568c3a0979c506 Mon Sep 17 00:00:00 2001
From: MichaelSchulzMETNO <MichaelSchulzMETNO@users.noreply.github.com>
Date: Sun, 5 May 2024 18:39:54 +0000
Subject: [PATCH] deploy: 92013fcaf295ce605a6dd41893173b401a428957

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diff --git a/_sources/basics/index.rst b/_sources/basics/index.rst
new file mode 100644
index 0000000..1d4a448
--- /dev/null
+++ b/_sources/basics/index.rst
@@ -0,0 +1,10 @@
+Jupyterhub basic usage
+======================
+
+
+.. toctree::
+   :maxdepth: 1
+
+   start_stop
+   lab
+   kernels
\ No newline at end of file
diff --git a/_sources/basics/kernels.rst b/_sources/basics/kernels.rst
new file mode 100644
index 0000000..e987803
--- /dev/null
+++ b/_sources/basics/kernels.rst
@@ -0,0 +1,80 @@
+Using different kernels in notebooks
+====================================
+
+
+.. note::
+  We are using ``mamba`` here which is a drop in replacement for ``conda`` that is generally faster. All commands that work with ``mamba`` should also work with ``conda``.
+
+We provide different conda environments as kernels for processing jupyternotebooks.
+You can see them in the launcher when you create a new notebook or choose one in the drop-dowmn menu in the top right corner.
+If you want to check which packages are included in the environment you can find the names of the environments available by doing: ``mamba env list``.
+To list packages and their versions within the environment use the following command: ``mamba env export -n environment_name --no-builds``.
+
+Available kernels
+-----------------
+
+- **minimal**: bare python3.11 environment
+- **base**: contains basic packages (mostly not useful for data processing)
+- **pangeo-notebook**: environment, built from `Pangeo nootbook v2024.04.05 <https://github.com/pangeo-data/pangeo-docker-images/tree/2024.04.05/pangeo-notebook>`_ extended with ``rioxarray``, ``pyrcel`` and ``geocat`` packages.
+- **ml-notebook**: environment, built from `Pangeo ml-nootbook v2024.04.05 <https://github.com/pangeo-data/pangeo-docker-images/tree/2024.04.05/ml-notebook>`_ with added packages:
+
+  .. code-block::
+
+    'gpflow' 
+    'scikit-learn'
+    'tf-keras'
+    'tensorflow-probability'
+    'tensorflow'
+    'iris'
+    'tqdm'
+    'cis'
+    'ESEM'
+    'pyaro'
+
+- **pyaero-notebook**: This `environment <https://raw.githubusercontent.com/metno/pyaerocom/v0.17.1/pyaerocom_env.yml>`_  includes various packages for ``pyaerocom``.
+
+  .. warning::
+    
+    This is environment contains older versions of packages to allow the latest  ``pyaerocom`` to work. If you don't require any specific packages from this environment, 
+    you should use the ``pangeo-notebook`` or ``ml-notebook`` kernel instead.
+  
+..
+  .. code-block::
+..
+    'pycel'
+    'ipykernel' 
+    'scikit-learn'
+    'netcdf4'
+    'xarray' 
+    'pyngl' 
+    'proplot' 
+    'cartopy' 
+    'rioxarray' 
+       
+    'pandas' 
+    'proplot' 
+    'seaborn' 
+    'cis'
+
+
+Using the conda environments outside of the course
+--------------------------------------------------
+
+.. note::
+  
+  Too learn more about what conda does and how to make your data analysis reproduce able, check out the code-refinery lesson on `conda-for-data-scientists <https://carpentries-incubator.github.io/introduction-to-conda-for-data-scientists/01-getting-started-with-conda/index.html>`_.
+
+
+You can also pipe it to a file to view later or to create same environment somewhere else: ``mamba env export -n <environment name> > environment.yml``. To leave out the build information use add ``--no-builds``.
+To create an environment out of this file: ``mamba -n environment_name -f environment.yml``. 
+
+
+
+.. attention:: 
+  :class: toggle
+  :name: Platform specific environments
+
+  The exported environment may be platform specific, f.e. you will see ``platform: linux-64``.
+  Recreating the environment on another platform might not work since some of the packages might not be available for your target platform.
+  In that case, it's recommended to use containers to reproduce the environment. However it is possible to export platform independent environments by using the ``--no-builds``. 
+  Furthermore, conda-lock can be used to create a lock file that solves the dependencies for different platforms and can then be used to recreate the environment on another platform.  
\ No newline at end of file
diff --git a/_sources/basics/lab.rst b/_sources/basics/lab.rst
new file mode 100644
index 0000000..ff929b3
--- /dev/null
+++ b/_sources/basics/lab.rst
@@ -0,0 +1,57 @@
+The JupyterLab Interface
+========================
+
+By default, you will get the web-based user interface for Project Jupyter that is called `JupyterLab <https://jupyterlab.readthedocs.io/en/stable/>`_.
+
+Menu Bar
+--------
+
+The menu bar at the top of JupyterLab has top-level menus that expose actions available in JupyterLab with
+their keyboard shortcuts. The default menus are:
+
+- **File**: actions related to files and directories
+- **Edit**: actions related to editing documents and other activities
+- **View**: actions that alter the appearance of JupyterLab
+- **Run**: actions for running code in different activities such as notebooks and code consoles
+- **Kernel**: actions for managing kernels, which are separate processes for running code
+- **Tabs**: a list of the open documents and activities in the dock panel
+- **Settings**: common settings and an advanced settings editor
+- **Help**: a list of JupyterLab and kernel help links
+
+Left Sidebar
+------------
+
+The left sidebar contains a number of commonly-used tabs, such as a file browser, a list of running
+kernels and terminals, the command palette, and a list of tabs in the main work area:
+
+
+
+If you move your mouse on the other icon of this left sidebar, a short information is given on its functionality.
+
+If you click on the "stop button" icon, you can see what is currently running on your server and you can click on
+"SHUT DOWN" to stop a running Python notebook or Terminal.
+
+### Start a new Terminal
+
+Similarly, you can start a new Terminal by clicking on "Terminal" in the Launcher.
+
+
+Tips
+----
+ If the **Launcher** tab does not exist
+ anymore in your JupyterLab, you can start a new one in "**File** --> **New Launcher**".
+
+
+
+Create a new python 3 notebook
+------------------------------
+
+Go back to the **File Browser** left sidebar tab and in the launcher select **Python 3** under the Notebook
+section:
+
+
+By default, your new notebook is named as "**Untitled.ipynb**":
+
+- **ipynb** is the extension for any Jupyter notebook and you should make sure all your notebooks get this extension (otherwise it is not recognized as a Jupyter notebook)
+- you can rename your jupyter notebook with the tab "File --> Rename Notebook..." or
+  right click on its name.
diff --git a/_sources/basics/start_stop.rst b/_sources/basics/start_stop.rst
new file mode 100644
index 0000000..0a9376f
--- /dev/null
+++ b/_sources/basics/start_stop.rst
@@ -0,0 +1,19 @@
+Starting and stopping your server
+=================================
+
+Your Jupyterhub tab should have the following panels:
+
+
+To start/stop your server, click "**File** --> **Hub Control Panel**":
+
+When your server is not running, the button "Stop My Server" does not appear and you only see the button "My Server".
+
+- To stop your server, click on "Stop My Server"
+- To start your server, click on "My Server"
+
+.. Warning ::
+
+  Don't forget to "**Stop My Server**" after you are done to free resources
+
+
+
diff --git a/_sources/contrib.md b/_sources/contrib.md
new file mode 100644
index 0000000..4629e52
--- /dev/null
+++ b/_sources/contrib.md
@@ -0,0 +1,43 @@
+# Contribute to this page
+
+
+
+## The recommended workflow for development
+1. Fork the repository to your Github account and fetch upstream to receive the newest commits.
+2. Alternatively, you should just clone this repo if you are part of the **eScience2024** team, this way the branches you create will get 
+3. Perform the development in a newly-created branch (other than `master`) in your repository. 
+4. Note that since we are using `myst-parser` both `.rst` and `.md` can be used.
+5. Build the page in the command line to test the introduced modifications by following the instructions below.
+
+### Locally build this page 
+Before filling a pull-request you should check that the changes introduced by you still make the site build. Therefore, you should always [build and test locally](https://coderefinery.github.io/sphinx-lesson/contributing-to-a-lesson/#build-and-test-locally) before you ask for a pull request. 
+
+To automatically update the documentation locally during development: 
+```
+$[~/PROJECT_ROOT] sphinx-autobuild docs/ _build
+```
+Using venv or conda is highly recommended. Also, when you are pulling from `master`, please don't forget to update your environment with `pip install -r requirements.txt` since those might have been changed since you last built the page locally.
+
+## After you are done with your changes:
+
+1. Merge or rebase on `upstream/master` (`master` if  you work within this repo) and resolve conflicts.
+2. Check with `sphinx-autobuild` to see if the page builds and looks as intended.
+3. Create a pull request to the `master` branch. Give a short description of what you have added.
+
+The static webpage is hosted on Github and automatically built by pushing changes to the `master` branch. The built webpage is displayed when selecting the `gh-pages` branch. This process is automatic. A guide to the principles can be found [here](https://pythonrepo.com/repo/executablebooks-sphinx-autobuild-python-documentation). 
+
+ If you have any questions, look in the Issues (including closed), if you don't find an answer - create a new one. 
+
+> **NOTE** If workflow above is too hard for you, there is a Github button in the top-right corner.
+
+
+
+## Reviewing PRs
+1. Checkout branch that is getting pulled.
+2. Build locally.
+3. Add commits locally to fix things.
+4. Add comments  in the pull request.
+5. Merge the PR (if you have rights and are happy with the changes).
+
+The web-page will get updated in a few minutes through github actions.
+
diff --git a/_sources/course_workflow/data.rst b/_sources/course_workflow/data.rst
new file mode 100644
index 0000000..8cecc9c
--- /dev/null
+++ b/_sources/course_workflow/data.rst
@@ -0,0 +1,9 @@
+Sharing data
+============
+
+Small size data (\<10 Mb) can be shared directly through the `eScience2024-projects repo <https://github.com/MetOs-UiO/eScience2024-projects>`_.
+
+Larger data will be put into read-only ``~/shared-craas1-nn9989k-geo4992/data/`` by request (ask @mvdebolsiy to copy it there).
+
+If you want to share something real quick with members of your group: you can access other user's home directories at ``~/shared-craas1-ns9989k-geo4992/dataporten-home/fc-3auid-3a<feide-user-id>/``.
+These folders are read-only for everyone except the owner.
diff --git a/_sources/course_workflow/index.rst b/_sources/course_workflow/index.rst
new file mode 100644
index 0000000..75dd2a8
--- /dev/null
+++ b/_sources/course_workflow/index.rst
@@ -0,0 +1,10 @@
+Workflow for eScience2024 course
+================================
+
+
+.. toctree::
+   :maxdepth: 2
+
+   workflow
+   rules
+   data
\ No newline at end of file
diff --git a/_sources/course_workflow/rules.rst b/_sources/course_workflow/rules.rst
new file mode 100644
index 0000000..eafea37
--- /dev/null
+++ b/_sources/course_workflow/rules.rst
@@ -0,0 +1,12 @@
+Basic Rules for the course
+==========================
+
+
+
+  #. Write your scripts/notebooks into the clone of your eScience2024-projects fork.
+  #. Work in your ``Group#`` subfolder in the clone (or even a subsubfolder for your work, one level deeper) to reduce number of potential conflicts when merging.
+  #. If there are files that are automatically created in that folder that should not be tracked, update `.gitignore`
+  #. Do not store data in that folder unless it is \< 10 Mb. See :doc:`Sharing Data <./data>`.
+  #. Do not download large number of files/large datasets into your home directory. 
+  #. Do not try to make files in the read-only folders (you will get errors on save). Mind where your File browser is when making new notebook/starting new Launcher.
+  #. Make issues in this repo, See :doc:`Contribute to this page <../contrib>`.
diff --git a/_sources/course_workflow/workflow.rst b/_sources/course_workflow/workflow.rst
new file mode 100644
index 0000000..a200859
--- /dev/null
+++ b/_sources/course_workflow/workflow.rst
@@ -0,0 +1,94 @@
+Basic setup
+===========
+
+
+1. Fork projects repository
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. |fbutton| image:: img/fork_button.png
+
+Before you start working on your group projects. You should fork `eScience2024-projects repo <https://github.com/MetOs-UiO/eScience2024-projects>`_.
+To make a fork, go to the repo page. There you will see a ``fork`` button |fbutton|. Click on it to create a copy of this repository in your github user space.
+**Uncheck** ``Copy the main branch only`` if you do not want to miss on other branches currently on the original repo.
+
+.. image:: img/fork-create.png
+   :width: 700
+   :alt: Fork Creation page
+
+2. Get GitGub Access token
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+From `GitHub documentation <https://docs.github.com/en/enterprise-server@3.9/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens>`_.
+
+- Go to Github.
+- Click on your your profile image in the top-right.
+- Click ``Settings``
+- Click ``Developer Settings``
+- Click ``Personel access tokens->Tokens (classic)``
+- Click ``Generate new token``
+- Click ``Generate new token (classic)``
+- Authenticate
+- Make a note
+- Click on ``repo``, ``user``
+- Click ``generate``
+- Save token somewhere, treat it as a password
+
+3. Setup git and clone on jupyterhub
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+After you have forked the projects repo you should login to `Jupyterhub <https://escience2024.craas1.sigma2.no>`_. 
+There, you would need to clone your fork and create your first branch you would be working on. See :doc:`Starting with git on the jupyterhub <../git_integration/git_jlab>`.
+
+.. attention:: 
+  :class: toggle
+
+  If you have already accessed `test sever <https://escience2024-test.craas1.sigma2.no>`_, you should move to `<https://escience2024.craas1.sigma2.no>`_. 
+  Test server is only there for testing and will get shutdown.
+
+- Open terminal through Launcher.
+- Type this commands filling in your **github** username and email (without ``<>``):
+
+  .. code-block:: bash
+
+    git config --global user.name "<your_username>"
+    git config --global user.email "<your_email>"
+
+- Clone **your fork** of  projects repository:
+
+  .. code-block:: bash
+
+    git clone https://github.com/<your_username>/eScience2024-projects
+
+- Go into your clone:
+
+  .. code-block:: bash
+
+    cd eScience2024-projects
+
+- Add upstream repository (See :doc:`Setting up remotes <../git_integration/remotes>`):
+
+  .. code-block:: bash
+
+    git remote add upstream https://github.com/MetOs-UiO/eScience2024-projects
+    git fetch --all
+
+- Make your first branch with a sensible name (what are you going to work on):
+
+  .. code-block:: bash
+
+    git checkout upstream/master
+    git switch -c <sensible-branch-name>
+    git push <sensible-branch-name> origin/<sensible-branch-name>
+
+
+
+4. Sharing your work within the group
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Within your fork, you should put all your code in your ``Group#`` folder.
+
+When you need to share your work with the others within your group you need to make a :doc:`Pull Request <../git_integration/github-work>` to the `upstream repo <https://github.com/MetOs-UiO/eScience2024-projects>`_ ``main`` branch.
+
+After a Teaching assistant responsible for you group has merged your PR to ``upstream/main`` other members of your group can pull these changes into branches on their forks to work on.
+
+In addition, you will most likely want to create new branches based on the updated ``upstream/main``. See :doc:`Setting up remotes <../git_integration/remotes>`.
diff --git a/_sources/data/ACTRIS-data.rst b/_sources/data/ACTRIS-data.rst
new file mode 100644
index 0000000..08d6970
--- /dev/null
+++ b/_sources/data/ACTRIS-data.rst
@@ -0,0 +1,12 @@
+ACTRIS data
+===========
+
+Access via thredds server from NILU
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Check examples 5-11 in ACTRIS Virtual Research Environment repository
+`ACTRIS and EBAS example notebooks <https://github.com/ACTRIS-Data-Centre/actris-jupyter-hub>`_
+
+
+Check availability via ACTRIS web interface
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+https://ebas-data.nilu.no
diff --git a/_sources/data/Intake-data-acess.ipynb b/_sources/data/Intake-data-acess.ipynb
new file mode 100644
index 0000000..39bd1dc
--- /dev/null
+++ b/_sources/data/Intake-data-acess.ipynb
@@ -0,0 +1,1412 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "19adb0e5",
+   "metadata": {},
+   "source": [
+    "# Acessing model data using intake-esm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ebb99754",
+   "metadata": {},
+   "source": [
+    "To access the CMIP6 model data and CESM-PPE data we created intake catalogs to help browse and subset the data. The catalogs are stored in shared folder `/mnt/craas1-ns9989k-geo4992/data/intake-catalogs/`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "6cc49382",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:52:37.748053Z",
+     "start_time": "2024-05-03T12:52:36.661135Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Importing the required packages\n",
+    "import intake\n",
+    "import xarray as xr\n",
+    "import intake_esm\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d942de23",
+   "metadata": {},
+   "source": [
+    "## Reading and browsing the catalog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "b5a4b54e",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:52:40.300156Z",
+     "start_time": "2024-05-03T12:52:37.749697Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<p><strong>cmip6 catalog with 155 dataset(s) from 536945 asset(s)</strong>:</p> <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unique</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>variable_id</th>\n",
+       "      <td>583</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>table_id</th>\n",
+       "      <td>24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_id</th>\n",
+       "      <td>75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>experiment_id</th>\n",
+       "      <td>94</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>member_id</th>\n",
+       "      <td>190</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>grid_label</th>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>time_range</th>\n",
+       "      <td>9100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>activity_id</th>\n",
+       "      <td>18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>institution_id</th>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>version</th>\n",
+       "      <td>577</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>path</th>\n",
+       "      <td>536945</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>derived_variable_id</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Open the catalog\n",
+    "\n",
+    "# col = intake.open_esm_datastore('https://storage.googleapis.com/cmip6/pangeo-cmip6.json') # Remote Pangeo\n",
+    "\n",
+    "col = intake.open_esm_datastore('/mnt/craas1-ns9989k-geo4992/data/catalogs/cmip6.json') # Local data stored on NIRD\n",
+    "col"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "87ac0d3a",
+   "metadata": {},
+   "source": [
+    "Under the hood `intake-esm` uses a large table csv, which contains some metadata and the paths of where to find it. The data can be stored both locally or in a remote cloud storage i.e `pangeo-cloud`. \n",
+    "\n",
+    "```{note}\n",
+    "Since the paths listed in the csv table are absolute, notebook starting from the same catalog can be run from any directory, without needing to change the in side the notebook paths. \n",
+    "```\n",
+    "\n",
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d06c631",
+   "metadata": {},
+   "source": [
+    "### Browsing the catalog: Comparing the change in AOD over the historical period across CMIP6 models"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "086257e3",
+   "metadata": {},
+   "source": [
+    "The keywords when browsing is columns of the table, e.g. `variable_id`, `source_uid` etc. To list all the keys available for a given key word you can use the `col.unique()['<keyword>']` function. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "a7c13523",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:52:40.378558Z",
+     "start_time": "2024-05-03T12:52:40.301719Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<p><strong>cmip6 catalog with 9 dataset(s) from 190 asset(s)</strong>:</p> <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unique</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>variable_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>table_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_id</th>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>experiment_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>member_id</th>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>grid_label</th>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>time_range</th>\n",
+       "      <td>185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>activity_id</th>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>institution_id</th>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>version</th>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>path</th>\n",
+       "      <td>190</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>derived_variable_id</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "col = col.search(\n",
+    "    variable_id='od550aer',\n",
+    "    experiment_id='histSST'\n",
+    ")\n",
+    "col"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "02c3df7a",
+   "metadata": {},
+   "source": [
+    "Models available for this request:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "efab3400",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:52:40.397129Z",
+     "start_time": "2024-05-03T12:52:40.380735Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['CNRM-ESM2-1',\n",
+       " 'MPI-ESM-1-2-HAM',\n",
+       " 'MIROC6',\n",
+       " 'UKESM1-0-LL',\n",
+       " 'MRI-ESM2-0',\n",
+       " 'GISS-E2-1-G',\n",
+       " 'CESM2-WACCM',\n",
+       " 'GFDL-ESM4',\n",
+       " 'EC-Earth3-AerChem']"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "col.unique()['source_id']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46a4275a",
+   "metadata": {},
+   "source": [
+    "## Loading the data and plotting"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b551425b",
+   "metadata": {},
+   "source": [
+    "```{warning}\n",
+    "The catalog can be huge, always query and subset catalog before loading the data. Preferably down to level of experiment and variable.\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6ae7f5dc",
+   "metadata": {},
+   "source": [
+    "The `.to_dataset_dict` function can accept an optional preprocessing function which can be used to harmonize the datasets, temporal resampling, or slicing.\n",
+    "Below we made a preprocessing function for resampling the data into annual means and calculate the global average to allow for easily plotting the time series. \n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "314301c0",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:52:40.401898Z",
+     "start_time": "2024-05-03T12:52:40.398453Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def resample_calculate_and_global_avg(ds):\n",
+    "    \"\"\"\n",
+    "    Function to resample the data to annual mean and calculate the global average.\n",
+    "    \"\"\"\n",
+    "    ds=ds.resample(time='YE').mean() # Resample to annual mean\n",
+    "    ds = ds.drop_vars(['lat_bnds','lon_bnds'], errors='ignore') # create conflict when calculating global average\n",
+    "    weights = np.cos(np.deg2rad(ds.lat)) # Make weighted global average\n",
+    "    ds_weighted = ds.weighted(weights)\n",
+    "    weighted_mean = ds_weighted.mean(dim=['lon','lat'])\n",
+    "    \n",
+    "    return weighted_mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1c04e261",
+   "metadata": {},
+   "source": [
+    "\n",
+    "```{admonition} Using dask\n",
+    ":class: dropdown\n",
+    "The processing can be done in parallel using dask, which can speed things up a bit.  \n",
+    "The dask cluster below is constrained within the resource each user have available.\n",
+    "The corresponding dask cluster panel can be viewed by clicking on the dask icon <img src=\"https://upload.wikimedia.org/wikipedia/commons/1/12/Dask_Logo.svg\" alt=\"\" width=\"30\" height=\"30\"> on the left-side panel.\n",
+    "```python\n",
+    "from dask.distributed import Client, LocalCluster\n",
+    "client = Client(LocalCluster(n_workers=4, threads_per_worker=1, memory_limit='16GB'))\n",
+    "```\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3fd710d7",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:52:53.705645Z",
+     "start_time": "2024-05-03T12:52:40.403088Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
+      "\t'activity_id.institution_id'\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='9' class='' max='9' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [9/9 00:13&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/conda/envs/pangeo-notebook/lib/python3.11/site-packages/xarray/conventions.py:286: SerializationWarning: variable 'od550aer' has multiple fill values {1e+20, 1e+20} defined, decoding all values to NaN.\n",
+      "  var = coder.decode(var, name=name)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# dataset_dict = col.to_dataset_dict()\n",
+    "dataset_dict = col.to_dataset_dict(xarray_open_kwargs={'use_cftime':True, 'chunks':{'time':48}}, \n",
+    "                           aggregate=True,\n",
+    "                           preprocess=resample_calculate_and_global_avg,\n",
+    "                           skip_on_error=True,\n",
+    "                           xarray_combine_by_coords={'combine_attrs': 'override'} \n",
+    "                          )\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "014fcfcd",
+   "metadata": {},
+   "source": [
+    "Without the providing a `preprocess` function the time aggregated output as dictionary with grouped by the following keys  `\"activity_id\"`, `\"institution_id\"`, `\"source_id\"`, `\"experiment_id\"`, `\"table_id\"`, `\"grid_label\"`.       "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "1b2d8bef",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:53:00.664439Z",
+     "start_time": "2024-05-03T12:52:53.707734Z"
+    },
+    "tags": [
+     "hide-output"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
+      "\t'activity_id.institution_id'\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='9' class='' max='9' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [9/9 00:06&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/conda/envs/pangeo-notebook/lib/python3.11/site-packages/xarray/conventions.py:286: SerializationWarning: variable 'od550aer' has multiple fill values {1e+20, 1e+20} defined, decoding all values to NaN.\n",
+      "  var = coder.decode(var, name=name)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'AerChemMIP.CNRM-CERFACS': <xarray.Dataset> Size: 260MB\n",
+       " Dimensions:      (lat: 128, lon: 256, time: 1980, axis_nbounds: 2, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * lat          (lat) float64 1kB -88.93 -87.54 -86.14 ... 86.14 87.54 88.93\n",
+       "   * lon          (lon) float64 2kB 0.0 1.406 2.812 4.219 ... 355.8 357.2 358.6\n",
+       "   * time         (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
+       "   * member_id    (member_id) object 8B 'r1i1p1f2'\n",
+       " Dimensions without coordinates: axis_nbounds\n",
+       " Data variables:\n",
+       "     time_bounds  (time, axis_nbounds) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n",
+       "     od550aer     (member_id, time, lat, lon) float32 260MB dask.array<chunksize=(1, 48, 128, 256), meta=np.ndarray>\n",
+       " Attributes: (12/65)\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     creation_date:                    2018-08-08T14:22:32Z\n",
+       "     description:                      Historical transient with SSTs prescrib...\n",
+       "     title:                            CNRM-ESM2-1 model output prepared for C...\n",
+       "     activity_id:                      AerChemMIP\n",
+       "     contact:                          contact.cmip@meteo.fr\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  CNRM-CERFACS\n",
+       "     intake_esm_attrs:version:         v20190621\n",
+       "     intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.CNRM-CERFACS,\n",
+       " 'AerChemMIP.NOAA-GFDL': <xarray.Dataset> Size: 411MB\n",
+       " Dimensions:    (bnds: 2, lat: 180, lon: 288, member_id: 1, time: 1980)\n",
+       " Coordinates:\n",
+       "   * bnds       (bnds) float64 16B 1.0 2.0\n",
+       "   * lat        (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "     lat_bnds   (lat, bnds) float64 3kB dask.array<chunksize=(180, 2), meta=np.ndarray>\n",
+       "   * lon        (lon) float64 2kB 0.625 1.875 3.125 4.375 ... 356.9 358.1 359.4\n",
+       "     lon_bnds   (lon, bnds) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "   * time       (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
+       "     time_bnds  (time, bnds) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n",
+       "   * member_id  (member_id) object 8B 'r1i1p1f1'\n",
+       " Data variables:\n",
+       "     od550aer   (member_id, time, lat, lon) float32 411MB dask.array<chunksize=(1, 48, 180, 288), meta=np.ndarray>\n",
+       " Attributes: (12/56)\n",
+       "     external_variables:               areacella\n",
+       "     history:                          File was processed by fremetar (GFDL an...\n",
+       "     table_id:                         AERmon\n",
+       "     activity_id:                      AerChemMIP\n",
+       "     branch_method:                    atmospheric and land state taken from p...\n",
+       "     branch_time_in_child:             0.0\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:grid_label:      gr1\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  NOAA-GFDL\n",
+       "     intake_esm_attrs:version:         v20180701\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.NOAA-GFDL,\n",
+       " 'AerChemMIP.NCAR': <xarray.Dataset> Size: 438MB\n",
+       " Dimensions:    (member_id: 1, time: 1980, lat: 192, lon: 288, nbnd: 2)\n",
+       " Coordinates:\n",
+       "   * lat        (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0\n",
+       "   * lon        (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
+       "   * time       (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00\n",
+       "     time_bnds  (time, nbnd) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n",
+       "     lat_bnds   (lat, nbnd) float32 2kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "     lon_bnds   (lon, nbnd) float32 2kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "   * member_id  (member_id) object 8B 'r1i2p1f1'\n",
+       " Dimensions without coordinates: nbnd\n",
+       " Data variables:\n",
+       "     od550aer   (member_id, time, lat, lon) float32 438MB dask.array<chunksize=(1, 48, 192, 288), meta=np.ndarray>\n",
+       " Attributes: (12/56)\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     activity_id:                      AerChemMIP\n",
+       "     branch_method:                    no parent\n",
+       "     branch_time_in_child:             674885.0\n",
+       "     branch_time_in_parent:            0.0\n",
+       "     case_id:                          47\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  NCAR\n",
+       "     intake_esm_attrs:version:         v20190531\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.NCAR,\n",
+       " 'AerChemMIP.NASA-GISS': <xarray.Dataset> Size: 103MB\n",
+       " Dimensions:    (time: 1980, bnds: 2, lat: 90, lon: 144, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time       (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
+       "     time_bnds  (time, bnds) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n",
+       "   * lat        (lat) float64 720B -89.0 -87.0 -85.0 -83.0 ... 85.0 87.0 89.0\n",
+       "     lat_bnds   (lat, bnds) float64 1kB dask.array<chunksize=(90, 2), meta=np.ndarray>\n",
+       "   * lon        (lon) float64 1kB 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "     lon_bnds   (lon, bnds) float64 2kB dask.array<chunksize=(144, 2), meta=np.ndarray>\n",
+       "   * member_id  (member_id) object 8B 'r1i1p3f1'\n",
+       " Dimensions without coordinates: bnds\n",
+       " Data variables:\n",
+       "     od550aer   (member_id, time, lat, lon) float32 103MB dask.array<chunksize=(1, 48, 90, 144), meta=np.ndarray>\n",
+       " Attributes: (12/56)\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     activity_id:                      AerChemMIP\n",
+       "     branch_method:                    standard\n",
+       "     branch_time_in_child:             0.0\n",
+       "     branch_time_in_parent:            0.0\n",
+       "     contact:                          Kenneth Lo (cdkkl@giss.nasa.gov)\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  NASA-GISS\n",
+       "     intake_esm_attrs:version:         v20191120\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.NASA-GISS,\n",
+       " 'AerChemMIP.MIROC': <xarray.Dataset> Size: 260MB\n",
+       " Dimensions:     (time: 1980, bnds: 2, lat: 128, lon: 256, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time        (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
+       "     time_bnds   (time, bnds) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n",
+       "   * lat         (lat) float64 1kB -88.93 -87.54 -86.14 ... 86.14 87.54 88.93\n",
+       "     lat_bnds    (lat, bnds) float64 2kB dask.array<chunksize=(128, 2), meta=np.ndarray>\n",
+       "   * lon         (lon) float64 2kB 0.0 1.406 2.812 4.219 ... 355.8 357.2 358.6\n",
+       "     lon_bnds    (lon, bnds) float64 4kB dask.array<chunksize=(256, 2), meta=np.ndarray>\n",
+       "     wavelength  float64 8B 550.0\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f1'\n",
+       " Dimensions without coordinates: bnds\n",
+       " Data variables:\n",
+       "     od550aer    (member_id, time, lat, lon) float32 260MB dask.array<chunksize=(1, 48, 128, 256), meta=np.ndarray>\n",
+       " Attributes: (12/53)\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     activity_id:                      AerChemMIP\n",
+       "     branch_method:                    standard\n",
+       "     branch_time_in_child:             0.0\n",
+       "     branch_time_in_parent:            0.0\n",
+       "     data_specs_version:               01.00.31\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  MIROC\n",
+       "     intake_esm_attrs:version:         v20190828\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.MIROC,\n",
+       " 'AerChemMIP.MOHC': <xarray.Dataset> Size: 219MB\n",
+       " Dimensions:     (time: 1980, bnds: 2, lat: 144, lon: 192, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time        (time) object 16kB 1850-01-16 00:00:00 ... 2014-12-16 00:00:00\n",
+       "     time_bnds   (time, bnds) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n",
+       "   * lat         (lat) float64 1kB -89.38 -88.12 -86.88 ... 86.88 88.12 89.38\n",
+       "     lat_bnds    (lat, bnds) float64 2kB dask.array<chunksize=(144, 2), meta=np.ndarray>\n",
+       "   * lon         (lon) float64 2kB 0.9375 2.812 4.688 6.562 ... 355.3 357.2 359.1\n",
+       "     lon_bnds    (lon, bnds) float64 3kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "     wavelength  float64 8B 550.0\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f2'\n",
+       " Dimensions without coordinates: bnds\n",
+       " Data variables:\n",
+       "     od550aer    (member_id, time, lat, lon) float32 219MB dask.array<chunksize=(1, 48, 144, 192), meta=np.ndarray>\n",
+       " Attributes: (12/56)\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     activity_id:                      AerChemMIP\n",
+       "     branch_time_in_child:             0.0\n",
+       "     data_specs_version:               01.00.29\n",
+       "     experiment:                       historical prescribed SSTs and historic...\n",
+       "     experiment_id:                    histSST\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  MOHC\n",
+       "     intake_esm_attrs:version:         v20190902\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.MOHC,\n",
+       " 'AerChemMIP.MRI': <xarray.Dataset> Size: 406MB\n",
+       " Dimensions:     (time: 1980, bnds: 2, lat: 160, lon: 320, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time        (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
+       "   * lat         (lat) float64 1kB -89.14 -88.03 -86.91 ... 86.91 88.03 89.14\n",
+       "   * lon         (lon) float64 3kB 0.0 1.125 2.25 3.375 ... 356.6 357.8 358.9\n",
+       "     wavelength  float64 8B ...\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f1'\n",
+       " Dimensions without coordinates: bnds\n",
+       " Data variables:\n",
+       "     time_bnds   (time, bnds) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n",
+       "     lat_bnds    (lat, bnds) float64 3kB dask.array<chunksize=(160, 2), meta=np.ndarray>\n",
+       "     lon_bnds    (lon, bnds) float64 5kB dask.array<chunksize=(320, 2), meta=np.ndarray>\n",
+       "     od550aer    (member_id, time, lat, lon) float32 406MB dask.array<chunksize=(1, 48, 160, 320), meta=np.ndarray>\n",
+       " Attributes: (12/59)\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     activity_id:                      AerChemMIP\n",
+       "     branch_method:                    standard (the actual parent run: RFMIP ...\n",
+       "     branch_time_in_child:             0.0\n",
+       "     branch_time_in_parent:            0.0\n",
+       "     comment:                          This od550aer includes AOD from stratos...\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  MRI\n",
+       "     intake_esm_attrs:version:         v20200207\n",
+       "     intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.MRI,\n",
+       " 'AerChemMIP.HAMMOZ-Consortium': <xarray.Dataset> Size: 146MB\n",
+       " Dimensions:     (time: 1980, bnds: 2, lat: 96, lon: 192, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time        (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
+       "     time_bnds   (time, bnds) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n",
+       "   * lat         (lat) float64 768B -88.57 -86.72 -84.86 ... 84.86 86.72 88.57\n",
+       "     lat_bnds    (lat, bnds) float64 2kB dask.array<chunksize=(96, 2), meta=np.ndarray>\n",
+       "   * lon         (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1\n",
+       "     lon_bnds    (lon, bnds) float64 3kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "     wavelength  float64 8B 550.0\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f1'\n",
+       " Dimensions without coordinates: bnds\n",
+       " Data variables:\n",
+       "     od550aer    (member_id, time, lat, lon) float32 146MB dask.array<chunksize=(1, 48, 96, 192), meta=np.ndarray>\n",
+       " Attributes: (12/57)\n",
+       "     CDO:                              Climate Data Operators version 1.9.9rc8...\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     activity_id:                      AerChemMIP\n",
+       "     branch_method:                    standard\n",
+       "     branch_time_in_child:             0.0\n",
+       "     branch_time_in_parent:            0.0\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  HAMMOZ-Consortium\n",
+       "     intake_esm_attrs:version:         v20190628\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.HAMMOZ-Consortium,\n",
+       " 'CMIP.EC-Earth-Consortium': <xarray.Dataset> Size: 86MB\n",
+       " Dimensions:     (time: 1980, bnds: 2, lat: 90, lon: 120, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time        (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
+       "     time_bnds   (time, bnds) object 32kB dask.array<chunksize=(12, 2), meta=np.ndarray>\n",
+       "   * lat         (lat) float64 720B -89.0 -87.0 -85.0 -83.0 ... 85.0 87.0 89.0\n",
+       "     lat_bnds    (lat, bnds) float64 1kB dask.array<chunksize=(90, 2), meta=np.ndarray>\n",
+       "   * lon         (lon) float64 960B 1.5 4.5 7.5 10.5 ... 349.5 352.5 355.5 358.5\n",
+       "     lon_bnds    (lon, bnds) float64 2kB dask.array<chunksize=(120, 2), meta=np.ndarray>\n",
+       "     wavelength  float64 8B 550.0\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f1'\n",
+       " Dimensions without coordinates: bnds\n",
+       " Data variables:\n",
+       "     od550aer    (member_id, time, lat, lon) float32 86MB dask.array<chunksize=(1, 12, 90, 120), meta=np.ndarray>\n",
+       " Attributes: (12/57)\n",
+       "     Conventions:                        CF-1.7 CMIP-6.2\n",
+       "     activity_id:                        AerChemMIP\n",
+       "     branch_method:                      standard\n",
+       "     branch_time_in_child:               0.0\n",
+       "     branch_time_in_parent:              0.0\n",
+       "     contact:                            cmip6-data@ec-earth.org\n",
+       "     ...                                 ...\n",
+       "     intake_esm_attrs:grid_label:        gn\n",
+       "     intake_esm_attrs:activity_id:       CMIP\n",
+       "     intake_esm_attrs:institution_id:    EC-Earth-Consortium\n",
+       "     intake_esm_attrs:version:           v20210309\n",
+       "     intake_esm_attrs:_data_format_:     netcdf\n",
+       "     intake_esm_dataset_key:             CMIP.EC-Earth-Consortium}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "col.to_dataset_dict(xarray_open_kwargs={'use_cftime':True, 'chunks':{'time':48}}, \n",
+    "                           aggregate=True,\n",
+    "                           skip_on_error=True,\n",
+    "                           xarray_combine_by_coords={'combine_attrs': 'override'} \n",
+    "                          )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "92cbf62a",
+   "metadata": {},
+   "source": [
+    "Preprocess dictionary only contain the time series, which is easy to loop over and plot for each model. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "5da56331",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:53:00.676386Z",
+     "start_time": "2024-05-03T12:53:00.666493Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'AerChemMIP.NASA-GISS': <xarray.Dataset> Size: 3kB\n",
+       " Dimensions:    (time: 165, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time       (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00\n",
+       "   * member_id  (member_id) object 8B 'r1i1p3f1'\n",
+       " Data variables:\n",
+       "     od550aer   (member_id, time) float64 1kB dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
+       " Attributes:\n",
+       "     intake_esm_vars:                  ['od550aer']\n",
+       "     intake_esm_attrs:variable_id:     od550aer\n",
+       "     intake_esm_attrs:table_id:        AERmon\n",
+       "     intake_esm_attrs:source_id:       GISS-E2-1-G\n",
+       "     intake_esm_attrs:experiment_id:   histSST\n",
+       "     intake_esm_attrs:member_id:       r1i1p3f1\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  NASA-GISS\n",
+       "     intake_esm_attrs:version:         v20191120\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.NASA-GISS,\n",
+       " 'AerChemMIP.CNRM-CERFACS': <xarray.Dataset> Size: 3kB\n",
+       " Dimensions:    (time: 165, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time       (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00\n",
+       "   * member_id  (member_id) object 8B 'r1i1p1f2'\n",
+       " Data variables:\n",
+       "     od550aer   (member_id, time) float64 1kB dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
+       " Attributes: (12/14)\n",
+       "     intake_esm_vars:                  ['od550aer']\n",
+       "     intake_esm_attrs:variable_id:     od550aer\n",
+       "     intake_esm_attrs:table_id:        AERmon\n",
+       "     intake_esm_attrs:source_id:       CNRM-ESM2-1\n",
+       "     intake_esm_attrs:experiment_id:   histSST\n",
+       "     intake_esm_attrs:member_id:       r1i1p1f2\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  CNRM-CERFACS\n",
+       "     intake_esm_attrs:version:         v20190621\n",
+       "     intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.CNRM-CERFACS,\n",
+       " 'AerChemMIP.NCAR': <xarray.Dataset> Size: 3kB\n",
+       " Dimensions:    (time: 165, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time       (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00\n",
+       "   * member_id  (member_id) object 8B 'r1i2p1f1'\n",
+       " Data variables:\n",
+       "     od550aer   (member_id, time) float64 1kB dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
+       " Attributes:\n",
+       "     intake_esm_vars:                  ['od550aer']\n",
+       "     intake_esm_attrs:variable_id:     od550aer\n",
+       "     intake_esm_attrs:table_id:        AERmon\n",
+       "     intake_esm_attrs:source_id:       CESM2-WACCM\n",
+       "     intake_esm_attrs:experiment_id:   histSST\n",
+       "     intake_esm_attrs:member_id:       r1i2p1f1\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  NCAR\n",
+       "     intake_esm_attrs:version:         v20190531\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.NCAR,\n",
+       " 'AerChemMIP.NOAA-GFDL': <xarray.Dataset> Size: 3kB\n",
+       " Dimensions:    (time: 165, member_id: 1)\n",
+       " Coordinates:\n",
+       "   * time       (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00\n",
+       "   * member_id  (member_id) object 8B 'r1i1p1f1'\n",
+       " Data variables:\n",
+       "     od550aer   (member_id, time) float64 1kB dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
+       " Attributes:\n",
+       "     intake_esm_vars:                  ['od550aer']\n",
+       "     intake_esm_attrs:variable_id:     od550aer\n",
+       "     intake_esm_attrs:table_id:        AERmon\n",
+       "     intake_esm_attrs:source_id:       GFDL-ESM4\n",
+       "     intake_esm_attrs:experiment_id:   histSST\n",
+       "     intake_esm_attrs:member_id:       r1i1p1f1\n",
+       "     intake_esm_attrs:grid_label:      gr1\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  NOAA-GFDL\n",
+       "     intake_esm_attrs:version:         v20180701\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.NOAA-GFDL,\n",
+       " 'AerChemMIP.MIROC': <xarray.Dataset> Size: 3kB\n",
+       " Dimensions:     (time: 165, member_id: 1)\n",
+       " Coordinates:\n",
+       "     wavelength  float64 8B 550.0\n",
+       "   * time        (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f1'\n",
+       " Data variables:\n",
+       "     od550aer    (member_id, time) float64 1kB dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
+       " Attributes:\n",
+       "     intake_esm_vars:                  ['od550aer']\n",
+       "     intake_esm_attrs:variable_id:     od550aer\n",
+       "     intake_esm_attrs:table_id:        AERmon\n",
+       "     intake_esm_attrs:source_id:       MIROC6\n",
+       "     intake_esm_attrs:experiment_id:   histSST\n",
+       "     intake_esm_attrs:member_id:       r1i1p1f1\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  MIROC\n",
+       "     intake_esm_attrs:version:         v20190828\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.MIROC,\n",
+       " 'AerChemMIP.MOHC': <xarray.Dataset> Size: 3kB\n",
+       " Dimensions:     (time: 165, member_id: 1)\n",
+       " Coordinates:\n",
+       "     wavelength  float64 8B 550.0\n",
+       "   * time        (time) object 1kB 1850-12-30 00:00:00 ... 2014-12-30 00:00:00\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f2'\n",
+       " Data variables:\n",
+       "     od550aer    (member_id, time) float64 1kB dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
+       " Attributes:\n",
+       "     intake_esm_vars:                  ['od550aer']\n",
+       "     intake_esm_attrs:variable_id:     od550aer\n",
+       "     intake_esm_attrs:table_id:        AERmon\n",
+       "     intake_esm_attrs:source_id:       UKESM1-0-LL\n",
+       "     intake_esm_attrs:experiment_id:   histSST\n",
+       "     intake_esm_attrs:member_id:       r1i1p1f2\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  MOHC\n",
+       "     intake_esm_attrs:version:         v20190902\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.MOHC,\n",
+       " 'AerChemMIP.HAMMOZ-Consortium': <xarray.Dataset> Size: 3kB\n",
+       " Dimensions:     (time: 165, member_id: 1)\n",
+       " Coordinates:\n",
+       "     wavelength  float64 8B 550.0\n",
+       "   * time        (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f1'\n",
+       " Data variables:\n",
+       "     od550aer    (member_id, time) float64 1kB dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
+       " Attributes:\n",
+       "     intake_esm_vars:                  ['od550aer']\n",
+       "     intake_esm_attrs:variable_id:     od550aer\n",
+       "     intake_esm_attrs:table_id:        AERmon\n",
+       "     intake_esm_attrs:source_id:       MPI-ESM-1-2-HAM\n",
+       "     intake_esm_attrs:experiment_id:   histSST\n",
+       "     intake_esm_attrs:member_id:       r1i1p1f1\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  HAMMOZ-Consortium\n",
+       "     intake_esm_attrs:version:         v20190628\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.HAMMOZ-Consortium,\n",
+       " 'AerChemMIP.MRI': <xarray.Dataset> Size: 3kB\n",
+       " Dimensions:     (time: 165, member_id: 1)\n",
+       " Coordinates:\n",
+       "     wavelength  float64 8B 550.0\n",
+       "   * time        (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f1'\n",
+       " Data variables:\n",
+       "     od550aer    (member_id, time) float64 1kB dask.array<chunksize=(1, 4), meta=np.ndarray>\n",
+       " Attributes: (12/14)\n",
+       "     intake_esm_vars:                  ['od550aer']\n",
+       "     intake_esm_attrs:variable_id:     od550aer\n",
+       "     intake_esm_attrs:table_id:        AERmon\n",
+       "     intake_esm_attrs:source_id:       MRI-ESM2-0\n",
+       "     intake_esm_attrs:experiment_id:   histSST\n",
+       "     intake_esm_attrs:member_id:       r1i1p1f1\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:activity_id:     AerChemMIP\n",
+       "     intake_esm_attrs:institution_id:  MRI\n",
+       "     intake_esm_attrs:version:         v20200207\n",
+       "     intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           AerChemMIP.MRI,\n",
+       " 'CMIP.EC-Earth-Consortium': <xarray.Dataset> Size: 3kB\n",
+       " Dimensions:     (time: 165, member_id: 1)\n",
+       " Coordinates:\n",
+       "     wavelength  float64 8B 550.0\n",
+       "   * time        (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00\n",
+       "   * member_id   (member_id) object 8B 'r1i1p1f1'\n",
+       " Data variables:\n",
+       "     od550aer    (member_id, time) float64 1kB dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
+       " Attributes:\n",
+       "     intake_esm_vars:                  ['od550aer']\n",
+       "     intake_esm_attrs:variable_id:     od550aer\n",
+       "     intake_esm_attrs:table_id:        AERmon\n",
+       "     intake_esm_attrs:source_id:       EC-Earth3-AerChem\n",
+       "     intake_esm_attrs:experiment_id:   histSST\n",
+       "     intake_esm_attrs:member_id:       r1i1p1f1\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:activity_id:     CMIP\n",
+       "     intake_esm_attrs:institution_id:  EC-Earth-Consortium\n",
+       "     intake_esm_attrs:version:         v20210309\n",
+       "     intake_esm_attrs:_data_format_:   netcdf\n",
+       "     intake_esm_dataset_key:           CMIP.EC-Earth-Consortium}"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "2bf4c27a",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:54:52.226978Z",
+     "start_time": "2024-05-03T12:53:00.677955Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fa1fc40f110>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots(figsize=(10,6))\n",
+    "for datakey, data in dataset_dict.items(): # Looping over ever varable in the dictionary\n",
+    "    source_id = data.attrs['intake_esm_attrs:source_id']\n",
+    "    member_id = data.attrs['intake_esm_attrs:member_id']\n",
+    "    data['od550aer'].isel(member_id=0).plot(label=f'{source_id} {member_id}', ax=ax)\n",
+    "\n",
+    "ax.legend()\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2ecfe25e",
+   "metadata": {},
+   "source": [
+    "### Exporting a subset of the catalog"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "18e01884",
+   "metadata": {},
+   "source": [
+    "Most likely you will only be analyzing a small subset of experiments the model experiment and it could be beneficial to work with a reduced catalog. \n",
+    "Below we will make a subset that only contain the information related to `histSST` and `histSST-piaer`, and only the absorption optical depth (`od550abs`) and total optical depth (`od550aer`). "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "d4d015f4",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:54:53.492592Z",
+     "start_time": "2024-05-03T12:54:52.229732Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "col = intake.open_esm_datastore('/mnt/craas1-ns9989k-geo4992/data/cmip6.json') # Local data stored on NIRD"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "3e57386d",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:54:53.645026Z",
+     "start_time": "2024-05-03T12:54:53.493934Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<p><strong>cmip6 catalog with 9 dataset(s) from 190 asset(s)</strong>:</p> <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unique</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>variable_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>table_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_id</th>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>experiment_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>member_id</th>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>grid_label</th>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>time_range</th>\n",
+       "      <td>185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>activity_id</th>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>institution_id</th>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>version</th>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>path</th>\n",
+       "      <td>190</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>derived_variable_id</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "col = col.search(    \n",
+    "    experiment_id=['histSST', 'histSST-piaer'],\n",
+    "    variable_id = ['od550abs', 'od550aer']\n",
+    ")\n",
+    "col"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d5678e30",
+   "metadata": {},
+   "source": [
+    "Then when we are happy with the selection the catalog can be exported as follows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "8131074a",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:54:53.652854Z",
+     "start_time": "2024-05-03T12:54:53.646372Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Successfully wrote ESM catalog json file to: file:///home/fc-3auid-3a9fdc0c87-2d7836-2d4bdc-2db802-2d9a250c322e3b//histSST-AerChemMIP.json\n"
+     ]
+    }
+   ],
+   "source": [
+    "col.serialize(name='histSST-AerChemMIP',catalog_type='file',directory='~/')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "90b4c58e",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-03T12:54:53.675734Z",
+     "start_time": "2024-05-03T12:54:53.654084Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<p><strong>histSST-AerChemMIP catalog with 9 dataset(s) from 190 asset(s)</strong>:</p> <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unique</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>variable_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>table_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_id</th>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>experiment_id</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>member_id</th>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>grid_label</th>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>time_range</th>\n",
+       "      <td>185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>activity_id</th>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>institution_id</th>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>version</th>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>path</th>\n",
+       "      <td>190</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>derived_variable_id</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "col = intake.open_esm_datastore('~/histSST-AerChemMIP.json')\n",
+    "col"
+   ]
+  }
+ ],
+ "metadata": {
+  "celltoolbar": "Edit Metadata",
+  "kernelspec": {
+   "display_name": "Python [conda env:pangeo-notebook]",
+   "language": "python",
+   "name": "conda-env-pangeo-notebook-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/_sources/data/index.rst b/_sources/data/index.rst
new file mode 100644
index 0000000..12b3c67
--- /dev/null
+++ b/_sources/data/index.rst
@@ -0,0 +1,12 @@
+Data
+====
+
+.. toctree::
+   :maxdepth: 1
+   :titlesonly:
+   :glob:
+
+   Intake-data-acess.ipynb
+   local-data
+   ACTRIS-data
+
diff --git a/_sources/data/local-data.rst b/_sources/data/local-data.rst
new file mode 100644
index 0000000..9038b8b
--- /dev/null
+++ b/_sources/data/local-data.rst
@@ -0,0 +1,11 @@
+Local shared data
+=================
+
+Direct local data access
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+Mounted data directories:
+- ``~/shared-craas1-nn9989k-geo4992/data/`` - data shared during this course.
+- ``~/shared-craas1-nn9989k-cmip6/`` subset of CMIP6 data from ESGF.
+- ``~/shared-craas1-nn9989k-ns9560k/CAM6_CESM_PPE`` CAM6 output for Perturbed Parameter Experiment
+- ``~/shared-craas1-nn9989k-ns9560k/``
\ No newline at end of file
diff --git a/_sources/feide.rst b/_sources/feide.rst
new file mode 100644
index 0000000..6d3a10b
--- /dev/null
+++ b/_sources/feide.rst
@@ -0,0 +1,65 @@
+Jupyterhub access
+===================
+
+
+Creating Feide OpenIdP account:
+-------------------------------
+
+If you do not have a Feide account follow these instructions:
+
+  - Go to `Feide OpenIdP <https://openidp.feide.no/>`_.
+
+  - Click on `Register a new account <https://openidp.feide.no/simplesaml/module.php/selfregister/newUser.php>`_. Preferably provide the email you specified for the course.
+
+  - You will receive an email from Feide OpenIdP \<noreply@sikt.no\>
+
+  .. note::
+     You might need to check your spam/junk folder
+
+  - Click on the link in the email and proceed with further registration.
+
+  - Now you have FEIDE **guest** account.
+
+Joining eScience2024 Feide group:
+---------------------------------
+
+Once you created a FEIDE account (or if you already have one):
+
+  - You might have already received the invitation to a FEIDE group eScience2024 by email. If not, send email to Matvey Debolskiy <matveyd@uio.no>.
+
+  - Click on the link in the email. You will be suggested to login in into dataporten.
+ 
+  - Login using your FEIDE account 
+
+  .. note::
+
+     For those with FEIDE guest accounts:
+      - Click ``Can't find your user account?``
+      - Choose ``Feide guest users``, you would be promted to the OpenIdP login page.
+
+  - Accept policies and become member of **eScience2024** Feide group
+
+
+Accessing Jupyterhub:
+---------------------
+
+Once you've become a memeber of **escience2024** Feide group you can use Jupyterhub for eScience2024 cource at `<https://escience2024.craas1.sigma2.no>`_.
+
+
+
+  - Press ``Sing in with NIRD Apps Auth``.
+
+  - Login with your Feide or Feide guest account. 
+
+  .. collapse:: Feide Guests
+
+     For those with FEIDE guest accounts:
+      - Click ``Can't find your user account?``
+      - Choose ``Feide guest users``, you would be promted to the OpenIdP login page.
+
+
+.. warning:: **Test server access**
+
+  Though `test sever <https://escience2024-test.craas1.sigma2.no>`_ is still reachable but will be shutdown soon.
+  So if you have anything there, move it to escience2024 server. If you  need help ask **@mvdeoblskiy**.
+
diff --git a/_sources/git_integration/git_jlab.rst b/_sources/git_integration/git_jlab.rst
new file mode 100644
index 0000000..ae3ef07
--- /dev/null
+++ b/_sources/git_integration/git_jlab.rst
@@ -0,0 +1,112 @@
+Starting with git on the jupyterhub
+===================================
+
+
+Adding your git username and email
+----------------------------------
+
+First thing that you would want to do is to add your github username and email to the ``git config``.
+To do that, open a terminal (f.e. through launcher) and do:
+
+.. code-block:: bash
+
+
+   git config --global user.name "<your_username>"
+   git config --global user.email "<your_email>"
+
+You can check if the config is added by doing ``git config --get user.name``.
+
+Using git GUI extension:
+------------------------
+
+.. |gitico| image:: img/git_ico.png
+
+.. |ppbuttons| image:: img/push-pull-gui.png
+
+Jupyterlab includes a GUI to make it easier to use git.
+You can see a git icon |gitico| on the left panel. To clone a repository, click on the icon and then on **Clone Reopsitory**. 
+You should see the following prompt:
+
+.. image:: img/clone-repo.png
+   :width: 800
+   :alt: Cloning repo GUI
+
+Check both boxes and press **Clone**. You will get the following prompt:
+
+.. image:: img/gui-credentials.png
+   :width: 300
+   :alt: Credentials prompt GUI
+
+If you do not know what a personal access token is follow `official github instructions <https://docs.github.com/en/enterprise-server@3.9/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens>`_ to create one. Usually, the tokens start with ``ghp_***``. Treat this token as a password. 
+Once you've logged in you will see in the file browser that a folder was created with the same name as the repo you have cloned.
+Go into that folder in the file browser and then click on the git tab |gitico| in the left panel. You will see the following:
+
+.. image:: img/repo-tab.png
+   :width: 200
+   :alt: Repo tab GUI
+
+You can hover over different tabs and buttons too see what they do.
+If you click on **History** tab, you will see the beautiful graph of the commit-history of the branch you are currently on.
+You can clone multiple repositories and if you are in some repo folder within your file browser you can always click on the git icon to use version control for that specific repository.
+
+Pulling and pushing and fetching are done using the cloud buttons |ppbuttons| at the top right of the panel.
+
+Using git CLI
+-------------
+
+You can also use git within the command line.
+To do that, Open a terminal through the **Launcher**. That will open the terminal at your current directory.
+To see the absolute path of where are you at use ``pwd``. Now, we will clone a repository that we use for the course (assuming you made a fork of it).
+
+.. code-block:: bash
+
+  git clone <repository url> <folder>
+
+  cd <folder>
+
+If the ``folder`` is not provided, the repository will be cloned into a folder with the same name as a repository.
+Since we are using private repositories, you will get promoted to authenticate. Use your github username and `token  <https://docs.github.com/en/enterprise-server@3.9/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens>`_.
+
+Once you are in the repo folder. You can create a new branch for a feature/piece of work you will be working on, so you can make a pull request to the upstream repo later.
+To see what branch are you on right now and any changes you have made use ``git status``.
+
+.. code-block:: bash
+
+  git switch -c my-new-branch
+
+  git status
+
+You will see that you just created a new branch and that you are up-to-date with it. Note, this branch is local and does not exist yet on github repo.
+
+Now, suppose you made some changes to a file ``file.txt``. You want to commit the changes and than push it to the remote (your repo on git hub). To commit your changes, you can add a single file, multiple files or all the changes.
+
+.. code-block:: bash
+
+  #this will stage a single file
+  git add file.txt
+  #this will stage multiple files
+  git add file1.txt file2.txt ...
+
+To commit the files you have staged:
+
+.. code-block:: bash
+
+  git commit -m "commit-message, changed file.txt"
+
+You can commit all the changes at once:
+
+.. code-block:: bash
+
+  git commit -a -m "changed bunch of stuff"
+
+Once you've made commits, you want to push them to the remote repository:
+
+.. code-block:: bash
+
+  #--set-upstream origin my-new-branch is only needed once
+  # for every newly created branch to push it along with commits.
+  git push --set-upstream origin my-new-branch
+  # after that you can just simply do:
+  git push
+
+To pull changes from the remote to your local repo use ``git pull``. To get updated history (branches, tags etc) from the remote use ``git fetch -a``.
\ No newline at end of file
diff --git a/_sources/git_integration/github-work.rst b/_sources/git_integration/github-work.rst
new file mode 100644
index 0000000..46a86fe
--- /dev/null
+++ b/_sources/git_integration/github-work.rst
@@ -0,0 +1,56 @@
+Pull requests and Issues
+========================
+
+
+Issues
+======
+
+Let's say you have found a bug in the code or want to request propose some new functionality for a code that is in some repo on GitHub.
+A good way to do it is to use Issues to keep the track record.
+
+On the GitHub web-page associated with the repo, you can find an Issues tab.
+
+.. image:: img/issues-tab.png
+   :width: 800
+   :alt: Issues
+
+
+There, you will see opened and closed issues, search through them, sort etc. To create a new Issue simply click on ``New Issue`` on the right.
+
+.. image:: img/new-issue.png
+   :width: 800
+   :alt: New Issue
+
+GitHub uses MarkDown with some extra features for formatting comments and messages ont GitHub web-pages.
+You can read about the basics of formatting on the `github documentation <https://docs.github.com/en/get-started/writing-on-github/getting-started-with-writing-and-formatting-on-github/basic-writing-and-formatting-syntax>`_.
+
+Pull requests
+-------------
+
+When you have developed some code and want other people to use it. For that, you will need to create a Pull Request.
+There is a Pull Requests tab near the Issues tab on the GitHub page of your repository. If you click on it, you will get similar page as the one for Issues:
+
+.. image:: img/pr-tab.png
+   :width: 800
+   :alt: Pull Requests
+
+When you click on the ``New Pull Request`` you will see a promt to choose which branch you are pulling from and which you are pulling into:
+
+.. image:: img/new-pr.png
+   :width: 800
+   :alt: Pull Requests
+
+``base repository`` and ``base`` correspond to the repo and branch you want your changes to **go in**.
+
+``head repository`` and ``compare`` correspond to the repo and branch you want changes **from**.
+
+.. attention:: 
+  :class: toggle
+
+  When submitting a Pull Request, double check that you are pulling the intended branch into intended remote.
+
+
+After you have chosen correct branches, you will see the comparison between them if you scroll down.
+To create a Pull Request click on **Create pull request**. Now you will se a page similar to the one you get when creating a new issue.
+Give your PR a meaningful title and description and check ``Allow edits by maintainers`` if you want people responsible for the repo your are pulling into to have access to your branch associated with the PR. 
+You can also request specific maintainers/users to review you PR. After you are done, press **Create pull request** again. 
\ No newline at end of file
diff --git a/_sources/git_integration/index.rst b/_sources/git_integration/index.rst
new file mode 100644
index 0000000..5ec10b3
--- /dev/null
+++ b/_sources/git_integration/index.rst
@@ -0,0 +1,9 @@
+Using version control on Jupyterhub:
+====================================
+
+.. toctree::
+   :maxdepth: 1
+
+   git_jlab
+   remotes
+   github-work
diff --git a/_sources/git_integration/remotes.rst b/_sources/git_integration/remotes.rst
new file mode 100644
index 0000000..eac10aa
--- /dev/null
+++ b/_sources/git_integration/remotes.rst
@@ -0,0 +1,61 @@
+Setting up remotes
+==================
+
+
+Since we are working with two repositories: your fork and the repository you forked from, you might want to set up your local repo to see them both.
+In order to do that you would have to use terminal even if you use GUI for committing/pushing.
+
+In git, remotes are repositories somewhere on the server (gitlab/github) that are not present locally on your machine.
+When you clone a repository and create a branch you generally want your branch to track some other branch on one of the remotes (usually with the same name).
+
+That's why you need to do ``git push --set-origin <remote-name> <branch-name>`` whe you first push a branch you have created locally with ``git switch -c <branch-name>``.
+
+Adding remotes
+~~~~~~~~~~~~~~
+
+Here we will add an ``upstream`` repository to the clone of your fork.
+Assuming you have cloned your fork and are currently in the folder that contains it. Open a terminal:
+
+.. code-block:: bash
+
+  git remote add upstream <url-of-the-repo-you-forked-from>
+  #check if the remote is added
+  git remote -v
+  #get all the branches/tags from newly added remote:
+  git fetch upstream
+
+Now, you have successfully added the upstream remote to your clone.
+
+.. note::
+  If you are using GUI, in the git tab when you click on branches, you will see branches from all the remotes you've in your clone ``remote-name/branch-name`` your locacl branches will not have ``remote-name/`` prefix.
+
+.. note::
+
+  To update your clone with any changes on the remotes (new branches, tags, commits) you might want to regularly run ``git fetch --all`` or for a specific remote: ``git fetch <remote-name>``.
+
+Checking out remote branches
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+When you have configured the remotes in your clone you can check out the heads of specific branches from those remotes or make local branches to track remote branches:
+
+.. code-block:: bash
+
+  # this will show you all the remote branches:
+  git branch -r
+  # to see ALL the branches local/remote:
+  git branch -v -a
+  # check out the head of a remote branch 
+  git checkout <remote-name/branch-name>
+  # create a new branch that will originate 
+  git switch -c <new-branch> # note, when you push you will need to --set-origin
+  # to create a new local branch that will TRACK already existing remote branch
+  git switch -c <branch-name> <remote-name>/<branch-name>
+
+  # to delete a local branch
+  git -d <branch-name>
+
+
+.. tip::
+
+  If you have local changes and you want to switch/make a new branch you can use ``git stash`` to get to the latest commit of the branch you are on.
+  The changes will stay in the stash and you can use it later. To permanently ``git reset --hard``.
\ No newline at end of file
diff --git a/_sources/index.rst b/_sources/index.rst
new file mode 100644
index 0000000..2f1f4d4
--- /dev/null
+++ b/_sources/index.rst
@@ -0,0 +1,14 @@
+eScience 2024 course
+=========================
+
+.. toctree::
+   :maxdepth: 5
+
+   feide
+   course_workflow/index
+   basics/index
+   data/index
+   learning/index
+   git_integration/index
+   contrib
+   license
diff --git a/_sources/learning/index.rst b/_sources/learning/index.rst
new file mode 100644
index 0000000..4a1a7bc
--- /dev/null
+++ b/_sources/learning/index.rst
@@ -0,0 +1,14 @@
+Learning Corner
+===============
+You will find examples of jupyter notebooks which you can run anywhere (if you install the necessary computing environment).
+To add a new example, add a jupyter notebook in :code:`learning/notebooks`. The table of content will be udated after adding
+it to the toctree.
+
+.. toctree::
+   :maxdepth: 3
+   :titlesonly:
+   :caption: Notebook Examples
+   :glob:
+
+   notebooks/*
+   us-links
diff --git a/_sources/learning/notebooks/cool_stuff.ipynb b/_sources/learning/notebooks/cool_stuff.ipynb
new file mode 100644
index 0000000..e9c5520
--- /dev/null
+++ b/_sources/learning/notebooks/cool_stuff.ipynb
@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Building notebooks directly"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def abc(a, b):\n",
+    "    return a + b\n",
+    "\n",
+    "\n",
+    "c = abc(1, 2)\n",
+    "\n",
+    "print(\"1 + 2 =\", c)"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/_sources/learning/notebooks/from_ebas_using_xarray.ipynb b/_sources/learning/notebooks/from_ebas_using_xarray.ipynb
new file mode 100644
index 0000000..5eb985c
--- /dev/null
+++ b/_sources/learning/notebooks/from_ebas_using_xarray.ipynb
@@ -0,0 +1,4254 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Using xarray to read EBAS data\n",
+    "\n",
+    "See more at http://ebas.nilu.no/\n",
+    "and https://ebas.nilu.no/thredds/\n",
+    "\n",
+    "requirements\n",
+    "pip install threddsclient\n",
+    "\n",
+    "The EBAS database collects observational data on atmospheric chemical composition and physical properties from a variety of national and international research projects and monitoring programs, such as ACTRIS, AMAP, EMEP, GAW and HELCOM, as well as for the Norwegian monitoring programs funded by the Norwegian Environment Agency, the Ministry of Climate and Environment and NILU – Norwegian Institute for Air Research.\n",
+    "\n",
+    "See all files available:\n",
+    "https://thredds.nilu.no/thredds/catalog/ebas/catalog.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# You need to first install threddsclient:\n",
+    "# remember to do in terminal pip install threddsclient\n",
+    "import threddsclient\n",
+    "import xarray as xr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Find url addresses for files on EBAS\n",
+    "\n",
+    "all_opendap_urls = threddsclient.opendap_urls(\n",
+    "'https://thredds.nilu.no/thredds/catalog/ebas/catalog.xml')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20100101000000.20150216111241.nephelometer..pm10.4y.1h.SE02L_TSI_3563_ZEP_dry.SE02L_scat_coef.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20080708135939.20181213000000.nephelometer..aerosol_humidified.3mo.6h.CH02L_TSI_3563_ZEP_ref+TSI_3563_ZEP_wet.CH02L_hygro_tandem_neph_CorrData.lev2.nc']"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Example 1 nephelometer scattering coefficient data\n",
+    "# get all data urls for one station, e.g., Zeppelin NO0042G\n",
+    "opendap_urls = [x for x in all_opendap_urls if 'NO0042G' in x]\n",
+    "# get all scattering data urls\n",
+    "opendap_urls = [x for x in opendap_urls if 'nephelometer' in x]\n",
+    "\n",
+    "opendap_urls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 66MB\n",
+       "Dimensions:                                                         (\n",
+       "                                                                     time: 35451,\n",
+       "                                                                     metadata_time: 5,\n",
+       "                                                                     Wavelength: 3,\n",
+       "                                                                     RH_base: 1,\n",
+       "                                                                     RH_humidified: 1,\n",
+       "                                                                     ...\n",
+       "                                                                     aerosol_light_scattering_coefficient_prec1587_qc_flags: 2,\n",
+       "                                                                     aerosol_light_scattering_coefficient_perc8413_qc_flags: 2,\n",
+       "                                                                     pressure_qc_flags: 2,\n",
+       "                                                                     aerosol_light_backscattering_coefficient_prec1587_qc_flags: 2,\n",
+       "                                                                     aerosol_light_backscattering_coefficient_amean_qc_flags: 2,\n",
+       "                                                                     aerosol_light_backscattering_coefficient_perc8413_qc_flags: 2)\n",
+       "Coordinates:\n",
+       "  * time                                                            (time) datetime64[ns] 284kB ...\n",
+       "  * metadata_time                                                   (metadata_time) datetime64[ns] 40B ...\n",
+       "  * Wavelength                                                      (Wavelength) float64 24B ...\n",
+       "  * RH_base                                                         (RH_base) float64 8B ...\n",
+       "  * RH_humidified                                                   (RH_humidified) float64 8B ...\n",
+       "  * RH_base_max                                                     (RH_base_max) float64 8B ...\n",
+       "  * RH                                                              (RH) float64 104B ...\n",
+       "  * Location                                                        (Location) |S64 64B ...\n",
+       "Dimensions without coordinates: tbnds,\n",
+       "                                aerosol_light_scattering_enhancement_factor_qc_flags,\n",
+       "                                aerosol_light_backscattering_coefficient_qc_flags,\n",
+       "                                aerosol_light_backscattering_enhancement_factor_qc_flags,\n",
+       "                                aerosol_light_scattering_coefficient_qc_flags,\n",
+       "                                temperature_qc_flags,\n",
+       "                                ...\n",
+       "                                aerosol_light_scattering_coefficient_prec1587_qc_flags,\n",
+       "                                aerosol_light_scattering_coefficient_perc8413_qc_flags,\n",
+       "                                pressure_qc_flags,\n",
+       "                                aerosol_light_backscattering_coefficient_prec1587_qc_flags,\n",
+       "                                aerosol_light_backscattering_coefficient_amean_qc_flags,\n",
+       "                                aerosol_light_backscattering_coefficient_perc8413_qc_flags\n",
+       "Data variables: (12/41)\n",
+       "    time_bnds                                                       (time, tbnds) datetime64[ns] 567kB dask.array&lt;chunksize=(35451, 2), meta=np.ndarray&gt;\n",
+       "    metadata_time_bnds                                              (metadata_time, tbnds) datetime64[ns] 80B dask.array&lt;chunksize=(5, 2), meta=np.ndarray&gt;\n",
+       "    aerosol_light_scattering_enhancement_factor_qc                  (Wavelength, RH_base, RH_humidified, aerosol_light_scattering_enhancement_factor_qc_flags, time) float64 851kB dask.array&lt;chunksize=(3, 1, 1, 1, 35451), meta=np.ndarray&gt;\n",
+       "    aerosol_light_backscattering_enhancement_factor_ebasmetadata    (Wavelength, RH_base_max, RH_humidified, metadata_time) object 120B dask.array&lt;chunksize=(3, 1, 1, 5), meta=np.ndarray&gt;\n",
+       "    aerosol_light_scattering_enhancement_factor_ebasmetadata        (Wavelength, RH_base, RH_humidified, metadata_time) object 120B dask.array&lt;chunksize=(3, 1, 1, 5), meta=np.ndarray&gt;\n",
+       "    aerosol_light_backscattering_coefficient_qc                     (Wavelength, RH, aerosol_light_backscattering_coefficient_qc_flags, time) float64 11MB dask.array&lt;chunksize=(3, 13, 1, 35451), meta=np.ndarray&gt;\n",
+       "    ...                                                              ...\n",
+       "    aerosol_light_scattering_coefficient_prec1587                   (Wavelength, time) float64 851kB dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;\n",
+       "    pressure                                                        (Location, time) float64 284kB dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;\n",
+       "    aerosol_light_backscattering_coefficient_amean                  (Wavelength, time) float64 851kB dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;\n",
+       "    aerosol_light_scattering_coefficient_perc8413                   (Wavelength, time) float64 851kB dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;\n",
+       "    relative_humidity                                               (Location, time) float64 284kB dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;\n",
+       "    aerosol_light_backscattering_coefficient_prec1587               (Wavelength, time) float64 851kB dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;\n",
+       "Attributes: (12/47)\n",
+       "    Conventions:                   CF-1.7, ACDD-1.3\n",
+       "    featureType:                   timeSeries\n",
+       "    title:                         Ground based in situ observations of nephe...\n",
+       "    keywords:                      NO0042G, Zeppelin mountain (Ny-Ålesund), a...\n",
+       "    id:                            NO0042G.20080708135939.20181213000000.neph...\n",
+       "    naming_authority:              EBAS\n",
+       "    ...                            ...\n",
+       "    geospatial_lat_units:          degrees_north\n",
+       "    geospatial_lon_units:          degrees_east\n",
+       "    comment:                       {\\n    &quot;Data definition&quot;: &quot;EBAS_1.1&quot;, \\n  ...\n",
+       "    standard_name_vocabulary:      CF-1.7, ACDD-1.3\n",
+       "    history:                       None\n",
+       "    creator_url:                   ebas.nilu.no</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c02cbbce-4e9a-4108-a726-50340ee56de0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c02cbbce-4e9a-4108-a726-50340ee56de0' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 35451</li><li><span class='xr-has-index'>metadata_time</span>: 5</li><li><span class='xr-has-index'>Wavelength</span>: 3</li><li><span class='xr-has-index'>RH_base</span>: 1</li><li><span class='xr-has-index'>RH_humidified</span>: 1</li><li><span class='xr-has-index'>RH_base_max</span>: 1</li><li><span class='xr-has-index'>RH</span>: 13</li><li><span>tbnds</span>: 2</li><li><span>aerosol_light_scattering_enhancement_factor_qc_flags</span>: 1</li><li><span>aerosol_light_backscattering_coefficient_qc_flags</span>: 1</li><li><span>aerosol_light_backscattering_enhancement_factor_qc_flags</span>: 1</li><li><span>aerosol_light_scattering_coefficient_qc_flags</span>: 1</li><li><span class='xr-has-index'>Location</span>: 1</li><li><span>temperature_qc_flags</span>: 2</li><li><span>relative_humidity_qc_flags</span>: 2</li><li><span>aerosol_light_scattering_coefficient_amean_qc_flags</span>: 2</li><li><span>aerosol_light_scattering_coefficient_prec1587_qc_flags</span>: 2</li><li><span>aerosol_light_scattering_coefficient_perc8413_qc_flags</span>: 2</li><li><span>pressure_qc_flags</span>: 2</li><li><span>aerosol_light_backscattering_coefficient_prec1587_qc_flags</span>: 2</li><li><span>aerosol_light_backscattering_coefficient_amean_qc_flags</span>: 2</li><li><span>aerosol_light_backscattering_coefficient_perc8413_qc_flags</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8c49fe42-f5e8-4e92-bbd8-43b971accd7c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8c49fe42-f5e8-4e92-bbd8-43b971accd7c' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2008-07-08T16:59:38.999999488 .....</div><input id='attrs-283ad786-e890-487b-a235-6ed7647466d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-283ad786-e890-487b-a235-6ed7647466d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f46b4a2d-8edf-4681-97bc-6128766d4002' class='xr-var-data-in' type='checkbox'><label for='data-f46b4a2d-8edf-4681-97bc-6128766d4002' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time of measurement</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>cell_methods :</span></dt><dd>mean</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2008-07-08T16:59:38.999999488&#x27;, &#x27;2008-07-08T22:59:38.999999488&#x27;,\n",
+       "       &#x27;2008-07-09T04:59:38.999999488&#x27;, ..., &#x27;2013-12-31T21:30:00.000000000&#x27;,\n",
+       "       &#x27;2013-12-31T22:29:59.000000000&#x27;, &#x27;2013-12-31T23:29:59.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>metadata_time</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2008-08-25T22:59:38.999999488 .....</div><input id='attrs-e2e7c8c8-bbf9-4852-9bb5-9b3048ccc837' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2e7c8c8-bbf9-4852-9bb5-9b3048ccc837' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb4c4b6d-d640-46bd-85db-7ab53a7d1d6c' class='xr-var-data-in' type='checkbox'><label for='data-eb4c4b6d-d640-46bd-85db-7ab53a7d1d6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time of ebas metadata intervals</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>metadata_time_bnds</dd><dt><span>cell_methods :</span></dt><dd>mean</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2008-08-25T22:59:38.999999488&#x27;, &#x27;2010-07-02T12:00:00.000000000&#x27;,\n",
+       "       &#x27;2011-07-02T12:00:00.000000000&#x27;, &#x27;2012-07-02T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2013-07-02T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Wavelength</span></div><div class='xr-var-dims'>(Wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>450.0 550.0 700.0</div><input id='attrs-c0f2f27b-ba68-47ea-b4e9-75caec7955b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0f2f27b-ba68-47ea-b4e9-75caec7955b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b63ef43-48fc-4ae1-b3c9-a7f2c47c33ba' class='xr-var-data-in' type='checkbox'><label for='data-1b63ef43-48fc-4ae1-b3c9-a7f2c47c33ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([450., 550., 700.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>RH_base</span></div><div class='xr-var-dims'>(RH_base)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0</div><input id='attrs-cf63a8ff-a245-4f7a-8153-4c43f3d29455' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf63a8ff-a245-4f7a-8153-4c43f3d29455' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c987b0b-3d06-467c-a868-621f28edb13e' class='xr-var-data-in' type='checkbox'><label for='data-4c987b0b-3d06-467c-a868-621f28edb13e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([40.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>RH_humidified</span></div><div class='xr-var-dims'>(RH_humidified)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>85.0</div><input id='attrs-056a30b6-eaf1-46ac-a1b6-a34f79ff2be4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-056a30b6-eaf1-46ac-a1b6-a34f79ff2be4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc8400de-ab8e-4075-8ab1-965eaea827ba' class='xr-var-data-in' type='checkbox'><label for='data-dc8400de-ab8e-4075-8ab1-965eaea827ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([85.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>RH_base_max</span></div><div class='xr-var-dims'>(RH_base_max)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0</div><input id='attrs-52e744d5-b350-4507-b7cc-dbdec1df08c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52e744d5-b350-4507-b7cc-dbdec1df08c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-318afd66-20c8-4c53-8e82-1629184c6770' class='xr-var-data-in' type='checkbox'><label for='data-318afd66-20c8-4c53-8e82-1629184c6770' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([40.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>RH</span></div><div class='xr-var-dims'>(RH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>30.0 35.0 40.0 ... 80.0 85.0 90.0</div><input id='attrs-7500a61c-7a72-4490-abe0-2c3693d33872' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7500a61c-7a72-4490-abe0-2c3693d33872' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93f67cd3-e536-4c5d-8d3a-79dad3c26c2c' class='xr-var-data-in' type='checkbox'><label for='data-93f67cd3-e536-4c5d-8d3a-79dad3c26c2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([30., 35., 40., 45., 50., 55., 60., 65., 70., 75., 80., 85., 90.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Location</span></div><div class='xr-var-dims'>(Location)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>b&#x27;instrument internal&#x27;</div><input id='attrs-3353dfe7-2f0d-4fbd-8af1-7b9c008f905e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3353dfe7-2f0d-4fbd-8af1-7b9c008f905e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdb6a5a9-e12e-4cf2-8cf1-bec7b7061928' class='xr-var-data-in' type='checkbox'><label for='data-fdb6a5a9-e12e-4cf2-8cf1-bec7b7061928' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([b&#x27;instrument internal&#x27;], dtype=&#x27;|S64&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e1cd6f9e-dca1-4ef3-8e84-661919955dd7' class='xr-section-summary-in' type='checkbox'  ><label for='section-e1cd6f9e-dca1-4ef3-8e84-661919955dd7' class='xr-section-summary' >Data variables: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, tbnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(35451, 2), meta=np.ndarray&gt;</div><input id='attrs-b48ab23b-e2ec-4319-b8ac-24f283fc43ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b48ab23b-e2ec-4319-b8ac-24f283fc43ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a03aabf-db15-4b99-9632-fbb19ed5233c' class='xr-var-data-in' type='checkbox'><label for='data-6a03aabf-db15-4b99-9632-fbb19ed5233c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time bounds for measurement</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 553.92 kiB </td>\n",
+       "                        <td> 553.92 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (35451, 2) </td>\n",
+       "                        <td> (35451, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
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+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>metadata_time_bnds</span></div><div class='xr-var-dims'>(metadata_time, tbnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(5, 2), meta=np.ndarray&gt;</div><input id='attrs-75019dac-2b7d-4e51-91d9-cc6b7e93b8b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75019dac-2b7d-4e51-91d9-cc6b7e93b8b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52b12302-e706-40ab-9759-5a0040691ceb' class='xr-var-data-in' type='checkbox'><label for='data-52b12302-e706-40ab-9759-5a0040691ceb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time bounds for ebas metadata intervals</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 80 B </td>\n",
+       "                        <td> 80 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (5, 2) </td>\n",
+       "                        <td> (5, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
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+       "                </tbody>\n",
+       "            </table>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_enhancement_factor_qc</span></div><div class='xr-var-dims'>(Wavelength, RH_base, RH_humidified, aerosol_light_scattering_enhancement_factor_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 1, 1, 1, 35451), meta=np.ndarray&gt;</div><input id='attrs-29e01cfe-14d9-4cdd-a113-af2b2d17c435' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29e01cfe-14d9-4cdd-a113-af2b2d17c435' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ce00c2a-6e4b-4c9d-a8bc-cdf13b0b636e' class='xr-var-data-in' type='checkbox'><label for='data-4ce00c2a-6e4b-4c9d-a8bc-cdf13b0b636e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
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+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                        <td> 830.88 kiB </td>\n",
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+       "                        <td> (3, 1, 1, 1, 35451) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 15 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_enhancement_factor_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, RH_base_max, RH_humidified, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 1, 1, 5), meta=np.ndarray&gt;</div><input id='attrs-1bfbb5b9-d6b2-455f-90a2-7f27c749f130' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bfbb5b9-d6b2-455f-90a2-7f27c749f130' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32b1f232-befb-4ffe-a6ec-9fa9761d97f0' class='xr-var-data-in' type='checkbox'><label for='data-32b1f232-befb-4ffe-a6ec-9fa9761d97f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 120 B </td>\n",
+       "                        <td> 120 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 1, 1, 5) </td>\n",
+       "                        <td> (3, 1, 1, 5) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 15 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_enhancement_factor_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, RH_base, RH_humidified, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 1, 1, 5), meta=np.ndarray&gt;</div><input id='attrs-f816028a-dd2a-4de1-86de-edcd64110738' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f816028a-dd2a-4de1-86de-edcd64110738' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02f8be97-3b73-4799-b72e-70e5c6ac89e9' class='xr-var-data-in' type='checkbox'><label for='data-02f8be97-3b73-4799-b72e-70e5c6ac89e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
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+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 120 B </td>\n",
+       "                        <td> 120 B </td>\n",
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+       "                    <tr>\n",
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+       "                        <td> (3, 1, 1, 5) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 15 graph layers </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_qc</span></div><div class='xr-var-dims'>(Wavelength, RH, aerosol_light_backscattering_coefficient_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 13, 1, 35451), meta=np.ndarray&gt;</div><input id='attrs-ccc1ca2c-7532-42cb-9e15-b0562f006199' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccc1ca2c-7532-42cb-9e15-b0562f006199' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97190e2e-6856-401b-91a7-422da984f1dd' class='xr-var-data-in' type='checkbox'><label for='data-97190e2e-6856-401b-91a7-422da984f1dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 10.55 MiB </td>\n",
+       "                        <td> 10.55 MiB </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_enhancement_factor_qc</span></div><div class='xr-var-dims'>(Wavelength, RH_base_max, RH_humidified, aerosol_light_backscattering_enhancement_factor_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 1, 1, 1, 35451), meta=np.ndarray&gt;</div><input id='attrs-addc86c4-7d44-4e3d-8805-8c751a116827' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-addc86c4-7d44-4e3d-8805-8c751a116827' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-230dfa0e-8d74-4a3c-ad18-62b92c1d720f' class='xr-var-data-in' type='checkbox'><label for='data-230dfa0e-8d74-4a3c-ad18-62b92c1d720f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                        <td> 830.88 kiB </td>\n",
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+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 1, 1, 1, 35451) </td>\n",
+       "                        <td> (3, 1, 1, 1, 35451) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_qc</span></div><div class='xr-var-dims'>(Wavelength, RH, aerosol_light_scattering_coefficient_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 13, 1, 35451), meta=np.ndarray&gt;</div><input id='attrs-91bff4b2-ef4a-417c-bbed-e06247978fea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91bff4b2-ef4a-417c-bbed-e06247978fea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d14ce503-bb55-45be-963c-4a1cd0217d23' class='xr-var-data-in' type='checkbox'><label for='data-d14ce503-bb55-45be-963c-4a1cd0217d23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
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+       "                        <td> 10.55 MiB </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, RH, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 13, 5), meta=np.ndarray&gt;</div><input id='attrs-dda800ae-ddb3-4e64-9766-25e634785d2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dda800ae-ddb3-4e64-9766-25e634785d2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b46682de-759a-48c7-a3a5-ec64cb570193' class='xr-var-data-in' type='checkbox'><label for='data-b46682de-759a-48c7-a3a5-ec64cb570193' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.52 kiB </td>\n",
+       "                        <td> 1.52 kiB </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, RH, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 13, 5), meta=np.ndarray&gt;</div><input id='attrs-8d7ad618-b5bd-4978-ac50-e57b867e7a18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d7ad618-b5bd-4978-ac50-e57b867e7a18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1b1230b-b9d2-4a39-b7b1-d604c9065ac7' class='xr-var-data-in' type='checkbox'><label for='data-d1b1230b-b9d2-4a39-b7b1-d604c9065ac7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.52 kiB </td>\n",
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+       "                        <td> (3, 13, 5) </td>\n",
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+       "                        <td colspan=\"2\"> 1 chunks in 14 graph layers </td>\n",
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+       "                        <th> Data type </th>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_enhancement_factor</span></div><div class='xr-var-dims'>(Wavelength, RH_base, RH_humidified, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 1, 1, 35451), meta=np.ndarray&gt;</div><input id='attrs-c66ab700-9e76-44e9-aa31-cf7372e3c4c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c66ab700-9e76-44e9-aa31-cf7372e3c4c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f45c515-ab23-4072-8c02-dd0ce6b7cb71' class='xr-var-data-in' type='checkbox'><label for='data-0f45c515-ab23-4072-8c02-dd0ce6b7cb71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>no unit</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_scattering_enhancement_factor_qc aerosol_light_scattering_enhancement_factor_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_enhancement_factor</span></div><div class='xr-var-dims'>(Wavelength, RH_base_max, RH_humidified, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 1, 1, 35451), meta=np.ndarray&gt;</div><input id='attrs-175ee4df-b4e1-4bd9-b240-b87069033229' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-175ee4df-b4e1-4bd9-b240-b87069033229' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a35afe4-d192-4ce3-9f41-706e7c07ab35' class='xr-var-data-in' type='checkbox'><label for='data-3a35afe4-d192-4ce3-9f41-706e7c07ab35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>no unit</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_backscattering_enhancement_factor_qc aerosol_light_backscattering_enhancement_factor_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                        <td> 830.88 kiB </td>\n",
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+       "                        <td> (3, 1, 1, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 14 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient</span></div><div class='xr-var-dims'>(Wavelength, RH, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 13, 35451), meta=np.ndarray&gt;</div><input id='attrs-74a6b3bb-01d2-4c3c-a0b0-fe4b219ee9db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74a6b3bb-01d2-4c3c-a0b0-fe4b219ee9db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8cd8a82-e507-4833-9588-e1e0d1992d80' class='xr-var-data-in' type='checkbox'><label for='data-f8cd8a82-e507-4833-9588-e1e0d1992d80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_backscattering_coefficient_qc aerosol_light_backscattering_coefficient_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 10.55 MiB </td>\n",
+       "                        <td> 10.55 MiB </td>\n",
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+       "                        <td> (3, 13, 35451) </td>\n",
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+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
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+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient</span></div><div class='xr-var-dims'>(Wavelength, RH, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 13, 35451), meta=np.ndarray&gt;</div><input id='attrs-37d1636b-cb0d-4e60-b5d0-623bb49eaa12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37d1636b-cb0d-4e60-b5d0-623bb49eaa12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14711f39-c7c4-4b57-899f-b8262bdf7331' class='xr-var-data-in' type='checkbox'><label for='data-14711f39-c7c4-4b57-899f-b8262bdf7331' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_scattering_coefficient_qc aerosol_light_scattering_coefficient_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
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+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 10.55 MiB </td>\n",
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+       "                        <td> (3, 13, 35451) </td>\n",
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+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
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+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_amean_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 5), meta=np.ndarray&gt;</div><input id='attrs-9abc88ae-5cb1-4cf7-b7db-35ba206e24f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9abc88ae-5cb1-4cf7-b7db-35ba206e24f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0e29cb1-2e32-408a-93f3-d95ccb99b90c' class='xr-var-data-in' type='checkbox'><label for='data-e0e29cb1-2e32-408a-93f3-d95ccb99b90c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 120 B </td>\n",
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+       "                    <tr>\n",
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+       "                        <td> (3, 5) </td>\n",
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+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
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+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature_qc</span></div><div class='xr-var-dims'>(Location, temperature_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-97ea1242-d6fc-452d-85b3-ae67de593ef4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97ea1242-d6fc-452d-85b3-ae67de593ef4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7288a209-f8aa-433f-b0dc-8dfb541996dc' class='xr-var-data-in' type='checkbox'><label for='data-7288a209-f8aa-433f-b0dc-8dfb541996dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 553.92 kiB </td>\n",
+       "                        <td> 553.92 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 2, 35451) </td>\n",
+       "                        <td> (1, 2, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>relative_humidity_qc</span></div><div class='xr-var-dims'>(Location, relative_humidity_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-2be2c242-b162-4fa7-bbd1-64f8302c9174' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2be2c242-b162-4fa7-bbd1-64f8302c9174' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31c798ec-bfdb-45da-86fe-e748cac8784e' class='xr-var-data-in' type='checkbox'><label for='data-31c798ec-bfdb-45da-86fe-e748cac8784e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                        <th> Array </th>\n",
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+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 553.92 kiB </td>\n",
+       "                        <td> 553.92 kiB </td>\n",
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+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 2, 35451) </td>\n",
+       "                        <td> (1, 2, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_prec1587_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 5), meta=np.ndarray&gt;</div><input id='attrs-6d220f77-eb96-4b48-9dbe-1d0dbe1a4bee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d220f77-eb96-4b48-9dbe-1d0dbe1a4bee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3355aa8-7493-4d18-a3be-5e71bf88080b' class='xr-var-data-in' type='checkbox'><label for='data-e3355aa8-7493-4d18-a3be-5e71bf88080b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 120 B </td>\n",
+       "                        <td> 120 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 5) </td>\n",
+       "                        <td> (3, 5) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_amean_qc</span></div><div class='xr-var-dims'>(Wavelength, aerosol_light_scattering_coefficient_amean_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-1f139e95-6758-4d13-bbe2-2241094f04d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f139e95-6758-4d13-bbe2-2241094f04d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45d964b2-8935-4450-8dfa-fbd9b9aa9719' class='xr-var-data-in' type='checkbox'><label for='data-45d964b2-8935-4450-8dfa-fbd9b9aa9719' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                    <tr>\n",
+       "                        <td> </td>\n",
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+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.62 MiB </td>\n",
+       "                        <td> 1.62 MiB </td>\n",
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+       "                    \n",
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+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 2, 35451) </td>\n",
+       "                        <td> (3, 2, 35451) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_prec1587_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 5), meta=np.ndarray&gt;</div><input id='attrs-7843394c-b0d3-440d-b2bf-4e777053b85e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7843394c-b0d3-440d-b2bf-4e777053b85e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df3226cb-fbf0-4d67-a043-067ba43abe0d' class='xr-var-data-in' type='checkbox'><label for='data-df3226cb-fbf0-4d67-a043-067ba43abe0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 120 B </td>\n",
+       "                        <td> 120 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 5) </td>\n",
+       "                        <td> (3, 5) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "            </table>\n",
+       "        </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_perc8413_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 5), meta=np.ndarray&gt;</div><input id='attrs-ad2b84fc-a6bc-441f-a122-2a2dbc8173d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad2b84fc-a6bc-441f-a122-2a2dbc8173d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66770ab0-b762-4b08-9932-c12f8f1ceec4' class='xr-var-data-in' type='checkbox'><label for='data-66770ab0-b762-4b08-9932-c12f8f1ceec4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 120 B </td>\n",
+       "                        <td> 120 B </td>\n",
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+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 5) </td>\n",
+       "                        <td> (3, 5) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature_ebasmetadata</span></div><div class='xr-var-dims'>(Location, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;</div><input id='attrs-af7f031b-93b7-490a-9430-fe03934ee065' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af7f031b-93b7-490a-9430-fe03934ee065' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5b4bed9-e2ca-4140-a204-27b173a14979' class='xr-var-data-in' type='checkbox'><label for='data-c5b4bed9-e2ca-4140-a204-27b173a14979' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 40 B </td>\n",
+       "                        <td> 40 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 5) </td>\n",
+       "                        <td> (1, 5) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "            </table>\n",
+       "        </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_ebasmetadata</span></div><div class='xr-var-dims'>(Location, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;</div><input id='attrs-d4e418c8-3fef-4c26-a371-690e597d1bb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4e418c8-3fef-4c26-a371-690e597d1bb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2a9b555-d685-4169-b868-0e9a5621e5ef' class='xr-var-data-in' type='checkbox'><label for='data-d2a9b555-d685-4169-b868-0e9a5621e5ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
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+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 40 B </td>\n",
+       "                        <td> 40 B </td>\n",
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+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                    <tr>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_prec1587_qc</span></div><div class='xr-var-dims'>(Wavelength, aerosol_light_scattering_coefficient_prec1587_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-dc1b74b0-9a80-4620-ae12-1af6cc0a7558' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc1b74b0-9a80-4620-ae12-1af6cc0a7558' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f994696-51ae-4178-b6d0-32c3f2577c40' class='xr-var-data-in' type='checkbox'><label for='data-9f994696-51ae-4178-b6d0-32c3f2577c40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
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+       "                <tbody>\n",
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+       "                        <td> 1.62 MiB </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_perc8413_qc</span></div><div class='xr-var-dims'>(Wavelength, aerosol_light_scattering_coefficient_perc8413_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-e9e68502-c5eb-4b3d-8b47-d6e53a277645' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9e68502-c5eb-4b3d-8b47-d6e53a277645' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b63ad800-90cf-445f-9103-749a3d7fa3e0' class='xr-var-data-in' type='checkbox'><label for='data-b63ad800-90cf-445f-9103-749a3d7fa3e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.62 MiB </td>\n",
+       "                        <td> 1.62 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
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+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 2, 35451) </td>\n",
+       "                        <td> (3, 2, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_qc</span></div><div class='xr-var-dims'>(Location, pressure_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-81bcdb3d-54d6-411e-8342-bccdb9e7b67c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81bcdb3d-54d6-411e-8342-bccdb9e7b67c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fafc84a-0864-4e6d-bd9f-c047b72228e4' class='xr-var-data-in' type='checkbox'><label for='data-0fafc84a-0864-4e6d-bd9f-c047b72228e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                    <tr>\n",
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+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 553.92 kiB </td>\n",
+       "                        <td> 553.92 kiB </td>\n",
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+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 2, 35451) </td>\n",
+       "                        <td> (1, 2, 35451) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_perc8413_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 5), meta=np.ndarray&gt;</div><input id='attrs-b2b4f2cb-3835-4f99-87c8-1e38467ebfda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2b4f2cb-3835-4f99-87c8-1e38467ebfda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9218105f-8a5b-49d0-8dee-b84c58ef0417' class='xr-var-data-in' type='checkbox'><label for='data-9218105f-8a5b-49d0-8dee-b84c58ef0417' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 120 B </td>\n",
+       "                        <td> 120 B </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 5) </td>\n",
+       "                        <td> (3, 5) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_prec1587_qc</span></div><div class='xr-var-dims'>(Wavelength, aerosol_light_backscattering_coefficient_prec1587_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-db78b512-75db-4ce7-8f2e-1895f2e5bee6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db78b512-75db-4ce7-8f2e-1895f2e5bee6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd74d781-fc05-48d4-8111-b585860c1f0b' class='xr-var-data-in' type='checkbox'><label for='data-bd74d781-fc05-48d4-8111-b585860c1f0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.62 MiB </td>\n",
+       "                        <td> 1.62 MiB </td>\n",
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+       "                        <td> (3, 2, 35451) </td>\n",
+       "                        <td> (3, 2, 35451) </td>\n",
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+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
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+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_amean_qc</span></div><div class='xr-var-dims'>(Wavelength, aerosol_light_backscattering_coefficient_amean_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-f8fd365f-a4e7-4397-8a26-d0297971d8b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8fd365f-a4e7-4397-8a26-d0297971d8b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-503557a3-ed39-4bdc-be0a-c31ad2808038' class='xr-var-data-in' type='checkbox'><label for='data-503557a3-ed39-4bdc-be0a-c31ad2808038' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "        <td>\n",
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+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.62 MiB </td>\n",
+       "                        <td> 1.62 MiB </td>\n",
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+       "                        <th> Data type </th>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_amean_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 5), meta=np.ndarray&gt;</div><input id='attrs-234df4f6-fb94-43db-9d2d-33e0735d2d16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-234df4f6-fb94-43db-9d2d-33e0735d2d16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7980393-d59f-4d99-ad3d-aa63a9ff9b78' class='xr-var-data-in' type='checkbox'><label for='data-a7980393-d59f-4d99-ad3d-aa63a9ff9b78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                </thead>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 120 B </td>\n",
+       "                        <td> 120 B </td>\n",
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+       "                        <td> (3, 5) </td>\n",
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+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_perc8413_qc</span></div><div class='xr-var-dims'>(Wavelength, aerosol_light_backscattering_coefficient_perc8413_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-10115508-013a-4277-8fd1-29cf1df2f816' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10115508-013a-4277-8fd1-29cf1df2f816' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b445f56b-52a4-45a1-9ac9-daeb46420d25' class='xr-var-data-in' type='checkbox'><label for='data-b445f56b-52a4-45a1-9ac9-daeb46420d25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.62 MiB </td>\n",
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+       "                        <td> (3, 2, 35451) </td>\n",
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+       "                        <th> Dask graph </th>\n",
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+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>relative_humidity_ebasmetadata</span></div><div class='xr-var-dims'>(Location, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;</div><input id='attrs-761aa528-6b56-4da3-8751-b0413b8d6cf0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-761aa528-6b56-4da3-8751-b0413b8d6cf0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c37cf06-2f97-450d-89c2-739a699d16ba' class='xr-var-data-in' type='checkbox'><label for='data-7c37cf06-2f97-450d-89c2-739a699d16ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                        <td> 40 B </td>\n",
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+       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
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+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_perc8413</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-ca70ed6d-874b-4585-8581-ead4a681eb67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca70ed6d-874b-4585-8581-ead4a681eb67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3ac19f5-b6b2-4d6f-951f-95a576008170' class='xr-var-data-in' type='checkbox'><label for='data-e3ac19f5-b6b2-4d6f-951f-95a576008170' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_backscattering_coefficient_perc8413_qc aerosol_light_backscattering_coefficient_perc8413_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: percentile:84.13</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                        <td> 830.88 kiB </td>\n",
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+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_amean</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-9372dba9-44ed-4669-b2c8-475b0b1b8aff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9372dba9-44ed-4669-b2c8-475b0b1b8aff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6e31db7-871b-4b91-a7cf-c41cee07f675' class='xr-var-data-in' type='checkbox'><label for='data-e6e31db7-871b-4b91-a7cf-c41cee07f675' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_scattering_coefficient_amean_qc aerosol_light_scattering_coefficient_amean_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(Location, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;</div><input id='attrs-d9f780da-bd0b-4125-917f-d4ae2066c22a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9f780da-bd0b-4125-917f-d4ae2066c22a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e971cee-ac7a-4ae8-8b2d-c2f539fd4530' class='xr-var-data-in' type='checkbox'><label for='data-4e971cee-ac7a-4ae8-8b2d-c2f539fd4530' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>ancillary_variables :</span></dt><dd>temperature_qc temperature_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 276.96 kiB </td>\n",
+       "                        <td> 276.96 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 35451) </td>\n",
+       "                        <td> (1, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_prec1587</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-dd4619a3-e54d-4639-98dd-7ddf53fc74eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd4619a3-e54d-4639-98dd-7ddf53fc74eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d286f9c1-105a-430f-a7bc-f1a3922aad45' class='xr-var-data-in' type='checkbox'><label for='data-d286f9c1-105a-430f-a7bc-f1a3922aad45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_scattering_coefficient_prec1587_qc aerosol_light_scattering_coefficient_prec1587_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: percentile:15.87</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(Location, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;</div><input id='attrs-ba2eed54-f197-4c8e-91fd-8f017d4c131a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba2eed54-f197-4c8e-91fd-8f017d4c131a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-676ba34a-41b6-4e55-a33b-fe265a1329f4' class='xr-var-data-in' type='checkbox'><label for='data-676ba34a-41b6-4e55-a33b-fe265a1329f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd><dt><span>ancillary_variables :</span></dt><dd>pressure_qc pressure_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 276.96 kiB </td>\n",
+       "                        <td> 276.96 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 35451) </td>\n",
+       "                        <td> (1, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
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+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
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+       "\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_amean</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-e13c66c6-34c5-446c-82bf-0d97e796deb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e13c66c6-34c5-446c-82bf-0d97e796deb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b747a934-cdf1-404f-8108-f83d1f4762c7' class='xr-var-data-in' type='checkbox'><label for='data-b747a934-cdf1-404f-8108-f83d1f4762c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_backscattering_coefficient_amean_qc aerosol_light_backscattering_coefficient_amean_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_perc8413</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-75b31c65-7500-4126-93cd-f15fbc84ac0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75b31c65-7500-4126-93cd-f15fbc84ac0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dffccd5-1502-4246-abd8-9440099f96ba' class='xr-var-data-in' type='checkbox'><label for='data-0dffccd5-1502-4246-abd8-9440099f96ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_scattering_coefficient_perc8413_qc aerosol_light_scattering_coefficient_perc8413_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: percentile:84.13</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >35451</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">3</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>relative_humidity</span></div><div class='xr-var-dims'>(Location, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;</div><input id='attrs-15a1750d-08e7-43da-9274-a7550e277189' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15a1750d-08e7-43da-9274-a7550e277189' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ea3b871-b2a8-4ebb-9492-612a35e5d909' class='xr-var-data-in' type='checkbox'><label for='data-3ea3b871-b2a8-4ebb-9492-612a35e5d909' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>ancillary_variables :</span></dt><dd>relative_humidity_qc relative_humidity_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 276.96 kiB </td>\n",
+       "                        <td> 276.96 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 35451) </td>\n",
+       "                        <td> (1, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >35451</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_prec1587</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-7c7bb327-0609-4e12-87be-5a78a0e59c4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c7bb327-0609-4e12-87be-5a78a0e59c4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e856bc0-c65c-407d-b431-57ef5144a241' class='xr-var-data-in' type='checkbox'><label for='data-6e856bc0-c65c-407d-b431-57ef5144a241' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_backscattering_coefficient_prec1587_qc aerosol_light_backscattering_coefficient_prec1587_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: percentile:15.87</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                        <td> 830.88 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                        <td> (3, 35451) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >35451</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">3</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6caddc14-68e2-437e-bf22-f07defea4817' class='xr-section-summary-in' type='checkbox'  ><label for='section-6caddc14-68e2-437e-bf22-f07defea4817' class='xr-section-summary' >Indexes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d6b3c699-826a-42d4-8e3a-73b6a89d8714' class='xr-index-data-in' type='checkbox'/><label for='index-d6b3c699-826a-42d4-8e3a-73b6a89d8714' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2008-07-08 16:59:38.999999488&#x27;,\n",
+       "               &#x27;2008-07-08 22:59:38.999999488&#x27;,\n",
+       "               &#x27;2008-07-09 04:59:38.999999488&#x27;,\n",
+       "               &#x27;2008-07-09 10:59:38.999999488&#x27;,\n",
+       "               &#x27;2008-07-09 16:59:38.999999488&#x27;,\n",
+       "               &#x27;2008-07-09 22:59:38.999999488&#x27;,\n",
+       "               &#x27;2008-07-10 04:59:38.999999488&#x27;,\n",
+       "               &#x27;2008-07-10 10:59:38.999999488&#x27;,\n",
+       "               &#x27;2008-07-10 16:59:38.999999488&#x27;,\n",
+       "               &#x27;2008-07-10 22:59:38.999999488&#x27;,\n",
+       "               ...\n",
+       "                         &#x27;2013-12-31 14:29:59&#x27;,\n",
+       "                         &#x27;2013-12-31 15:30:00&#x27;,\n",
+       "                         &#x27;2013-12-31 16:29:59&#x27;,\n",
+       "                         &#x27;2013-12-31 17:29:59&#x27;,\n",
+       "                         &#x27;2013-12-31 18:30:00&#x27;,\n",
+       "                         &#x27;2013-12-31 19:29:59&#x27;,\n",
+       "                         &#x27;2013-12-31 20:29:59&#x27;,\n",
+       "                         &#x27;2013-12-31 21:30:00&#x27;,\n",
+       "                         &#x27;2013-12-31 22:29:59&#x27;,\n",
+       "                         &#x27;2013-12-31 23:29:59&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=35451, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>metadata_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-da030b04-28f0-4385-858f-c639acb357e2' class='xr-index-data-in' type='checkbox'/><label for='index-da030b04-28f0-4385-858f-c639acb357e2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2008-08-25 22:59:38.999999488&#x27;,\n",
+       "                         &#x27;2010-07-02 12:00:00&#x27;,\n",
+       "                         &#x27;2011-07-02 12:00:00&#x27;,\n",
+       "                         &#x27;2012-07-02 00:00:00&#x27;,\n",
+       "                         &#x27;2013-07-02 12:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;metadata_time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>Wavelength</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-58008ea5-7bf4-4357-b849-5fbcc866a308' class='xr-index-data-in' type='checkbox'/><label for='index-58008ea5-7bf4-4357-b849-5fbcc866a308' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([450.0, 550.0, 700.0], dtype=&#x27;float64&#x27;, name=&#x27;Wavelength&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>RH_base</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bca85a7c-9d4c-4792-97be-e139ac2a318c' class='xr-index-data-in' type='checkbox'/><label for='index-bca85a7c-9d4c-4792-97be-e139ac2a318c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([40.0], dtype=&#x27;float64&#x27;, name=&#x27;RH_base&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>RH_humidified</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3eafcd23-5bc0-4384-81c7-c9d7960f6cba' class='xr-index-data-in' type='checkbox'/><label for='index-3eafcd23-5bc0-4384-81c7-c9d7960f6cba' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([85.0], dtype=&#x27;float64&#x27;, name=&#x27;RH_humidified&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>RH_base_max</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0148ea02-fe96-4bc2-9fcb-8efcd6c7c194' class='xr-index-data-in' type='checkbox'/><label for='index-0148ea02-fe96-4bc2-9fcb-8efcd6c7c194' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([40.0], dtype=&#x27;float64&#x27;, name=&#x27;RH_base_max&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>RH</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f8cefb99-30a3-4b8b-b582-b64ce092e544' class='xr-index-data-in' type='checkbox'/><label for='index-f8cefb99-30a3-4b8b-b582-b64ce092e544' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0,\n",
+       "       90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;RH&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>Location</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-821bd459-6a7a-4a64-9c4f-39428ee8323f' class='xr-index-data-in' type='checkbox'/><label for='index-821bd459-6a7a-4a64-9c4f-39428ee8323f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([b&#x27;instrument internal&#x27;], dtype=&#x27;object&#x27;, name=&#x27;Location&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f789336-5d98-4d64-960e-a6883fdfc3c3' class='xr-section-summary-in' type='checkbox'  ><label for='section-6f789336-5d98-4d64-960e-a6883fdfc3c3' class='xr-section-summary' >Attributes: <span>(47)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7, ACDD-1.3</dd><dt><span>featureType :</span></dt><dd>timeSeries</dd><dt><span>title :</span></dt><dd>Ground based in situ observations of nephelometer at Zeppelin mountain (Ny-Ålesund) (NO0042G)</dd><dt><span>keywords :</span></dt><dd>NO0042G, Zeppelin mountain (Ny-Ålesund), aerosol_light_scattering_enhancement_factor, aerosol_light_backscattering_enhancement_factor, aerosol_light_backscattering_coefficient, EMEP, aerosol_light_scattering_coefficient, GAW-WDCA, aerosol_humidified, ACTRIS, CREATE</dd><dt><span>id :</span></dt><dd>NO0042G.20080708135939.20181213000000.nephelometer..aerosol_humidified.3mo.6h.CH02L_TSI_3563_ZEP_ref+TSI_3563_ZEP_wet.CH02L_hygro_tandem_neph_CorrData.lev2.nc</dd><dt><span>naming_authority :</span></dt><dd>EBAS</dd><dt><span>project :</span></dt><dd>CREATE, ACTRIS, EMEP, GAW-WDCA</dd><dt><span>acknowledgement :</span></dt><dd>Request acknowledgement details from data originator</dd><dt><span>license :</span></dt><dd>CREATE: Fair use data policy (see also EMEP and WMO-GAW), ACTRIS: http://actris.nilu.no/Content/Documents/DataPolicy.pdf, EMEP: Public open access. We encourage contacting data originators if substatial use of individual time series is planned (fair use data policy)., GAW-WDCA: </dd><dt><span>summary :</span></dt><dd>Ground based in situ observations of nephelometer at Zeppelin mountain (Ny-Ålesund) (NO0042G). These measurements are gathered as a part of the following projects CREATE, ACTRIS, EMEP, GAW-WDCA and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: aerosol_light_backscattering_coefficient in aerosol_humidified, aerosol_light_backscattering_enhancement_factor in aerosol_humidified, aerosol_light_scattering_coefficient in aerosol_humidified, aerosol_light_scattering_enhancement_factor in aerosol_humidified</dd><dt><span>source :</span></dt><dd>surface observation</dd><dt><span>institution :</span></dt><dd>CH02L, Paul Scherrer Institut, PSI, Laboratory of Atmospheric Chemistry (LAC), OFLB, 5232, Villigen PSI, Switzerland</dd><dt><span>processing_level :</span></dt><dd>processing_level_test</dd><dt><span>date_created :</span></dt><dd>2018-12-13T00:00:00 UTC</dd><dt><span>date_metadata_modified :</span></dt><dd>2018-12-13T00:00:00 UTC</dd><dt><span>creator_name :</span></dt><dd>Paul Zieger, Maria A. Burgos</dd><dt><span>creator_type :</span></dt><dd>person</dd><dt><span>creator_email :</span></dt><dd>paul.zieger@aces.su.se, paul.zieger@aces.su.se</dd><dt><span>creator_institution :</span></dt><dd>&quot;Department of Environmental Science and Analytical Chemistry, ACES&quot;, &quot;Department of Environmental Science and Analytical Chemistry, ACES&quot;</dd><dt><span>contributor_name :</span></dt><dd>Maria A. Burgos</dd><dt><span>contributor_role :</span></dt><dd>data submitter</dd><dt><span>publisher_type :</span></dt><dd>institution</dd><dt><span>publisher_name :</span></dt><dd>NILU - Norwegian Institute for Air Research, ATMOS, EBAS</dd><dt><span>publisher_institution :</span></dt><dd>NILU - Norwegian Institute for Air Research, ATMOS, EBAS</dd><dt><span>publisher_email :</span></dt><dd>ebas@nilu.no</dd><dt><span>publisher_url :</span></dt><dd>https://www.nilu.no/</dd><dt><span>geospatial_bounds :</span></dt><dd>POINT Z (78.91 11.88 477.0)</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>EPSG:4979</dd><dt><span>geospatial_lat_min :</span></dt><dd>78.91</dd><dt><span>geospatial_lat_max :</span></dt><dd>78.91</dd><dt><span>geospatial_lon_min :</span></dt><dd>11.88</dd><dt><span>geospatial_lon_max :</span></dt><dd>11.88</dd><dt><span>geospatial_vertical_min :</span></dt><dd>477.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>477.0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>time_coverage_start :</span></dt><dd>2008-07-08T13:59:39 UTC</dd><dt><span>time_coverage_end :</span></dt><dd>2008-10-13T07:59:39 UTC</dd><dt><span>time_coverage_duration :</span></dt><dd>P0000-03-04T18:00:00</dd><dt><span>time_coverage_resolution :</span></dt><dd>P0000-00-00T06:00:00</dd><dt><span>timezone :</span></dt><dd>UTC</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>comment :</span></dt><dd>{\n",
+       "    &quot;Data definition&quot;: &quot;EBAS_1.1&quot;, \n",
+       "    &quot;Set type code&quot;: &quot;TU&quot;, \n",
+       "    &quot;Timezone&quot;: &quot;UTC&quot;, \n",
+       "    &quot;File name&quot;: &quot;NO0042G.20080708135939.20181213000000.nephelometer..aerosol_humidified.3mo.6h.CH02L_TSI_3563_ZEP_ref+TSI_3563_ZEP_wet.CH02L_hygro_tandem_neph_CorrData.lev2.nc&quot;, \n",
+       "    &quot;File creation&quot;: &quot;20190627182802&quot;, \n",
+       "    &quot;Startdate&quot;: &quot;20080708135939&quot;, \n",
+       "    &quot;Revision date&quot;: &quot;20181213000000&quot;, \n",
+       "    &quot;Version&quot;: &quot;1&quot;, \n",
+       "    &quot;Version description&quot;: &quot;interpolated scattering coefficients, calculated scattering enhancement factors as described in Burgos et al., 2018&quot;, \n",
+       "    &quot;Statistics&quot;: &quot;arithmetic mean&quot;, \n",
+       "    &quot;Data level&quot;: &quot;2&quot;, \n",
+       "    &quot;Period code&quot;: &quot;3mo&quot;, \n",
+       "    &quot;Resolution code&quot;: &quot;6h&quot;, \n",
+       "    &quot;Sample duration&quot;: &quot;6h&quot;, \n",
+       "    &quot;Orig. time res.&quot;: &quot;6h&quot;, \n",
+       "    &quot;Station code&quot;: &quot;NO0042G&quot;, \n",
+       "    &quot;Platform code&quot;: &quot;NO0042S&quot;, \n",
+       "    &quot;Station name&quot;: &quot;Zeppelin mountain (Ny-Ålesund)&quot;, \n",
+       "    &quot;Station WDCA-ID&quot;: &quot;GAWANO__ZEP&quot;, \n",
+       "    &quot;Station GAW-ID&quot;: &quot;ZEP&quot;, \n",
+       "    &quot;Station GAW-Name&quot;: &quot;Zeppelin Mountain (Ny Ålesund)&quot;, \n",
+       "    &quot;Station land use&quot;: &quot;Gravel and stone&quot;, \n",
+       "    &quot;Station setting&quot;: &quot;Polar&quot;, \n",
+       "    &quot;Station GAW type&quot;: &quot;G&quot;, \n",
+       "    &quot;Station WMO region&quot;: &quot;6&quot;, \n",
+       "    &quot;Station latitude&quot;: &quot;78.90715&quot;, \n",
+       "    &quot;Station longitude&quot;: &quot;11.88668&quot;, \n",
+       "    &quot;Station altitude&quot;: &quot;474.0 m&quot;, \n",
+       "    &quot;Measurement latitude&quot;: &quot;78.91&quot;, \n",
+       "    &quot;Measurement longitude&quot;: &quot;11.88&quot;, \n",
+       "    &quot;Measurement altitude&quot;: &quot;477.0 m&quot;, \n",
+       "    &quot;Measurement height&quot;: &quot;2.0 m&quot;, \n",
+       "    &quot;Regime&quot;: &quot;IMG&quot;, \n",
+       "    &quot;Unit&quot;: &quot;1/Mm&quot;, \n",
+       "    &quot;Matrix&quot;: &quot;aerosol_humidified&quot;, \n",
+       "    &quot;Laboratory code&quot;: &quot;CH02L&quot;, \n",
+       "    &quot;Instrument type&quot;: &quot;nephelometer&quot;, \n",
+       "    &quot;Instrument name&quot;: &quot;TSI_3563_ZEP_ref+TSI_3563_ZEP_wet&quot;, \n",
+       "    &quot;Instrument manufacturer&quot;: &quot;TSI&quot;, \n",
+       "    &quot;Instrument model&quot;: &quot;3563&quot;, \n",
+       "    &quot;Instrument serial number&quot;: &quot;1043&quot;, \n",
+       "    &quot;Method ref&quot;: &quot;CH02L_hygro_tandem_neph_CorrData&quot;, \n",
+       "    &quot;Standard method&quot;: &quot;cal-gas=CO2+AIR_truncation-correction=Anderson1998&quot;, \n",
+       "    &quot;Inlet type&quot;: &quot;Stainless steel&quot;, \n",
+       "    &quot;Inlet description&quot;: &quot;no heater, no cut size&quot;, \n",
+       "    &quot;Humidity/temperature control&quot;: &quot;Humidification&quot;, \n",
+       "    &quot;Humidity/temperature control description&quot;: &quot;humidogram&quot;, \n",
+       "    &quot;Volume std. temperature&quot;: &quot;273.15 K&quot;, \n",
+       "    &quot;Volume std. pressure&quot;: &quot;1013.25 hPa&quot;, \n",
+       "    &quot;Detection limit&quot;: &quot;0.5 1/Mm&quot;, \n",
+       "    &quot;Detection limit expl.&quot;: &quot;Determined by instrument counting statistics, no detection limit flag used&quot;, \n",
+       "    &quot;Measurement uncertainty expl.&quot;: &quot;Uncertainty analysis described in Burgos et al., 2019&quot;, \n",
+       "    &quot;Zero/negative values code&quot;: &quot;Zero/negative possible&quot;, \n",
+       "    &quot;Zero/negative values&quot;: &quot;zero and neg. values may appear due to statistical variations at very low concentrations&quot;, \n",
+       "    &quot;Organization&quot;: &quot;CH02L, Paul Scherrer Institut, PSI, Laboratory of Atmospheric Chemistry (LAC), OFLB, , 5232, Villigen PSI, Switzerland&quot;, \n",
+       "    &quot;Frameworks&quot;: &quot;ACTRIS CREATE EMEP GAW-WDCA&quot;, \n",
+       "    &quot;Originator&quot;: &quot;Burgos, Maria A., paul.zieger@aces.su.se, Department of Environmental Science and Analytical Chemistry, ACES, , Frescativägen 54, , SE10691, Stockholm, Sweden&quot;, \n",
+       "    &quot;Submitter&quot;: &quot;Burgos, Maria A., paul.zieger@aces.su.se, Department of Environmental Science and Analytical Chemistry, ACES, , Frescativägen 54, , SE10691, Stockholm, Sweden&quot;, \n",
+       "    &quot;Acknowledgement&quot;: &quot;Request acknowledgement details from data originator&quot;\n",
+       "}</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF-1.7, ACDD-1.3</dd><dt><span>history :</span></dt><dd>None</dd><dt><span>creator_url :</span></dt><dd>ebas.nilu.no</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 66MB\n",
+       "Dimensions:                                                         (\n",
+       "                                                                     time: 35451,\n",
+       "                                                                     metadata_time: 5,\n",
+       "                                                                     Wavelength: 3,\n",
+       "                                                                     RH_base: 1,\n",
+       "                                                                     RH_humidified: 1,\n",
+       "                                                                     ...\n",
+       "                                                                     aerosol_light_scattering_coefficient_prec1587_qc_flags: 2,\n",
+       "                                                                     aerosol_light_scattering_coefficient_perc8413_qc_flags: 2,\n",
+       "                                                                     pressure_qc_flags: 2,\n",
+       "                                                                     aerosol_light_backscattering_coefficient_prec1587_qc_flags: 2,\n",
+       "                                                                     aerosol_light_backscattering_coefficient_amean_qc_flags: 2,\n",
+       "                                                                     aerosol_light_backscattering_coefficient_perc8413_qc_flags: 2)\n",
+       "Coordinates:\n",
+       "  * time                                                            (time) datetime64[ns] 284kB ...\n",
+       "  * metadata_time                                                   (metadata_time) datetime64[ns] 40B ...\n",
+       "  * Wavelength                                                      (Wavelength) float64 24B ...\n",
+       "  * RH_base                                                         (RH_base) float64 8B ...\n",
+       "  * RH_humidified                                                   (RH_humidified) float64 8B ...\n",
+       "  * RH_base_max                                                     (RH_base_max) float64 8B ...\n",
+       "  * RH                                                              (RH) float64 104B ...\n",
+       "  * Location                                                        (Location) |S64 64B ...\n",
+       "Dimensions without coordinates: tbnds,\n",
+       "                                aerosol_light_scattering_enhancement_factor_qc_flags,\n",
+       "                                aerosol_light_backscattering_coefficient_qc_flags,\n",
+       "                                aerosol_light_backscattering_enhancement_factor_qc_flags,\n",
+       "                                aerosol_light_scattering_coefficient_qc_flags,\n",
+       "                                temperature_qc_flags,\n",
+       "                                ...\n",
+       "                                aerosol_light_scattering_coefficient_prec1587_qc_flags,\n",
+       "                                aerosol_light_scattering_coefficient_perc8413_qc_flags,\n",
+       "                                pressure_qc_flags,\n",
+       "                                aerosol_light_backscattering_coefficient_prec1587_qc_flags,\n",
+       "                                aerosol_light_backscattering_coefficient_amean_qc_flags,\n",
+       "                                aerosol_light_backscattering_coefficient_perc8413_qc_flags\n",
+       "Data variables: (12/41)\n",
+       "    time_bnds                                                       (time, tbnds) datetime64[ns] 567kB dask.array<chunksize=(35451, 2), meta=np.ndarray>\n",
+       "    metadata_time_bnds                                              (metadata_time, tbnds) datetime64[ns] 80B dask.array<chunksize=(5, 2), meta=np.ndarray>\n",
+       "    aerosol_light_scattering_enhancement_factor_qc                  (Wavelength, RH_base, RH_humidified, aerosol_light_scattering_enhancement_factor_qc_flags, time) float64 851kB dask.array<chunksize=(3, 1, 1, 1, 35451), meta=np.ndarray>\n",
+       "    aerosol_light_backscattering_enhancement_factor_ebasmetadata    (Wavelength, RH_base_max, RH_humidified, metadata_time) object 120B dask.array<chunksize=(3, 1, 1, 5), meta=np.ndarray>\n",
+       "    aerosol_light_scattering_enhancement_factor_ebasmetadata        (Wavelength, RH_base, RH_humidified, metadata_time) object 120B dask.array<chunksize=(3, 1, 1, 5), meta=np.ndarray>\n",
+       "    aerosol_light_backscattering_coefficient_qc                     (Wavelength, RH, aerosol_light_backscattering_coefficient_qc_flags, time) float64 11MB dask.array<chunksize=(3, 13, 1, 35451), meta=np.ndarray>\n",
+       "    ...                                                              ...\n",
+       "    aerosol_light_scattering_coefficient_prec1587                   (Wavelength, time) float64 851kB dask.array<chunksize=(3, 35451), meta=np.ndarray>\n",
+       "    pressure                                                        (Location, time) float64 284kB dask.array<chunksize=(1, 35451), meta=np.ndarray>\n",
+       "    aerosol_light_backscattering_coefficient_amean                  (Wavelength, time) float64 851kB dask.array<chunksize=(3, 35451), meta=np.ndarray>\n",
+       "    aerosol_light_scattering_coefficient_perc8413                   (Wavelength, time) float64 851kB dask.array<chunksize=(3, 35451), meta=np.ndarray>\n",
+       "    relative_humidity                                               (Location, time) float64 284kB dask.array<chunksize=(1, 35451), meta=np.ndarray>\n",
+       "    aerosol_light_backscattering_coefficient_prec1587               (Wavelength, time) float64 851kB dask.array<chunksize=(3, 35451), meta=np.ndarray>\n",
+       "Attributes: (12/47)\n",
+       "    Conventions:                   CF-1.7, ACDD-1.3\n",
+       "    featureType:                   timeSeries\n",
+       "    title:                         Ground based in situ observations of nephe...\n",
+       "    keywords:                      NO0042G, Zeppelin mountain (Ny-Ålesund), a...\n",
+       "    id:                            NO0042G.20080708135939.20181213000000.neph...\n",
+       "    naming_authority:              EBAS\n",
+       "    ...                            ...\n",
+       "    geospatial_lat_units:          degrees_north\n",
+       "    geospatial_lon_units:          degrees_east\n",
+       "    comment:                       {\\n    \"Data definition\": \"EBAS_1.1\", \\n  ...\n",
+       "    standard_name_vocabulary:      CF-1.7, ACDD-1.3\n",
+       "    history:                       None\n",
+       "    creator_url:                   ebas.nilu.no"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# read multiple files\n",
+    "# the problem with this example is, \n",
+    "#    that the files are from different instruments\n",
+    "#    thus, they need to be treated and digested one by one.\n",
+    "\n",
+    "dsmf = xr.open_mfdataset(opendap_urls)\n",
+    "dsmf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20200101070000.20230314140946.filter_3pack...1y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20160101070000.20230314140946.filter_3pack...3y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20230511100226.filter_3pack.sulphate_corrected.aerosol.9y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20230314140946.filter_3pack.sum_nitric_acid_and_nitrate.air+aerosol.9y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20230314140050.filter_3pack.potassium.aerosol.7y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20230314140050.filter_3pack.chloride.aerosol.7y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.sulphate_total.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.sodium.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.nitric_acid.air.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.nitrate.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.magnesium.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.calcium.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.ammonium.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.ammonia.air.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20010101070000.20230511100226.filter_3pack...19y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.19930101070000.20210421112338.filter_3pack...8y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.19920101070000.20210420142507.filter_3pack...1y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc',\n",
+       " 'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.19891101070000.20210420142507.filter_3pack...26mo.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc']"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Example 2 aerosol sulphate data \n",
+    "# also here - \n",
+    "#    the files are differently shaped for different periods\n",
+    "#    best to read single files, analyse, and then concatenate for longer time series\n",
+    "#    note that catalogue file names give no full description of what is in a file\n",
+    "\n",
+    "# get all data urls for one station, e.g., Zeppelin NO0042G\n",
+    "opendap_urls = [x for x in all_opendap_urls if 'NO0042G' in x]\n",
+    "\n",
+    "# get all data urls which could contain sulphate data, exclude some\n",
+    "opendap_urls = [x for x in opendap_urls if 'filter_3pack' in x]\n",
+    "opendap_urls = [x for x in opendap_urls if not 'sum_ammonia' in x]\n",
+    "opendap_urls = [x for x in opendap_urls if not 'sulphur_dioxide' in x]\n",
+    "\n",
+    "opendap_urls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc'"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file_to_read = opendap_urls[0]\n",
+    "file_to_read"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 183kB\n",
+       "Dimensions:                                  (time: 730, tbnds: 2,\n",
+       "                                              metadata_time: 2,\n",
+       "                                              ammonia_qc_flags: 1,\n",
+       "                                              ammonium_ug_N_per_m3_qc_flags: 1,\n",
+       "                                              ammonium_ug_per_m3_qc_flags: 1,\n",
+       "                                              calcium_qc_flags: 1,\n",
+       "                                              ...\n",
+       "                                              nitric_acid_qc_flags: 1,\n",
+       "                                              potassium_qc_flags: 1,\n",
+       "                                              sodium_qc_flags: 1,\n",
+       "                                              sulphate_total_ug_S_per_m3_qc_flags: 1,\n",
+       "                                              sulphate_total_ug_per_m3_qc_flags: 1,\n",
+       "                                              sulphur_dioxide_qc_flags: 1)\n",
+       "Coordinates:\n",
+       "  * time                                     (time) datetime64[ns] 6kB 2021-0...\n",
+       "  * metadata_time                            (metadata_time) datetime64[ns] 16B ...\n",
+       "Dimensions without coordinates: tbnds, ammonia_qc_flags,\n",
+       "                                ammonium_ug_N_per_m3_qc_flags,\n",
+       "                                ammonium_ug_per_m3_qc_flags, calcium_qc_flags,\n",
+       "                                chloride_qc_flags, magnesium_qc_flags,\n",
+       "                                nitrate_ug_N_per_m3_qc_flags,\n",
+       "                                nitrate_ug_per_m3_qc_flags,\n",
+       "                                nitric_acid_qc_flags, potassium_qc_flags,\n",
+       "                                sodium_qc_flags,\n",
+       "                                sulphate_total_ug_S_per_m3_qc_flags,\n",
+       "                                sulphate_total_ug_per_m3_qc_flags,\n",
+       "                                sulphur_dioxide_qc_flags\n",
+       "Data variables: (12/44)\n",
+       "    time_bnds                                (time, tbnds) datetime64[ns] 12kB ...\n",
+       "    metadata_time_bnds                       (metadata_time, tbnds) datetime64[ns] 32B ...\n",
+       "    ammonia                                  (time) float64 6kB ...\n",
+       "    ammonia_qc                               (ammonia_qc_flags, time) float64 6kB ...\n",
+       "    ammonia_ebasmetadata                     (metadata_time) |S64 128B ...\n",
+       "    ammonium_ug_N_per_m3                     (time) float64 6kB ...\n",
+       "    ...                                       ...\n",
+       "    sulphate_total_ug_per_m3                 (time) float64 6kB ...\n",
+       "    sulphate_total_ug_per_m3_qc              (sulphate_total_ug_per_m3_qc_flags, time) float64 6kB ...\n",
+       "    sulphate_total_ug_per_m3_ebasmetadata    (metadata_time) |S64 128B ...\n",
+       "    sulphur_dioxide                          (time) float64 6kB ...\n",
+       "    sulphur_dioxide_qc                       (sulphur_dioxide_qc_flags, time) float64 6kB ...\n",
+       "    sulphur_dioxide_ebasmetadata             (metadata_time) |S64 128B ...\n",
+       "Attributes: (12/106)\n",
+       "    Conventions:                                   CF-1.8, ACDD-1.3\n",
+       "    featureType:                                   timeSeries\n",
+       "    title:                                         Ground based in situ obser...\n",
+       "    keywords:                                      mass_concentration_of_nitr...\n",
+       "    id:                                            NO0042G.20210101070000.202...\n",
+       "    naming_authority:                              EBAS\n",
+       "    ...                                            ...\n",
+       "    geospatial_lat_units:                          degrees_north\n",
+       "    geospatial_lon_units:                          degrees_east\n",
+       "    comment:                                       {\\n    &quot;Data definition&quot;: ...\n",
+       "    standard_name_vocabulary:                      CF-1.7, ACDD-1.3\n",
+       "    history:                                       None\n",
+       "    creator_url:                                   ebas.nilu.no</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6a36b03a-3f96-48a2-b37f-c7b81600fec5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6a36b03a-3f96-48a2-b37f-c7b81600fec5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 730</li><li><span>tbnds</span>: 2</li><li><span class='xr-has-index'>metadata_time</span>: 2</li><li><span>ammonia_qc_flags</span>: 1</li><li><span>ammonium_ug_N_per_m3_qc_flags</span>: 1</li><li><span>ammonium_ug_per_m3_qc_flags</span>: 1</li><li><span>calcium_qc_flags</span>: 1</li><li><span>chloride_qc_flags</span>: 1</li><li><span>magnesium_qc_flags</span>: 1</li><li><span>nitrate_ug_N_per_m3_qc_flags</span>: 1</li><li><span>nitrate_ug_per_m3_qc_flags</span>: 1</li><li><span>nitric_acid_qc_flags</span>: 1</li><li><span>potassium_qc_flags</span>: 1</li><li><span>sodium_qc_flags</span>: 1</li><li><span>sulphate_total_ug_S_per_m3_qc_flags</span>: 1</li><li><span>sulphate_total_ug_per_m3_qc_flags</span>: 1</li><li><span>sulphur_dioxide_qc_flags</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-63eea7d2-907f-40d0-8881-db111ada73eb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-63eea7d2-907f-40d0-8881-db111ada73eb' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01T19:00:00 ... 2022-12-...</div><input id='attrs-bb922fc0-9cfc-4763-8fbb-b28017012122' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb922fc0-9cfc-4763-8fbb-b28017012122' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7aa82031-4025-4ef0-8fcb-4f64df694b68' class='xr-var-data-in' type='checkbox'><label for='data-7aa82031-4025-4ef0-8fcb-4f64df694b68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time of measurement</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T19:00:00.000000000&#x27;, &#x27;2021-01-02T19:00:00.000000000&#x27;,\n",
+       "       &#x27;2021-01-03T19:00:00.000000000&#x27;, ..., &#x27;2022-12-29T19:00:00.000000000&#x27;,\n",
+       "       &#x27;2022-12-30T19:00:00.000000000&#x27;, &#x27;2022-12-31T19:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>metadata_time</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-07-02T19:00:00 2022-07-02T1...</div><input id='attrs-abeee7de-2745-4250-8da0-3b9fe3629886' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abeee7de-2745-4250-8da0-3b9fe3629886' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4ef8efa-b44d-4c5d-89eb-955a1a12ca71' class='xr-var-data-in' type='checkbox'><label for='data-b4ef8efa-b44d-4c5d-89eb-955a1a12ca71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time of ebas metadata intervals</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>metadata_time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-07-02T19:00:00.000000000&#x27;, &#x27;2022-07-02T19:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6654873f-4c28-414d-9fc3-019ef303e43e' class='xr-section-summary-in' type='checkbox'  ><label for='section-6654873f-4c28-414d-9fc3-019ef303e43e' class='xr-section-summary' >Data variables: <span>(44)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, tbnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c1ab47e2-1c1b-4e7c-ad34-6decc1e33ca7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1ab47e2-1c1b-4e7c-ad34-6decc1e33ca7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f071e50-0eb4-4da8-8322-917ce45d1d9d' class='xr-var-data-in' type='checkbox'><label for='data-3f071e50-0eb4-4da8-8322-917ce45d1d9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time bounds for measurement</dd></dl></div><div class='xr-var-data'><pre>[1460 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>metadata_time_bnds</span></div><div class='xr-var-dims'>(metadata_time, tbnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9031fa9b-8704-4dda-92fd-1d706de241d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9031fa9b-8704-4dda-92fd-1d706de241d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35b241b7-149e-411c-877c-31a2600deee4' class='xr-var-data-in' type='checkbox'><label for='data-35b241b7-149e-411c-877c-31a2600deee4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time bounds for ebas metadata intervals</dd></dl></div><div class='xr-var-data'><pre>[4 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonia</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3005ba4d-e2b2-4880-b7d4-0b303bc935f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3005ba4d-e2b2-4880-b7d4-0b303bc935f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cce05361-07e2-43f8-adff-6639922b21c6' class='xr-var-data-in' type='checkbox'><label for='data-cce05361-07e2-43f8-adff-6639922b21c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_ammonia_expressed_as_nitrogen_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>ammonia_qc ammonia_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>ammonia</dd><dt><span>ebas_unit :</span></dt><dd>ug N/m3</dd><dt><span>ebas_matrix :</span></dt><dd>air</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Cellulose</dd><dt><span>ebas_coating_solution :</span></dt><dd>Oxalic acid</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.04 ug N/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonia_qc</span></div><div class='xr-var-dims'>(ammonia_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d4c949a4-580c-4acc-9679-edcf50f8daa5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4c949a4-580c-4acc-9679-edcf50f8daa5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd1d325a-4d23-4f31-b1ab-a1879dda1652' class='xr-var-data-in' type='checkbox'><label for='data-fd1d325a-4d23-4f31-b1ab-a1879dda1652' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonia_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c00c8d98-106e-4b68-964c-709c7415b20f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c00c8d98-106e-4b68-964c-709c7415b20f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b93e9340-14ea-45bd-965e-947b2976691f' class='xr-var-data-in' type='checkbox'><label for='data-b93e9340-14ea-45bd-965e-947b2976691f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_N_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f09cc450-fb1e-4256-94ef-aae6ac227f4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f09cc450-fb1e-4256-94ef-aae6ac227f4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8260f0d-b2c0-4a37-9e9a-081cc266deb7' class='xr-var-data-in' type='checkbox'><label for='data-e8260f0d-b2c0-4a37-9e9a-081cc266deb7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_ammonium_expressed_as_nitrogen_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>ammonium_ug N_per_m3_qc ammonium_ug N_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>ammonium</dd><dt><span>ebas_unit :</span></dt><dd>ug N/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0103 ug N/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_N_per_m3_qc</span></div><div class='xr-var-dims'>(ammonium_ug_N_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cfe9106c-2621-447e-a780-cbdf14ece2ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfe9106c-2621-447e-a780-cbdf14ece2ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06392c9e-6faa-4a8a-9e54-3bdf6b3c2d25' class='xr-var-data-in' type='checkbox'><label for='data-06392c9e-6faa-4a8a-9e54-3bdf6b3c2d25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_N_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-76fcf987-9b97-4827-8bc7-9f3cc746a7bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76fcf987-9b97-4827-8bc7-9f3cc746a7bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a51a72a4-d827-4c01-ab47-4d0361ee5f6e' class='xr-var-data-in' type='checkbox'><label for='data-a51a72a4-d827-4c01-ab47-4d0361ee5f6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-caac7b0f-6bc4-433e-9010-719cd6ca43af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-caac7b0f-6bc4-433e-9010-719cd6ca43af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37f552c3-1a64-47a1-8676-2712d2f8f74d' class='xr-var-data-in' type='checkbox'><label for='data-37f552c3-1a64-47a1-8676-2712d2f8f74d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_ammonium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>ammonium_ug_per_m3_qc ammonium_ug_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>ammonium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.013 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_comment :</span></dt><dd>Data converted on export from EBAS from &#x27;ug N/m3&#x27; to &#x27;ug/m3&#x27;, conversion factor 1.28786. Detection limit converted from &#x27;0.0103 ug N/m3&#x27; to &#x27;0.013 ug/m3&#x27;, conversion factor 1.28786.</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_per_m3_qc</span></div><div class='xr-var-dims'>(ammonium_ug_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-efe6d814-bac9-412a-a2f2-9b0f69698f08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efe6d814-bac9-412a-a2f2-9b0f69698f08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6209b05-6824-4f19-b8c7-802b72d9dd08' class='xr-var-data-in' type='checkbox'><label for='data-f6209b05-6824-4f19-b8c7-802b72d9dd08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-34d9b517-4795-4bf3-a750-1e6a9fdda047' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34d9b517-4795-4bf3-a750-1e6a9fdda047' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1201d86b-7a37-489b-a4f6-14a3e6dc57e6' class='xr-var-data-in' type='checkbox'><label for='data-1201d86b-7a37-489b-a4f6-14a3e6dc57e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calcium</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e5634032-5e92-41ca-888f-291e6c0c5acc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5634032-5e92-41ca-888f-291e6c0c5acc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e737fa46-f4bd-43a1-a517-1f13b8ff9844' class='xr-var-data-in' type='checkbox'><label for='data-e737fa46-f4bd-43a1-a517-1f13b8ff9844' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_calcium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>calcium_qc calcium_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>calcium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0177 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calcium_qc</span></div><div class='xr-var-dims'>(calcium_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-73d90db7-6d10-4641-a99a-f5747f6c6d92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73d90db7-6d10-4641-a99a-f5747f6c6d92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab1f49d9-f58c-405e-b58a-9bd5f6f6d4d3' class='xr-var-data-in' type='checkbox'><label for='data-ab1f49d9-f58c-405e-b58a-9bd5f6f6d4d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calcium_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e5819d06-71bc-4df1-a706-417819551aaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5819d06-71bc-4df1-a706-417819551aaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16ba0b82-4891-4d65-a9fe-c23f0b73d3e0' class='xr-var-data-in' type='checkbox'><label for='data-16ba0b82-4891-4d65-a9fe-c23f0b73d3e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>chloride</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7b78ebca-8668-4219-b062-569baa8b3fd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b78ebca-8668-4219-b062-569baa8b3fd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6dac1a1-13d3-422c-bb25-f503e6961210' class='xr-var-data-in' type='checkbox'><label for='data-f6dac1a1-13d3-422c-bb25-f503e6961210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_chloride_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>chloride_qc chloride_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>chloride</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>chloride_qc</span></div><div class='xr-var-dims'>(chloride_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8d3d57f1-735b-4a93-aa07-6cd0aee0372b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d3d57f1-735b-4a93-aa07-6cd0aee0372b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cea7f1be-b080-4e3b-9c74-6655c4e963e2' class='xr-var-data-in' type='checkbox'><label for='data-cea7f1be-b080-4e3b-9c74-6655c4e963e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>chloride_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd230975-f973-4498-b32e-8dbf196b48cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd230975-f973-4498-b32e-8dbf196b48cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b68bb57d-98b6-4de1-8a8f-8fd25fdbd8b9' class='xr-var-data-in' type='checkbox'><label for='data-b68bb57d-98b6-4de1-8a8f-8fd25fdbd8b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>magnesium</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f6e22587-5085-4fa4-8845-b14b4d684395' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6e22587-5085-4fa4-8845-b14b4d684395' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa083b69-6f95-4b5a-aab2-3c1acd47e0ea' class='xr-var-data-in' type='checkbox'><label for='data-fa083b69-6f95-4b5a-aab2-3c1acd47e0ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_magnesium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>magnesium_qc magnesium_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>magnesium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0148 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>magnesium_qc</span></div><div class='xr-var-dims'>(magnesium_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-491a5d63-4d61-4776-8acd-9ec5253f8837' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-491a5d63-4d61-4776-8acd-9ec5253f8837' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53adcb69-1b5e-4955-857e-1f5e82d6f5a7' class='xr-var-data-in' type='checkbox'><label for='data-53adcb69-1b5e-4955-857e-1f5e82d6f5a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>magnesium_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-59bdc409-1663-4977-833e-c0a872798511' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59bdc409-1663-4977-833e-c0a872798511' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a95056d-f043-4286-a0fc-e004c7f2c1e6' class='xr-var-data-in' type='checkbox'><label for='data-8a95056d-f043-4286-a0fc-e004c7f2c1e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_N_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6953e430-7542-4d65-a215-0304764647b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6953e430-7542-4d65-a215-0304764647b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69c6a8a6-5c16-4b24-b970-f32beaa2bd5d' class='xr-var-data-in' type='checkbox'><label for='data-69c6a8a6-5c16-4b24-b970-f32beaa2bd5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_nitrate_expressed_as_nitrogen_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>nitrate_ug N_per_m3_qc nitrate_ug N_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>nitrate</dd><dt><span>ebas_unit :</span></dt><dd>ug N/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug N/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_N_per_m3_qc</span></div><div class='xr-var-dims'>(nitrate_ug_N_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4c30655c-d1c6-48eb-bb4e-b11f407aa5ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c30655c-d1c6-48eb-bb4e-b11f407aa5ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-164e005a-1ff0-4bee-985c-7337b07a7e6e' class='xr-var-data-in' type='checkbox'><label for='data-164e005a-1ff0-4bee-985c-7337b07a7e6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_N_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd4e338c-0612-42fb-ab9a-55378342c68f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd4e338c-0612-42fb-ab9a-55378342c68f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45a62f25-b53e-4e61-8493-142c89e753f3' class='xr-var-data-in' type='checkbox'><label for='data-45a62f25-b53e-4e61-8493-142c89e753f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-89ec7033-ff4c-4c9b-82af-b122ee7c706a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89ec7033-ff4c-4c9b-82af-b122ee7c706a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e312112a-e166-40b6-9301-d0f32db560fe' class='xr-var-data-in' type='checkbox'><label for='data-e312112a-e166-40b6-9301-d0f32db560fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_nitrate_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>nitrate_ug_per_m3_qc nitrate_ug_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>nitrate</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.09 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_comment :</span></dt><dd>Data converted on export from EBAS from &#x27;ug N/m3&#x27; to &#x27;ug/m3&#x27;, conversion factor 4.4267. Detection limit converted from &#x27;0.02 ug N/m3&#x27; to &#x27;0.09 ug/m3&#x27;, conversion factor 4.4267.</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_per_m3_qc</span></div><div class='xr-var-dims'>(nitrate_ug_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ce6674c9-ece4-4c29-860a-2122df0034e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce6674c9-ece4-4c29-860a-2122df0034e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6de7b1ce-f4b4-4163-8c4a-306e1f83fc03' class='xr-var-data-in' type='checkbox'><label for='data-6de7b1ce-f4b4-4163-8c4a-306e1f83fc03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-427c6265-4d26-4328-b232-e8fcb76673e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-427c6265-4d26-4328-b232-e8fcb76673e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24f8e645-2eec-489d-90b0-d03d815b2534' class='xr-var-data-in' type='checkbox'><label for='data-24f8e645-2eec-489d-90b0-d03d815b2534' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitric_acid</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-70d0197f-386f-44c7-87d5-6304ddfd07f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70d0197f-386f-44c7-87d5-6304ddfd07f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5b0d2d0-fa99-441f-a4e6-e42a7560b3d1' class='xr-var-data-in' type='checkbox'><label for='data-a5b0d2d0-fa99-441f-a4e6-e42a7560b3d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_nitric_acid_expressed_as_nitrogen_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>nitric_acid_qc nitric_acid_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>nitric_acid</dd><dt><span>ebas_unit :</span></dt><dd>ug N/m3</dd><dt><span>ebas_matrix :</span></dt><dd>air</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Cellulose</dd><dt><span>ebas_coating_solution :</span></dt><dd>KOH</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug N/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitric_acid_qc</span></div><div class='xr-var-dims'>(nitric_acid_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-325c6e23-e7b6-4ddb-8b07-c26956968c37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-325c6e23-e7b6-4ddb-8b07-c26956968c37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff7e37b3-c448-4ffa-a1ec-3d9969dfb579' class='xr-var-data-in' type='checkbox'><label for='data-ff7e37b3-c448-4ffa-a1ec-3d9969dfb579' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitric_acid_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ce8b5956-6eee-4cb1-bbcc-ad58e248721d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce8b5956-6eee-4cb1-bbcc-ad58e248721d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2e4487e-cc46-41f8-a42e-3bc9ddadae09' class='xr-var-data-in' type='checkbox'><label for='data-c2e4487e-cc46-41f8-a42e-3bc9ddadae09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>potassium</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ff574fc4-2ee7-438b-8014-176036ba2a08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff574fc4-2ee7-438b-8014-176036ba2a08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd0f895b-ef9d-4078-a452-1c73ed3ab3d4' class='xr-var-data-in' type='checkbox'><label for='data-dd0f895b-ef9d-4078-a452-1c73ed3ab3d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_potassium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>potassium_qc potassium_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>potassium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0155 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>potassium_qc</span></div><div class='xr-var-dims'>(potassium_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-362a040d-56d8-468d-b50b-8f829be7bd0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-362a040d-56d8-468d-b50b-8f829be7bd0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-671fe420-98b5-4564-8b43-23b123a4a1b8' class='xr-var-data-in' type='checkbox'><label for='data-671fe420-98b5-4564-8b43-23b123a4a1b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>potassium_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4a3588d5-89e7-4c96-ac7f-975e9a68df2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a3588d5-89e7-4c96-ac7f-975e9a68df2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41397e56-5a95-4231-b1ef-92007f24f87d' class='xr-var-data-in' type='checkbox'><label for='data-41397e56-5a95-4231-b1ef-92007f24f87d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sodium</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ee81b262-14a5-4359-b34e-08781c944267' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee81b262-14a5-4359-b34e-08781c944267' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ffb533f-fed7-4e2b-8815-9e16489768ba' class='xr-var-data-in' type='checkbox'><label for='data-3ffb533f-fed7-4e2b-8815-9e16489768ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_sodium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>sodium_qc sodium_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>sodium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0188 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sodium_qc</span></div><div class='xr-var-dims'>(sodium_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-424378a8-a08b-41db-bb51-a0eaced174f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-424378a8-a08b-41db-bb51-a0eaced174f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4adb628c-5990-4d44-88d7-91500f68f9e1' class='xr-var-data-in' type='checkbox'><label for='data-4adb628c-5990-4d44-88d7-91500f68f9e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sodium_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-73978c65-e14b-4147-b9e4-b529a85e0684' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73978c65-e14b-4147-b9e4-b529a85e0684' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66fdb1e4-078e-4c74-b4d9-f826e1553925' class='xr-var-data-in' type='checkbox'><label for='data-66fdb1e4-078e-4c74-b4d9-f826e1553925' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_S_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cad1f31a-d597-4b2a-98b3-d1ea20ad1c42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cad1f31a-d597-4b2a-98b3-d1ea20ad1c42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dec00460-cac1-4ae8-b77e-45d53e5dab1f' class='xr-var-data-in' type='checkbox'><label for='data-dec00460-cac1-4ae8-b77e-45d53e5dab1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>sulphate_total_ug S_per_m3_qc sulphate_total_ug S_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>sulphate_total</dd><dt><span>ebas_unit :</span></dt><dd>ug S/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug S/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_S_per_m3_qc</span></div><div class='xr-var-dims'>(sulphate_total_ug_S_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c13832e3-341e-4485-a79e-ce73fdd8e034' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c13832e3-341e-4485-a79e-ce73fdd8e034' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45b29f86-153a-41a9-8b09-c6b300b03575' class='xr-var-data-in' type='checkbox'><label for='data-45b29f86-153a-41a9-8b09-c6b300b03575' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_S_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c992d25a-fe19-4d80-b3d0-4f2e91ecc0f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c992d25a-fe19-4d80-b3d0-4f2e91ecc0f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b9c4adc-5b14-4f75-8f38-7ba83a71a5a2' class='xr-var-data-in' type='checkbox'><label for='data-2b9c4adc-5b14-4f75-8f38-7ba83a71a5a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd103b30-ff9d-4d82-b1b7-c95b35af3840' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd103b30-ff9d-4d82-b1b7-c95b35af3840' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2d5804b-0218-4411-b5fd-f595c3a9f318' class='xr-var-data-in' type='checkbox'><label for='data-a2d5804b-0218-4411-b5fd-f595c3a9f318' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>sulphate_total_ug_per_m3_qc sulphate_total_ug_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>sulphate_total</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.06 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_comment :</span></dt><dd>Data converted on export from EBAS from &#x27;ug S/m3&#x27; to &#x27;ug/m3&#x27;, conversion factor 2.9962. Detection limit converted from &#x27;0.02 ug S/m3&#x27; to &#x27;0.06 ug/m3&#x27;, conversion factor 2.9962.</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_per_m3_qc</span></div><div class='xr-var-dims'>(sulphate_total_ug_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-29d7a19c-769e-45e2-b077-01cdf996b01a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29d7a19c-769e-45e2-b077-01cdf996b01a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e5f0b4f-c444-4182-9ba1-765ece6c999a' class='xr-var-data-in' type='checkbox'><label for='data-3e5f0b4f-c444-4182-9ba1-765ece6c999a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f285e969-ff85-4385-ba23-5184eb156277' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f285e969-ff85-4385-ba23-5184eb156277' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81925295-b5b5-4d8d-88e5-6e3b8b5c8d46' class='xr-var-data-in' type='checkbox'><label for='data-81925295-b5b5-4d8d-88e5-6e3b8b5c8d46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphur_dioxide</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-96567704-89cd-4277-ac6f-f6d39874b29d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96567704-89cd-4277-ac6f-f6d39874b29d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9c96b30-80ba-45b9-b5d1-1c4276026394' class='xr-var-data-in' type='checkbox'><label for='data-e9c96b30-80ba-45b9-b5d1-1c4276026394' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_sulphur_dioxide_expressed_as_sulphur_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>sulphur_dioxide_qc sulphur_dioxide_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>sulphur_dioxide</dd><dt><span>ebas_unit :</span></dt><dd>ug S/m3</dd><dt><span>ebas_matrix :</span></dt><dd>air</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Cellulose</dd><dt><span>ebas_coating_solution :</span></dt><dd>KOH</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug S/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphur_dioxide_qc</span></div><div class='xr-var-dims'>(sulphur_dioxide_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3801f11e-8afa-4029-afef-fda5833b4be1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3801f11e-8afa-4029-afef-fda5833b4be1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4fbf7a9-b07e-414f-ad4f-575f8ab10c38' class='xr-var-data-in' type='checkbox'><label for='data-b4fbf7a9-b07e-414f-ad4f-575f8ab10c38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphur_dioxide_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7cbb44d2-fc66-410a-b99c-258d6f1eecf7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7cbb44d2-fc66-410a-b99c-258d6f1eecf7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3081937f-f0dc-4ce5-b679-a363c43a75cc' class='xr-var-data-in' type='checkbox'><label for='data-3081937f-f0dc-4ce5-b679-a363c43a75cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-091f477a-042a-4001-a94d-2de996c9691d' class='xr-section-summary-in' type='checkbox'  ><label for='section-091f477a-042a-4001-a94d-2de996c9691d' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e53c6e94-1d02-4b5b-912f-4b7ce0282f0f' class='xr-index-data-in' type='checkbox'/><label for='index-e53c6e94-1d02-4b5b-912f-4b7ce0282f0f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-01-01 19:00:00&#x27;, &#x27;2021-01-02 19:00:00&#x27;,\n",
+       "               &#x27;2021-01-03 19:00:00&#x27;, &#x27;2021-01-04 19:00:00&#x27;,\n",
+       "               &#x27;2021-01-05 19:00:00&#x27;, &#x27;2021-01-06 19:00:00&#x27;,\n",
+       "               &#x27;2021-01-07 19:00:00&#x27;, &#x27;2021-01-08 19:00:00&#x27;,\n",
+       "               &#x27;2021-01-09 19:00:00&#x27;, &#x27;2021-01-10 19:00:00&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2022-12-22 19:00:00&#x27;, &#x27;2022-12-23 19:00:00&#x27;,\n",
+       "               &#x27;2022-12-24 19:00:00&#x27;, &#x27;2022-12-25 19:00:00&#x27;,\n",
+       "               &#x27;2022-12-26 19:00:00&#x27;, &#x27;2022-12-27 19:00:00&#x27;,\n",
+       "               &#x27;2022-12-28 19:00:00&#x27;, &#x27;2022-12-29 19:00:00&#x27;,\n",
+       "               &#x27;2022-12-30 19:00:00&#x27;, &#x27;2022-12-31 19:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=730, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>metadata_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4b2dfbeb-dde8-42d0-82c7-9848edcb4dbc' class='xr-index-data-in' type='checkbox'/><label for='index-4b2dfbeb-dde8-42d0-82c7-9848edcb4dbc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-07-02 19:00:00&#x27;, &#x27;2022-07-02 19:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;metadata_time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-006f714a-0af6-404b-83e9-8ef7b9184806' class='xr-section-summary-in' type='checkbox'  ><label for='section-006f714a-0af6-404b-83e9-8ef7b9184806' class='xr-section-summary' >Attributes: <span>(106)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8, ACDD-1.3</dd><dt><span>featureType :</span></dt><dd>timeSeries</dd><dt><span>title :</span></dt><dd>Ground based in situ observations of filter_3pack at Zeppelin mountain (Ny-Ålesund) (NO0042G)</dd><dt><span>keywords :</span></dt><dd>mass_concentration_of_nitrate_in_dry_aerosol_particles_in _air, potassium, mass_concentration_of_sodium_in_dry_aerosol_particles_in _air, chloride, air, nitrate, sodium, NILU, nitric_acid, aerosol, ammonia, ammonium, mass_concentration_of_calcium_in_dry_aerosol_particles_in _air, EMEP, mass_concentration_of_potassium_in_dry_aerosol_particles_in _air, mass_concentration_of_nitric_acid_expressed_as_nitrogen_in_air, sulphur_dioxide, AMAP, mass_concentration_of_ammonium_expressed_as_nitrogen_in_dry_aerosol_particles_in _air, CAMP, calcium, magnesium, mass_concentration_of_sulphur_dioxide_expressed_as_sulphur_in_air, NO0042G, mass_concentration_of_ammonium_in_dry_aerosol_particles_in _air, mass_concentration_of_nitrate_expressed_as_nitrogen_in_dry_aerosol_particles_in _air, mass_concentration_of_magnesium_in_dry_aerosol_particles_in _air, mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air, mass_concentration_of_chloride_in_dry_aerosol_particles_in _air, Zeppelin mountain (Ny-Ålesund), sulphate_total, mass_concentration_of_ammonia_expressed_as_nitrogen_in_air</dd><dt><span>id :</span></dt><dd>NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc</dd><dt><span>naming_authority :</span></dt><dd>EBAS</dd><dt><span>project :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>summary :</span></dt><dd>Ground based in situ observations of filter_3pack at Zeppelin mountain (Ny-Ålesund) (NO0042G). These measurements are gathered as a part of the following projects AMAP, CAMP, EMEP, NILU and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: ammonia in air (mass_concentration_of_ammonia_expressed_as_nitrogen_in_air), ammonium in aerosol (mass_concentration_of_ammonium_expressed_as_nitrogen_in_dry_aerosol_particles_in _air), ammonium in aerosol (mass_concentration_of_ammonium_in_dry_aerosol_particles_in _air), calcium in aerosol (mass_concentration_of_calcium_in_dry_aerosol_particles_in _air), chloride in aerosol (mass_concentration_of_chloride_in_dry_aerosol_particles_in _air), magnesium in aerosol (mass_concentration_of_magnesium_in_dry_aerosol_particles_in _air), nitrate in aerosol (mass_concentration_of_nitrate_expressed_as_nitrogen_in_dry_aerosol_particles_in _air), nitrate in aerosol (mass_concentration_of_nitrate_in_dry_aerosol_particles_in _air), nitric_acid in air (mass_concentration_of_nitric_acid_expressed_as_nitrogen_in_air), potassium in aerosol (mass_concentration_of_potassium_in_dry_aerosol_particles_in _air), sodium in aerosol (mass_concentration_of_sodium_in_dry_aerosol_particles_in _air), sulphate_total in aerosol (mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air), sulphate_total in aerosol (mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air), sulphur_dioxide in air (mass_concentration_of_sulphur_dioxide_expressed_as_sulphur_in_air)</dd><dt><span>source :</span></dt><dd>surface observation</dd><dt><span>institution :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway</dd><dt><span>processing_level :</span></dt><dd>processing_level_test</dd><dt><span>date_created :</span></dt><dd>2023-03-14T14:00:50 UTC</dd><dt><span>date_metadata_modified :</span></dt><dd>2023-03-14T14:00:50 UTC</dd><dt><span>creator_name :</span></dt><dd>Wenche Aas</dd><dt><span>creator_type :</span></dt><dd>person</dd><dt><span>creator_email :</span></dt><dd>waa@nilu.no</dd><dt><span>creator_institution :</span></dt><dd>&quot;Norwegian Institute for Air Research, Atmosphere and Climate Department, NILU&quot;</dd><dt><span>contributor_name :</span></dt><dd>Anne Hjellbrekke</dd><dt><span>contributor_role :</span></dt><dd>data submitter</dd><dt><span>publisher_type :</span></dt><dd>institution</dd><dt><span>publisher_name :</span></dt><dd>NILU - Norwegian Institute for Air Research, ATMOS, EBAS</dd><dt><span>publisher_institution :</span></dt><dd>NILU - Norwegian Institute for Air Research, ATMOS, EBAS</dd><dt><span>publisher_email :</span></dt><dd>ebas@nilu.no</dd><dt><span>publisher_url :</span></dt><dd>https://www.nilu.no/</dd><dt><span>geospatial_bounds :</span></dt><dd>POINT Z (78.90715 11.88668 474.0)</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>EPSG:4979</dd><dt><span>geospatial_lat_min :</span></dt><dd>78.90715</dd><dt><span>geospatial_lat_max :</span></dt><dd>78.90715</dd><dt><span>geospatial_lon_min :</span></dt><dd>11.88668</dd><dt><span>geospatial_lon_max :</span></dt><dd>11.88668</dd><dt><span>geospatial_vertical_min :</span></dt><dd>474.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>474.0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>time_coverage_start :</span></dt><dd>2021-01-01T07:00:00 UTC</dd><dt><span>time_coverage_end :</span></dt><dd>2023-01-01T07:00:00 UTC</dd><dt><span>time_coverage_duration :</span></dt><dd>P0002-00-00T00:00:00</dd><dt><span>time_coverage_resolution :</span></dt><dd>P0000-00-01T00:00:00</dd><dt><span>timezone :</span></dt><dd>UTC</dd><dt><span>ebas_data_definition :</span></dt><dd>EBAS_1.1</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_set_type_code :</span></dt><dd>TI</dd><dt><span>ebas_timezone :</span></dt><dd>UTC</dd><dt><span>ebas_file_name :</span></dt><dd>NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc</dd><dt><span>ebas_file_creation :</span></dt><dd>2023-05-11T11:26:58.786202 UTC</dd><dt><span>ebas_export_state :</span></dt><dd>2023-05-11T10:25:03.246277 UTC</dd><dt><span>ebas_export_filter :</span></dt><dd>exclude-900,exclude-invalid</dd><dt><span>ebas_startdate :</span></dt><dd>20210101070000</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_period_code :</span></dt><dd>2y</dd><dt><span>ebas_resolution_code :</span></dt><dd>1d</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>comment :</span></dt><dd>{\n",
+       "    &quot;Data definition&quot;: &quot;EBAS_1.1&quot;,\n",
+       "    &quot;Data license&quot;: &quot;https://creativecommons.org/licenses/by/4.0/&quot;,\n",
+       "    &quot;Set type code&quot;: &quot;TI&quot;,\n",
+       "    &quot;Timezone&quot;: &quot;UTC&quot;,\n",
+       "    &quot;File name&quot;: &quot;NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&quot;,\n",
+       "    &quot;File creation&quot;: &quot;2023-05-11T11:26:58.786202 UTC&quot;,\n",
+       "    &quot;Export state&quot;: &quot;2023-05-11T10:25:03.246277 UTC&quot;,\n",
+       "    &quot;Export filter&quot;: &quot;exclude-900,exclude-invalid&quot;,\n",
+       "    &quot;Startdate&quot;: &quot;20210101070000&quot;,\n",
+       "    &quot;Revision date&quot;: &quot;20230314140050&quot;,\n",
+       "    &quot;Statistics&quot;: &quot;arithmetic mean&quot;,\n",
+       "    &quot;Data level&quot;: &quot;2&quot;,\n",
+       "    &quot;Period code&quot;: &quot;2y&quot;,\n",
+       "    &quot;Resolution code&quot;: &quot;1d&quot;,\n",
+       "    &quot;Station code&quot;: &quot;NO0042G&quot;,\n",
+       "    &quot;Platform code&quot;: &quot;NO0042S&quot;,\n",
+       "    &quot;Station name&quot;: &quot;Zeppelin mountain (Ny-Ålesund)&quot;,\n",
+       "    &quot;Station WDCA-ID&quot;: &quot;GAWANO__ZEP&quot;,\n",
+       "    &quot;Station GAW-ID&quot;: &quot;ZEP&quot;,\n",
+       "    &quot;Station GAW-Name&quot;: &quot;Zeppelin Mountain (Ny Ålesund)&quot;,\n",
+       "    &quot;Station land use&quot;: &quot;Gravel and stone&quot;,\n",
+       "    &quot;Station setting&quot;: &quot;Polar&quot;,\n",
+       "    &quot;Station GAW type&quot;: &quot;G&quot;,\n",
+       "    &quot;Station WMO region&quot;: &quot;6&quot;,\n",
+       "    &quot;Station latitude&quot;: &quot;78.90715&quot;,\n",
+       "    &quot;Station longitude&quot;: &quot;11.88668&quot;,\n",
+       "    &quot;Station altitude&quot;: &quot;474.0 m&quot;,\n",
+       "    &quot;Regime&quot;: &quot;IMG&quot;,\n",
+       "    &quot;Laboratory code&quot;: &quot;NO01L&quot;,\n",
+       "    &quot;Instrument type&quot;: &quot;filter_3pack&quot;,\n",
+       "    &quot;Instrument name&quot;: &quot;f3p_d_0042&quot;,\n",
+       "    &quot;Instrument manufacturer&quot;: &quot;NILU&quot;,\n",
+       "    &quot;Instrument model&quot;: &quot;Three stage open face&quot;,\n",
+       "    &quot;Analytical laboratory code&quot;: &quot;NO01L&quot;,\n",
+       "    &quot;Analytical measurement technique&quot;: &quot;IC&quot;,\n",
+       "    &quot;Analytical instrument name&quot;: &quot;IC&quot;,\n",
+       "    &quot;Analytical instrument manufacturer&quot;: &quot;Dionex&quot;,\n",
+       "    &quot;Analytical instrument model&quot;: &quot;ICS-2100&quot;,\n",
+       "    &quot;Method ref&quot;: &quot;NO01L_IC&quot;,\n",
+       "    &quot;Standard method&quot;: &quot;SOP=EMEP_manual_v2014&quot;,\n",
+       "    &quot;Inlet type&quot;: &quot;Hat or hood&quot;,\n",
+       "    &quot;Inlet description&quot;: &quot;Downward facing&quot;,\n",
+       "    &quot;Flow rate&quot;: &quot;17.4 l/min&quot;,\n",
+       "    &quot;Sample preparation&quot;: &quot;Water extraction after ultrasonic treatment&quot;,\n",
+       "    &quot;Blank correction&quot;: &quot;Blank corrected&quot;,\n",
+       "    &quot;Humidity/temperature control&quot;: &quot;None&quot;,\n",
+       "    &quot;Humidity/temperature control description&quot;: &quot;Filter kept at ambient conditions together with sampling head&quot;,\n",
+       "    &quot;Volume std. temperature&quot;: &quot;ambient&quot;,\n",
+       "    &quot;Volume std. pressure&quot;: &quot;ambient&quot;,\n",
+       "    &quot;Detection limit expl.&quot;: &quot;Detection limit is determined by taking three times standard deviation of ensemble of field blanks&quot;,\n",
+       "    &quot;Zero/negative values code&quot;: &quot;Zero/negative impossible&quot;,\n",
+       "    &quot;Zero/negative values&quot;: &quot;Values below detection limit are reported as DL value, flagged with 781.&quot;,\n",
+       "    &quot;Organization&quot;: &quot;NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway&quot;,\n",
+       "    &quot;Framework acronym&quot;: &quot;AMAP, CAMP, EMEP, NILU&quot;,\n",
+       "    &quot;Framework name&quot;: &quot;, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research&quot;,\n",
+       "    &quot;Framework description&quot;: &quot;, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.&quot;,\n",
+       "    &quot;Framework contact name&quot;: &quot;Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth&quot;,\n",
+       "    &quot;Framework contact email&quot;: &quot;waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no&quot;,\n",
+       "    &quot;Originator&quot;: &quot;Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970&quot;,\n",
+       "    &quot;Submitter&quot;: &quot;Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway&quot;\n",
+       "}</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF-1.7, ACDD-1.3</dd><dt><span>history :</span></dt><dd>None</dd><dt><span>creator_url :</span></dt><dd>ebas.nilu.no</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 183kB\n",
+       "Dimensions:                                  (time: 730, tbnds: 2,\n",
+       "                                              metadata_time: 2,\n",
+       "                                              ammonia_qc_flags: 1,\n",
+       "                                              ammonium_ug_N_per_m3_qc_flags: 1,\n",
+       "                                              ammonium_ug_per_m3_qc_flags: 1,\n",
+       "                                              calcium_qc_flags: 1,\n",
+       "                                              ...\n",
+       "                                              nitric_acid_qc_flags: 1,\n",
+       "                                              potassium_qc_flags: 1,\n",
+       "                                              sodium_qc_flags: 1,\n",
+       "                                              sulphate_total_ug_S_per_m3_qc_flags: 1,\n",
+       "                                              sulphate_total_ug_per_m3_qc_flags: 1,\n",
+       "                                              sulphur_dioxide_qc_flags: 1)\n",
+       "Coordinates:\n",
+       "  * time                                     (time) datetime64[ns] 6kB 2021-0...\n",
+       "  * metadata_time                            (metadata_time) datetime64[ns] 16B ...\n",
+       "Dimensions without coordinates: tbnds, ammonia_qc_flags,\n",
+       "                                ammonium_ug_N_per_m3_qc_flags,\n",
+       "                                ammonium_ug_per_m3_qc_flags, calcium_qc_flags,\n",
+       "                                chloride_qc_flags, magnesium_qc_flags,\n",
+       "                                nitrate_ug_N_per_m3_qc_flags,\n",
+       "                                nitrate_ug_per_m3_qc_flags,\n",
+       "                                nitric_acid_qc_flags, potassium_qc_flags,\n",
+       "                                sodium_qc_flags,\n",
+       "                                sulphate_total_ug_S_per_m3_qc_flags,\n",
+       "                                sulphate_total_ug_per_m3_qc_flags,\n",
+       "                                sulphur_dioxide_qc_flags\n",
+       "Data variables: (12/44)\n",
+       "    time_bnds                                (time, tbnds) datetime64[ns] 12kB ...\n",
+       "    metadata_time_bnds                       (metadata_time, tbnds) datetime64[ns] 32B ...\n",
+       "    ammonia                                  (time) float64 6kB ...\n",
+       "    ammonia_qc                               (ammonia_qc_flags, time) float64 6kB ...\n",
+       "    ammonia_ebasmetadata                     (metadata_time) |S64 128B ...\n",
+       "    ammonium_ug_N_per_m3                     (time) float64 6kB ...\n",
+       "    ...                                       ...\n",
+       "    sulphate_total_ug_per_m3                 (time) float64 6kB ...\n",
+       "    sulphate_total_ug_per_m3_qc              (sulphate_total_ug_per_m3_qc_flags, time) float64 6kB ...\n",
+       "    sulphate_total_ug_per_m3_ebasmetadata    (metadata_time) |S64 128B ...\n",
+       "    sulphur_dioxide                          (time) float64 6kB ...\n",
+       "    sulphur_dioxide_qc                       (sulphur_dioxide_qc_flags, time) float64 6kB ...\n",
+       "    sulphur_dioxide_ebasmetadata             (metadata_time) |S64 128B ...\n",
+       "Attributes: (12/106)\n",
+       "    Conventions:                                   CF-1.8, ACDD-1.3\n",
+       "    featureType:                                   timeSeries\n",
+       "    title:                                         Ground based in situ obser...\n",
+       "    keywords:                                      mass_concentration_of_nitr...\n",
+       "    id:                                            NO0042G.20210101070000.202...\n",
+       "    naming_authority:                              EBAS\n",
+       "    ...                                            ...\n",
+       "    geospatial_lat_units:                          degrees_north\n",
+       "    geospatial_lon_units:                          degrees_east\n",
+       "    comment:                                       {\\n    \"Data definition\": ...\n",
+       "    standard_name_vocabulary:                      CF-1.7, ACDD-1.3\n",
+       "    history:                                       None\n",
+       "    creator_url:                                   ebas.nilu.no"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_single_file = xr.open_dataset(file_to_read)\n",
+    "ds_single_file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f4257b00950>]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds_single_file['sulphate_total_ug_S_per_m3'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:pangeo-notebook]",
+   "language": "python",
+   "name": "conda-env-pangeo-notebook-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/_sources/learning/notebooks/masked_and_weighted_average.ipynb b/_sources/learning/notebooks/masked_and_weighted_average.ipynb
new file mode 100644
index 0000000..f786a7f
--- /dev/null
+++ b/_sources/learning/notebooks/masked_and_weighted_average.ipynb
@@ -0,0 +1,1354 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Using masks and computing weighted average"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This example is based from xarray example http://xarray.pydata.org/en/stable/examples/area_weighted_temperature.html"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Import python packages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "xr.set_options(display_style='html')\n",
+    "import intake\n",
+    "import cftime\n",
+    "import matplotlib.pyplot as plt\n",
+    "import cartopy.crs as ccrs\n",
+    "import numpy as np\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<p><strong>pangeo-cmip6 catalog with 7674 dataset(s) from 514818 asset(s)</strong>:</p> <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unique</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>activity_id</th>\n",
+       "      <td>18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>institution_id</th>\n",
+       "      <td>36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_id</th>\n",
+       "      <td>88</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>experiment_id</th>\n",
+       "      <td>170</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>member_id</th>\n",
+       "      <td>657</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>table_id</th>\n",
+       "      <td>37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>variable_id</th>\n",
+       "      <td>700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>grid_label</th>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>zstore</th>\n",
+       "      <td>514818</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <td>60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>version</th>\n",
+       "      <td>736</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>derived_variable_id</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cat_url = \"https://storage.googleapis.com/cmip6/pangeo-cmip6.json\"\n",
+    "col = intake.open_esm_datastore(cat_url)\n",
+    "col"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Search data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>activity_id</th>\n",
+       "      <th>institution_id</th>\n",
+       "      <th>source_id</th>\n",
+       "      <th>experiment_id</th>\n",
+       "      <th>member_id</th>\n",
+       "      <th>table_id</th>\n",
+       "      <th>variable_id</th>\n",
+       "      <th>grid_label</th>\n",
+       "      <th>zstore</th>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <th>version</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>CMIP</td>\n",
+       "      <td>NCC</td>\n",
+       "      <td>NorESM2-LM</td>\n",
+       "      <td>historical</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>Amon</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>gn</td>\n",
+       "      <td>gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historica...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>20190815</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  activity_id institution_id   source_id experiment_id member_id table_id  \\\n",
+       "0        CMIP            NCC  NorESM2-LM    historical  r1i1p1f1     Amon   \n",
+       "\n",
+       "  variable_id grid_label                                             zstore  \\\n",
+       "0         tas         gn  gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historica...   \n",
+       "\n",
+       "   dcpp_init_year   version  \n",
+       "0             NaN  20190815  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat = col.search(source_id=['NorESM2-LM'], experiment_id=['historical'], table_id=['Amon'], variable_id=['tas'], member_id=['r1i1p1f1'])\n",
+    "cat.df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create dictionary from the list of datasets we found\n",
+    "- This step may take several minutes so be patient!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
+      "\t'activity_id.institution_id.source_id.experiment_id.table_id.grid_label'\n"
+     ]
+    },
+    {
+     "data": {
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+       "\n",
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+       "        border: none;\n",
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+       "    }\n",
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+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='1' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [1/1 00:12&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dset_dict = cat.to_dataset_dict(zarr_kwargs={'use_cftime':True})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['CMIP.NCC.NorESM2-LM.historical.Amon.gn']"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "list(dset_dict.keys())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 110MB\n",
+       "Dimensions:         (lat: 96, bnds: 2, lon: 144, member_id: 1,\n",
+       "                     dcpp_init_year: 1, time: 1980)\n",
+       "Coordinates:\n",
+       "    height          float64 8B ...\n",
+       "  * lat             (lat) float64 768B -90.0 -88.11 -86.21 ... 86.21 88.11 90.0\n",
+       "    lat_bnds        (lat, bnds) float64 2kB dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;\n",
+       "  * lon             (lon) float64 1kB 0.0 2.5 5.0 7.5 ... 352.5 355.0 357.5\n",
+       "    lon_bnds        (lon, bnds) float64 2kB dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;\n",
+       "  * time            (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:...\n",
+       "    time_bnds       (time, bnds) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 109MB dask.array&lt;chunksize=(1, 1, 990, 96, 144), meta=np.ndarray&gt;\n",
+       "Attributes: (12/65)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    Hybrid-restart from year 1600-01-01 of ...\n",
+       "    branch_time:                      0.0\n",
+       "    branch_time_in_child:             0.0\n",
+       "    branch_time_in_parent:            430335.0\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     tas\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/hi...\n",
+       "    intake_esm_attrs:version:         20190815\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCC.NorESM2-LM.historical.Amon.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2f5bb113-4108-45a8-8b6e-a23f5ff0cadb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2f5bb113-4108-45a8-8b6e-a23f5ff0cadb' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 96</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 144</li><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-24910492-b4b3-49c9-b1db-625b27633c26' class='xr-section-summary-in' type='checkbox'  checked><label for='section-24910492-b4b3-49c9-b1db-625b27633c26' class='xr-section-summary' >Coordinates: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-25bffdd6-7a32-489d-a7d3-a8741cf0e77d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25bffdd6-7a32-489d-a7d3-a8741cf0e77d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-136117b1-8d4a-4c51-9f4e-2b9f7507180e' class='xr-var-data-in' type='checkbox'><label for='data-136117b1-8d4a-4c51-9f4e-2b9f7507180e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.11 -86.21 ... 88.11 90.0</div><input id='attrs-add5a11d-33a7-4d01-92fe-04dafb7aefd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-add5a11d-33a7-4d01-92fe-04dafb7aefd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67431778-c956-4f2f-b711-81c139a3dd4e' class='xr-var-data-in' type='checkbox'><label for='data-67431778-c956-4f2f-b711-81c139a3dd4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -88.105263, -86.210526, -84.315789, -82.421053, -80.526316,\n",
+       "       -78.631579, -76.736842, -74.842105, -72.947368, -71.052632, -69.157895,\n",
+       "       -67.263158, -65.368421, -63.473684, -61.578947, -59.684211, -57.789474,\n",
+       "       -55.894737, -54.      , -52.105263, -50.210526, -48.315789, -46.421053,\n",
+       "       -44.526316, -42.631579, -40.736842, -38.842105, -36.947368, -35.052632,\n",
+       "       -33.157895, -31.263158, -29.368421, -27.473684, -25.578947, -23.684211,\n",
+       "       -21.789474, -19.894737, -18.      , -16.105263, -14.210526, -12.315789,\n",
+       "       -10.421053,  -8.526316,  -6.631579,  -4.736842,  -2.842105,  -0.947368,\n",
+       "         0.947368,   2.842105,   4.736842,   6.631579,   8.526316,  10.421053,\n",
+       "        12.315789,  14.210526,  16.105263,  18.      ,  19.894737,  21.789474,\n",
+       "        23.684211,  25.578947,  27.473684,  29.368421,  31.263158,  33.157895,\n",
+       "        35.052632,  36.947368,  38.842105,  40.736842,  42.631579,  44.526316,\n",
+       "        46.421053,  48.315789,  50.210526,  52.105263,  54.      ,  55.894737,\n",
+       "        57.789474,  59.684211,  61.578947,  63.473684,  65.368421,  67.263158,\n",
+       "        69.157895,  71.052632,  72.947368,  74.842105,  76.736842,  78.631579,\n",
+       "        80.526316,  82.421053,  84.315789,  86.210526,  88.105263,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;</div><input id='attrs-2ad0f556-14c8-4960-ab9d-3dfc3e1859ea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2ad0f556-14c8-4960-ab9d-3dfc3e1859ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9cac7e1-55c0-4472-b83b-db6b1d64de40' class='xr-var-data-in' type='checkbox'><label for='data-b9cac7e1-55c0-4472-b83b-db6b1d64de40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 kiB </td>\n",
+       "                        <td> 1.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (96, 2) </td>\n",
+       "                        <td> (96, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"79\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"29\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"29\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"29\" y1=\"0\" x2=\"29\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 29.2612335534925,0.0 29.2612335534925,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"14.630617\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"49.261234\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,49.261234,60.000000)\">96</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5 5.0 ... 352.5 355.0 357.5</div><input id='attrs-8b12e301-791e-42c8-82f9-1bf903daab62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b12e301-791e-42c8-82f9-1bf903daab62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6440b1e2-4d43-40ba-bd3c-a1bc6c628f69' class='xr-var-data-in' type='checkbox'><label for='data-6440b1e2-4d43-40ba-bd3c-a1bc6c628f69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0. ,   2.5,   5. ,   7.5,  10. ,  12.5,  15. ,  17.5,  20. ,  22.5,\n",
+       "        25. ,  27.5,  30. ,  32.5,  35. ,  37.5,  40. ,  42.5,  45. ,  47.5,\n",
+       "        50. ,  52.5,  55. ,  57.5,  60. ,  62.5,  65. ,  67.5,  70. ,  72.5,\n",
+       "        75. ,  77.5,  80. ,  82.5,  85. ,  87.5,  90. ,  92.5,  95. ,  97.5,\n",
+       "       100. , 102.5, 105. , 107.5, 110. , 112.5, 115. , 117.5, 120. , 122.5,\n",
+       "       125. , 127.5, 130. , 132.5, 135. , 137.5, 140. , 142.5, 145. , 147.5,\n",
+       "       150. , 152.5, 155. , 157.5, 160. , 162.5, 165. , 167.5, 170. , 172.5,\n",
+       "       175. , 177.5, 180. , 182.5, 185. , 187.5, 190. , 192.5, 195. , 197.5,\n",
+       "       200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,\n",
+       "       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
+       "       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
+       "       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
+       "       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
+       "       325. , 327.5, 330. , 332.5, 335. , 337.5, 340. , 342.5, 345. , 347.5,\n",
+       "       350. , 352.5, 355. , 357.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;</div><input id='attrs-e7442090-4a19-4647-a8b4-ab92a8f44588' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7442090-4a19-4647-a8b4-ab92a8f44588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4eeb2154-4bc1-4828-8492-45f6c158b28f' class='xr-var-data-in' type='checkbox'><label for='data-4eeb2154-4bc1-4828-8492-45f6c158b28f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.25 kiB </td>\n",
+       "                        <td> 2.25 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (144, 2) </td>\n",
+       "                        <td> (144, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"77\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"27\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"27\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"27\" y1=\"0\" x2=\"27\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 27.054035963169408,0.0 27.054035963169408,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"13.527018\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"47.054036\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,47.054036,60.000000)\">144</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2014-12-...</div><input id='attrs-73258975-2fb9-449a-9ec7-a8d2bf6ea155' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73258975-2fb9-449a-9ec7-a8d2bf6ea155' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e06054b-f481-4a88-9c00-8b6014f55e0f' class='xr-var-data-in' type='checkbox'><label for='data-9e06054b-f481-4a88-9c00-8b6014f55e0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2014, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-4d0ce4ef-db65-4ec5-a879-36a4815dbf39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d0ce4ef-db65-4ec5-a879-36a4815dbf39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6f5a4a6-b35c-4a01-89d6-10dfda46bbcb' class='xr-var-data-in' type='checkbox'><label for='data-d6f5a4a6-b35c-4a01-89d6-10dfda46bbcb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-acc42975-e02e-4dad-84c6-2554daea5204' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-acc42975-e02e-4dad-84c6-2554daea5204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3620eb4-d6df-48ae-a736-2f6c76aea28b' class='xr-var-data-in' type='checkbox'><label for='data-c3620eb4-d6df-48ae-a736-2f6c76aea28b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-98ffee70-2221-4c81-a431-93fab9c1fb1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98ffee70-2221-4c81-a431-93fab9c1fb1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da08f6d4-9cda-4819-a825-8fa730341863' class='xr-var-data-in' type='checkbox'><label for='data-da08f6d4-9cda-4819-a825-8fa730341863' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0d0e4745-1664-4bc3-824c-73a1a6be2723' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0d0e4745-1664-4bc3-824c-73a1a6be2723' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 990, 96, 144), meta=np.ndarray&gt;</div><input id='attrs-a0ffedab-455b-46fe-8cbf-32c5ac361863' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0ffedab-455b-46fe-8cbf-32c5ac361863' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6943860-f327-41e6-a286-f0db563209ac' class='xr-var-data-in' type='checkbox'><label for='data-f6943860-f327-41e6-a286-f0db563209ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>history :</span></dt><dd>2019-08-15T12:42:20Z altered by CMOR: Treated scalar dimension: &#x27;height&#x27;. 2019-08-15T12:42:21Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>original_name :</span></dt><dd>TREFHT</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 104.41 MiB </td>\n",
+       "                        <td> 52.21 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 1980, 96, 144) </td>\n",
+       "                        <td> (1, 1, 990, 96, 144) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 2 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"347\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1</text>\n",
+       "  <text x=\"45.412617\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,45.412617,12.706308)\">1</text>\n",
+       "\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"95\" y1=\"0\" x2=\"165\" y2=\"70\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"95\" y1=\"0\" x2=\"95\" y2=\"34\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"165\" y1=\"70\" x2=\"165\" y2=\"104\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"95.0,0.0 165.58823529411765,70.58823529411765 165.58823529411765,104.9007638365262 95.0,34.31252854240854\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"95\" y1=\"0\" x2=\"131\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"95\" y1=\"0\" x2=\"165\" y2=\"70\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"131\" y1=\"0\" x2=\"202\" y2=\"70\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"165\" y1=\"70\" x2=\"202\" y2=\"70\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"165\" y1=\"104\" x2=\"202\" y2=\"104\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"165\" y1=\"70\" x2=\"165\" y2=\"104\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"202\" y1=\"70\" x2=\"202\" y2=\"104\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"165.58823529411765,70.58823529411765 202.35463992729706,70.58823529411765 202.35463992729706,104.9007638365262 165.58823529411765,104.9007638365262\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"183.971438\" y=\"124.900764\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >144</text>\n",
+       "  <text x=\"222.354640\" y=\"87.744500\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,222.354640,87.744500)\">96</text>\n",
+       "  <text x=\"120.294118\" y=\"89.606646\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,120.294118,89.606646)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-d7393555-5f4b-4bd3-8ed0-164f44ff1283' class='xr-section-summary-in' type='checkbox'  ><label for='section-d7393555-5f4b-4bd3-8ed0-164f44ff1283' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-938ffefc-eb5a-42c1-a92a-38e5e6733c8f' class='xr-index-data-in' type='checkbox'/><label for='index-938ffefc-eb5a-42c1-a92a-38e5e6733c8f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([              -90.0,  -88.10526315789474,  -86.21052631578948,\n",
+       "         -84.3157894736842,  -82.42105263157895,  -80.52631578947368,\n",
+       "        -78.63157894736842,  -76.73684210526316,  -74.84210526315789,\n",
+       "        -72.94736842105263,  -71.05263157894737,  -69.15789473684211,\n",
+       "        -67.26315789473685,  -65.36842105263158, -63.473684210526315,\n",
+       "       -61.578947368421055, -59.684210526315795,  -57.78947368421053,\n",
+       "        -55.89473684210527,               -54.0,  -52.10526315789474,\n",
+       "        -50.21052631578947,  -48.31578947368421,  -46.42105263157895,\n",
+       "       -44.526315789473685, -42.631578947368425,  -40.73684210526316,\n",
+       "         -38.8421052631579,  -36.94736842105264,  -35.05263157894737,\n",
+       "        -33.15789473684211, -31.263157894736842, -29.368421052631582,\n",
+       "       -27.473684210526322, -25.578947368421055, -23.684210526315795,\n",
+       "       -21.789473684210535,  -19.89473684210526,               -18.0,\n",
+       "        -16.10526315789474,  -14.21052631578948,  -12.31578947368422,\n",
+       "       -10.421052631578945,  -8.526315789473685,  -6.631578947368425,\n",
+       "        -4.736842105263165, -2.8421052631579045, -0.9473684210526301,\n",
+       "        0.9473684210526301,  2.8421052631578902,    4.73684210526315,\n",
+       "         6.631578947368411,   8.526315789473685,  10.421052631578945,\n",
+       "        12.315789473684205,  14.210526315789465,  16.105263157894726,\n",
+       "                      18.0,   19.89473684210526,   21.78947368421052,\n",
+       "         23.68421052631578,   25.57894736842104,  27.473684210526315,\n",
+       "        29.368421052631575,  31.263157894736835,  33.157894736842096,\n",
+       "        35.052631578947356,   36.94736842105263,   38.84210526315789,\n",
+       "         40.73684210526315,   42.63157894736841,   44.52631578947367,\n",
+       "         46.42105263157893,   48.31578947368419,   50.21052631578948,\n",
+       "         52.10526315789474,                54.0,   55.89473684210526,\n",
+       "         57.78947368421052,   59.68421052631578,   61.57894736842104,\n",
+       "          63.4736842105263,   65.36842105263156,   67.26315789473682,\n",
+       "         69.15789473684211,   71.05263157894737,   72.94736842105263,\n",
+       "         74.84210526315789,   76.73684210526315,   78.63157894736841,\n",
+       "         80.52631578947367,   82.42105263157893,   84.31578947368419,\n",
+       "         86.21052631578945,   88.10526315789474,                90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d2d8b648-b942-4086-877f-64848dba7677' class='xr-index-data-in' type='checkbox'/><label for='index-d2d8b648-b942-4086-877f-64848dba7677' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.0,   2.5,   5.0,   7.5,  10.0,  12.5,  15.0,  17.5,  20.0,  22.5,\n",
+       "       ...\n",
+       "       335.0, 337.5, 340.0, 342.5, 345.0, 347.5, 350.0, 352.5, 355.0, 357.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=144))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-42ec8893-285d-4063-899d-498012cca2e3' class='xr-index-data-in' type='checkbox'/><label for='index-42ec8893-285d-4063-899d-498012cca2e3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,\n",
+       "             1850-04-16 00:00:00, 1850-05-16 12:00:00, 1850-06-16 00:00:00,\n",
+       "             1850-07-16 12:00:00, 1850-08-16 12:00:00, 1850-09-16 00:00:00,\n",
+       "             1850-10-16 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-16 12:00:00, 2014-04-16 00:00:00, 2014-05-16 12:00:00,\n",
+       "             2014-06-16 00:00:00, 2014-07-16 12:00:00, 2014-08-16 12:00:00,\n",
+       "             2014-09-16 00:00:00, 2014-10-16 12:00:00, 2014-11-16 00:00:00,\n",
+       "             2014-12-16 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2a11e953-0839-4697-9436-51600baf9acf' class='xr-index-data-in' type='checkbox'/><label for='index-2a11e953-0839-4697-9436-51600baf9acf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4f928d45-6df3-4efe-841f-45ea08d37338' class='xr-index-data-in' type='checkbox'/><label for='index-4f928d45-6df3-4efe-841f-45ea08d37338' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3fb8dc2c-430c-4bb7-97a2-d9ad9606c2f2' class='xr-section-summary-in' type='checkbox'  ><label for='section-3fb8dc2c-430c-4bb7-97a2-d9ad9606c2f2' class='xr-section-summary' >Attributes: <span>(65)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>Hybrid-restart from year 1600-01-01 of piControl</dd><dt><span>branch_time :</span></dt><dd>0.0</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>430335.0</dd><dt><span>cmor_version :</span></dt><dd>3.5.0</dd><dt><span>contact :</span></dt><dd>Please send any requests or bug reports to noresm-ncc@met.no.</dd><dt><span>creation_date :</span></dt><dd>2019-08-15T12:42:21Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.31</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCC.NorESM2-LM.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>finite-volume grid with 1.9x2.5 degree lat/lon resolution</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2019-08-15T12:42:21Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>NorESM Climate modeling Consortium consisting of CICERO (Center for International Climate and Environmental Research, Oslo 0349), MET-Norway (Norwegian Meteorological Institute, Oslo 0313), NERSC (Nansen Environmental and Remote Sensing Center, Bergen 5006), NILU (Norwegian Institute for Air Research, Kjeller 2027), UiB (University of Bergen, Bergen 5007), UiO (University of Oslo, Oslo 0313) and UNI (Uni Research, Bergen 5008), Norway. Mailing address: NCC, c/o MET-Norway, Henrik Mohns plass 1, Oslo 0313, Norway</dd><dt><span>institution_id :</span></dt><dd>NCC</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by NCC is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https:///pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_id :</span></dt><dd>NorESM2-LM</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>NorESM2-LM</dd><dt><span>parent_sub_experiment_id :</span></dt><dd>none</dd><dt><span>parent_time_units :</span></dt><dd>days since 0421-01-01</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>N/A</dd><dt><span>source :</span></dt><dd>NorESM2-LM (2017): \n",
+       "aerosol: OsloAero\n",
+       "atmos: CAM-OSLO (2 degree resolution; 144 x 96; 32 levels; top level 3 mb)\n",
+       "atmosChem: OsloChemSimp\n",
+       "land: CLM\n",
+       "landIce: CISM\n",
+       "ocean: MICOM (1 degree resolution; 360 x 384; 70 levels; top grid cell minimum 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data])\n",
+       "ocnBgchem: HAMOCC\n",
+       "seaIce: CICE</dd><dt><span>source_id :</span></dt><dd>NorESM2-LM</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>status :</span></dt><dd>2020-04-30;created; by gcs.cmip6.ldeo@gmail.com</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(24 July 2019) MD5:08e314340b9dd440c36c1b8e484514f4</dd><dt><span>title :</span></dt><dd>NorESM2-LM output prepared for CMIP6</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/2486cf87-033c-4848-ab3e-e828c3b7c759\n",
+       "hdl:21.14100/8d2ec216-30d3-4f90-8664-7cf75e29780b\n",
+       "hdl:21.14100/9f798305-d0cf-4eac-89b0-b13dc25574ca\n",
+       "hdl:21.14100/e0da9277-4784-446b-b3b5-ba33bb18cc3a\n",
+       "hdl:21.14100/ca48487c-955a-4b15-9582-5ce55ce39c73\n",
+       "hdl:21.14100/fc7602aa-fd09-49d8-94c6-e619622c211b\n",
+       "hdl:21.14100/cd51a9c2-0a94-45b2-8d9b-59bcb3467214\n",
+       "hdl:21.14100/9b7ad334-1217-4229-98e8-b5a9287c0e5e\n",
+       "hdl:21.14100/043ca527-40c7-451f-990b-ccc94720f612\n",
+       "hdl:21.14100/a9613498-ea0d-4be4-97e8-77661872798d\n",
+       "hdl:21.14100/52699832-d86c-491b-a0a4-2f27d9ee4d69\n",
+       "hdl:21.14100/358c4a18-33b2-4c44-bd30-f6125a4df63c\n",
+       "hdl:21.14100/77254eaf-90ca-44e7-9a3c-763a840e188f\n",
+       "hdl:21.14100/62aed49c-6ca5-4027-80fe-4ddd99af575a\n",
+       "hdl:21.14100/83ffe172-769b-42b1-b979-b92d768f60fd\n",
+       "hdl:21.14100/91a8c4e2-d33b-4b87-a978-0247d8112ef3\n",
+       "hdl:21.14100/e8fb384f-d5a7-41e1-bf12-b8de3e2ffb80</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/2486cf87-033c-4848-ab3e-e828c3b7c759\n",
+       "hdl:21.14100/8d2ec216-30d3-4f90-8664-7cf75e29780b\n",
+       "hdl:21.14100/9f798305-d0cf-4eac-89b0-b13dc25574ca\n",
+       "hdl:21.14100/e0da9277-4784-446b-b3b5-ba33bb18cc3a\n",
+       "hdl:21.14100/ca48487c-955a-4b15-9582-5ce55ce39c73\n",
+       "hdl:21.14100/fc7602aa-fd09-49d8-94c6-e619622c211b\n",
+       "hdl:21.14100/cd51a9c2-0a94-45b2-8d9b-59bcb3467214\n",
+       "hdl:21.14100/9b7ad334-1217-4229-98e8-b5a9287c0e5e\n",
+       "hdl:21.14100/043ca527-40c7-451f-990b-ccc94720f612\n",
+       "hdl:21.14100/a9613498-ea0d-4be4-97e8-77661872798d\n",
+       "hdl:21.14100/52699832-d86c-491b-a0a4-2f27d9ee4d69\n",
+       "hdl:21.14100/358c4a18-33b2-4c44-bd30-f6125a4df63c\n",
+       "hdl:21.14100/77254eaf-90ca-44e7-9a3c-763a840e188f\n",
+       "hdl:21.14100/62aed49c-6ca5-4027-80fe-4ddd99af575a\n",
+       "hdl:21.14100/83ffe172-769b-42b1-b979-b92d768f60fd\n",
+       "hdl:21.14100/91a8c4e2-d33b-4b87-a978-0247d8112ef3\n",
+       "hdl:21.14100/e8fb384f-d5a7-41e1-bf12-b8de3e2ffb80</dd><dt><span>version_id :</span></dt><dd>v20190815</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;tas&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCC</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>NorESM2-LM</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>Amon</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>tas</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historical/r1i1p1f1/Amon/tas/gn/v20190815/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190815</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCC.NorESM2-LM.historical.Amon.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 110MB\n",
+       "Dimensions:         (lat: 96, bnds: 2, lon: 144, member_id: 1,\n",
+       "                     dcpp_init_year: 1, time: 1980)\n",
+       "Coordinates:\n",
+       "    height          float64 8B ...\n",
+       "  * lat             (lat) float64 768B -90.0 -88.11 -86.21 ... 86.21 88.11 90.0\n",
+       "    lat_bnds        (lat, bnds) float64 2kB dask.array<chunksize=(96, 2), meta=np.ndarray>\n",
+       "  * lon             (lon) float64 1kB 0.0 2.5 5.0 7.5 ... 352.5 355.0 357.5\n",
+       "    lon_bnds        (lon, bnds) float64 2kB dask.array<chunksize=(144, 2), meta=np.ndarray>\n",
+       "  * time            (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:...\n",
+       "    time_bnds       (time, bnds) object 32kB dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 109MB dask.array<chunksize=(1, 1, 990, 96, 144), meta=np.ndarray>\n",
+       "Attributes: (12/65)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    Hybrid-restart from year 1600-01-01 of ...\n",
+       "    branch_time:                      0.0\n",
+       "    branch_time_in_child:             0.0\n",
+       "    branch_time_in_parent:            430335.0\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     tas\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/hi...\n",
+       "    intake_esm_attrs:version:         20190815\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCC.NorESM2-LM.historical.Amon.gn"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dset = dset_dict[list(dset_dict.keys())[0]]\n",
+    "dset"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot the first timestep"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<cartopy.mpl.feature_artist.FeatureArtist at 0x7fb9527cac50>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "projection = ccrs.Mercator(central_longitude=-10)\n",
+    "\n",
+    "f, ax = plt.subplots(subplot_kw=dict(projection=projection))\n",
+    "\n",
+    "dset['tas'].isel(time=0).plot(transform=ccrs.PlateCarree(), cbar_kwargs=dict(shrink=0.7), cmap='coolwarm')\n",
+    "ax.coastlines()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Compute weighted mean\n",
+    "\n",
+    "1. Creating weights: for a rectangular grid the cosine of the latitude is proportional to the grid cell area.\n",
+    "2. Compute weighted mean values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def computeWeightedMean(ds):\n",
+    "    # Compute weights based on the xarray you pass\n",
+    "    weights = np.cos(np.deg2rad(ds.lat))\n",
+    "    weights.name = \"weights\"\n",
+    "    # Compute weighted mean\n",
+    "    air_weighted = ds.weighted(weights)\n",
+    "    weighted_mean = air_weighted.mean((\"lon\", \"lat\"))\n",
+    "    return weighted_mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Compute weighted average over the entire globe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weighted_mean = computeWeightedMean(dset)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Comparison with unweighted mean\n",
+    "- We select a time range\n",
+    "- Note how the weighted mean temperature is higher than the unweighted."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fb9516e4110>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weighted_mean['tas'].sel(time=slice('2000-01-01', '2010-01-01')).plot(label=\"weighted\")\n",
+    "dset['tas'].sel(time=slice('2000-01-01', '2010-01-01')).mean((\"lon\", \"lat\")).plot(label=\"unweighted\")\n",
+    "\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Compute Weigted arctic average\n",
+    "Let's try to also take only the data above 60$^\\circ$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weighted_mean = computeWeightedMean(dset.where(dset['lat']>60.))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fb9505cf450>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weighted_mean['tas'].sel(time=slice('2000-01-01', '2010-01-01')).plot(label=\"weighted\")\n",
+    "dset['tas'].where(dset['lat']>60.).sel(time=slice('2000-01-01', '2010-01-01')).mean((\"lon\", \"lat\")).plot(label=\"unweighted\")\n",
+    "\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "formats": "ipynb,md"
+  },
+  "kernelspec": {
+   "display_name": "Python [conda env:pangeo-notebook]",
+   "language": "python",
+   "name": "conda-env-pangeo-notebook-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/_sources/learning/notebooks/projections.ipynb b/_sources/learning/notebooks/projections.ipynb
new file mode 100644
index 0000000..5544baf
--- /dev/null
+++ b/_sources/learning/notebooks/projections.ipynb
@@ -0,0 +1,2256 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "boxed-driving",
+   "metadata": {},
+   "source": [
+    "# Using cartopy and projections for plotting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "smooth-gates",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import s3fs\n",
+    "import xarray as xr\n",
+    "import cartopy.crs as ccrs\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "weekly-immunology",
+   "metadata": {},
+   "source": [
+    "## Open ERA5 dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "e9442b99-7e6b-4d3b-b6fe-479e1cee6563",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Importing the required packages\n",
+    "import intake\n",
+    "import xarray as xr\n",
+    "import intake_esm\n",
+    "import numpy as np\n",
+    "from dask.distributed import Client, LocalCluster\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0fc2dc8d-1bed-4a3a-a771-72a03c73b845",
+   "metadata": {},
+   "source": [
+    "## Reading and browsing the catalog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "9f79cb30-d905-443a-8fdd-75e0f8c8c959",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<p><strong>cmip6 catalog with 155 dataset(s) from 536945 asset(s)</strong>:</p> <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unique</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>variable_id</th>\n",
+       "      <td>583</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>table_id</th>\n",
+       "      <td>24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_id</th>\n",
+       "      <td>75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>experiment_id</th>\n",
+       "      <td>94</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>member_id</th>\n",
+       "      <td>190</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>grid_label</th>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>time_range</th>\n",
+       "      <td>9100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>activity_id</th>\n",
+       "      <td>18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>institution_id</th>\n",
+       "      <td>35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>version</th>\n",
+       "      <td>577</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>path</th>\n",
+       "      <td>536945</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>derived_variable_id</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Open the catalog\n",
+    "\n",
+    "# col = intake.open_esm_datastore('https://storage.googleapis.com/cmip6/pangeo-cmip6.json') # Remote Pangeo\n",
+    "\n",
+    "col = intake.open_esm_datastore('/mnt/craas1-ns9989k-geo4992/data/cmip6.json') # Local data stored on NIRD\n",
+    "col"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d1f77183-ed0b-49da-9bcd-9a245b020342",
+   "metadata": {},
+   "source": [
+    "### Browsing the catalog: Compering the change in AOD over the historical period across CMIP6 models"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1ea4d425-dba0-459f-b885-0861551af466",
+   "metadata": {},
+   "source": [
+    "The keywords when browsing is columns of the table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "0c52ae70-9e05-4f4e-9267-ef4239229833",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "col = col.search(\n",
+    "    experiment_id=['historical'],\n",
+    "    source_id=['CESM2'], \n",
+    "    table_id=['Amon'],\n",
+    "    variable_id=['tas',], \n",
+    "    member_id=['r1i1p1f1']\n",
+    "    \n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "afbd8adf-5e5d-4f0f-b5b6-86c82828b72e",
+   "metadata": {},
+   "source": [
+    "Models available for this request:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "181d88df-76a0-4073-8e55-c82b6604bc64",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['CESM2']"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "col.unique()['source_id']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "53e78659-4d10-4bfe-8c70-d3fcd8b55eb9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
+      "\t'activity_id.institution_id'\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
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+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='1' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [1/1 00:00&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/conda/envs/pangeo-notebook/lib/python3.11/site-packages/xarray/conventions.py:286: SerializationWarning: variable 'tas' has multiple fill values {1e+20, 1e+20} defined, decoding all values to NaN.\n",
+      "  var = coder.decode(var, name=name)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# dataset_dict = col.to_dataset_dict()\n",
+    "dataset_dict = col.to_dataset_dict(xarray_open_kwargs={'use_cftime':True, 'chunks':{'time':48}}, \n",
+    "                           aggregate=True,\n",
+    "                               #preprocess=calculate_global_avg_and_resample,\n",
+    "                                   #skip_on_error=True,\n",
+    "                            xarray_combine_by_coords={'combine_attrs': 'override'}\n",
+    "                            \n",
+    "                          )\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "6a06e150-5b68-40c7-b16b-1344dde45c26",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dset = dataset_dict['CMIP.NCAR']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "strong-ethiopia",
+   "metadata": {},
+   "source": [
+    "## Get metadata "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "occupational-indianapolis",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       ".xr-wrap {\n",
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+       "  min-width: 300px;\n",
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+       "\n",
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+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 438MB\n",
+       "Dimensions:    (member_id: 1, time: 1980, lat: 192, lon: 288, nbnd: 2)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
+       "  * time       (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00\n",
+       "  * member_id  (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    tas        (member_id, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 48, 192, 288), meta=np.ndarray&gt;\n",
+       "    time_bnds  (time, nbnd) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;\n",
+       "    lat_bnds   (lat, nbnd) float32 2kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;\n",
+       "    lon_bnds   (lon, nbnd) float32 2kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "Attributes: (12/59)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    case_id:                          15\n",
+       "    cesm_casename:                    b.e21.BHIST.f09_g17.CMIP6-historical.001\n",
+       "    contact:                          cesm_cmip6@ucar.edu\n",
+       "    creation_date:                    2019-01-16T23:34:05Z\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:activity_id:     CMIP\n",
+       "    intake_esm_attrs:institution_id:  NCAR\n",
+       "    intake_esm_attrs:version:         v20190308\n",
+       "    intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...\n",
+       "    intake_esm_attrs:_data_format_:   netcdf\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b4f3183e-9e36-4d6a-b5c7-f4ca1ed1cb1f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b4f3183e-9e36-4d6a-b5c7-f4ca1ed1cb1f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-319f3381-98b9-4c44-8fc1-d7325a90532c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-319f3381-98b9-4c44-8fc1-d7325a90532c' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-a9f36114-1eaa-46fe-82fb-42802a8a35c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9f36114-1eaa-46fe-82fb-42802a8a35c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d55b032-64ab-426c-86e1-ea2cb89ee637' class='xr-var-data-in' type='checkbox'><label for='data-9d55b032-64ab-426c-86e1-ea2cb89ee637' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-4d38248d-a2f7-43a3-aff6-31d52888754a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d38248d-a2f7-43a3-aff6-31d52888754a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fba6e39-b3b5-43b2-83fc-f11e20d54a01' class='xr-var-data-in' type='checkbox'><label for='data-4fba6e39-b3b5-43b2-83fc-f11e20d54a01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-5fb64c82-c94f-4d58-8161-a251c161f19b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fb64c82-c94f-4d58-8161-a251c161f19b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbc1ffd6-83b8-4546-805b-029a90a5f987' class='xr-var-data-in' type='checkbox'><label for='data-dbc1ffd6-83b8-4546-805b-029a90a5f987' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-27866ed2-3741-4d60-ba0f-f59b2df0ef03' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-27866ed2-3741-4d60-ba0f-f59b2df0ef03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52bd08b8-b29a-4f5b-9486-a60bc35004e2' class='xr-var-data-in' type='checkbox'><label for='data-52bd08b8-b29a-4f5b-9486-a60bc35004e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d9e1f21-6434-47b8-9d50-18ff76b4d9a7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7d9e1f21-6434-47b8-9d50-18ff76b4d9a7' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 48, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-30d32fca-e22d-4064-8d58-f82f149646dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30d32fca-e22d-4064-8d58-f82f149646dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13e5f9a4-5de3-4f2f-9476-ab2c1a7f67ec' class='xr-var-data-in' type='checkbox'><label for='data-13e5f9a4-5de3-4f2f-9476-ab2c1a7f67ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 417.66 MiB </td>\n",
+       "                        <td> 10.12 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1980, 192, 288) </td>\n",
+       "                        <td> (1, 48, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 42 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"351\" height=\"159\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
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+       "\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"95\" y1=\"0\" x2=\"165\" y2=\"70\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"165\" y1=\"70\" x2=\"206\" y2=\"70\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"165\" y1=\"109\" x2=\"206\" y2=\"109\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"165\" y1=\"70\" x2=\"165\" y2=\"109\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"206\" y1=\"70\" x2=\"206\" y2=\"109\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"165.58823529411765,70.58823529411765 206.14509559394764,70.58823529411765 206.14509559394764,109.01386754281697 165.58823529411765,109.01386754281697\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"185.866665\" y=\"129.013868\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >288</text>\n",
+       "  <text x=\"226.145096\" y=\"89.801051\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,226.145096,89.801051)\">192</text>\n",
+       "  <text x=\"120.294118\" y=\"93.719750\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,120.294118,93.719750)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;</div><input id='attrs-ba86a7b2-970e-4a7d-ab32-05f1d36a1f4f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba86a7b2-970e-4a7d-ab32-05f1d36a1f4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5f16676-a339-441c-a86d-30cb4bf24a31' class='xr-var-data-in' type='checkbox'><label for='data-f5f16676-a339-441c-a86d-30cb4bf24a31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                        <td> 768 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                        <td> (48, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 42 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"25\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"25\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"25\" y2=\"17\" />\n",
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+       "  <line x1=\"0\" y1=\"32\" x2=\"25\" y2=\"32\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"25\" y2=\"37\" />\n",
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+       "  <line x1=\"0\" y1=\"64\" x2=\"25\" y2=\"64\" />\n",
+       "  <line x1=\"0\" y1=\"69\" x2=\"25\" y2=\"69\" />\n",
+       "  <line x1=\"0\" y1=\"75\" x2=\"25\" y2=\"75\" />\n",
+       "  <line x1=\"0\" y1=\"81\" x2=\"25\" y2=\"81\" />\n",
+       "  <line x1=\"0\" y1=\"87\" x2=\"25\" y2=\"87\" />\n",
+       "  <line x1=\"0\" y1=\"96\" x2=\"25\" y2=\"96\" />\n",
+       "  <line x1=\"0\" y1=\"101\" x2=\"25\" y2=\"101\" />\n",
+       "  <line x1=\"0\" y1=\"107\" x2=\"25\" y2=\"107\" />\n",
+       "  <line x1=\"0\" y1=\"113\" x2=\"25\" y2=\"113\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, nbnd)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;</div><input id='attrs-730e4497-953a-40f8-a67a-884b3d0db34d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-730e4497-953a-40f8-a67a-884b3d0db34d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3cd890b-b560-40a4-b4bc-1f7c5a29b8fe' class='xr-var-data-in' type='checkbox'><label for='data-e3cd890b-b560-40a4-b4bc-1f7c5a29b8fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 kiB </td>\n",
+       "                        <td> 1.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (192, 2) </td>\n",
+       "                        <td> (192, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.60913412115106,0.0 25.60913412115106,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.804567\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.609134\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.609134,60.000000)\">192</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-0ec9ce2d-633b-4edd-adb5-19341a1c61dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ec9ce2d-633b-4edd-adb5-19341a1c61dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c566b42-2f59-4a97-80ed-107bd6771b23' class='xr-var-data-in' type='checkbox'><label for='data-3c566b42-2f59-4a97-80ed-107bd6771b23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.25 kiB </td>\n",
+       "                        <td> 2.25 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-b3629ddc-9b98-4283-9aaf-fc1effe83f93' class='xr-section-summary-in' type='checkbox'  ><label for='section-b3629ddc-9b98-4283-9aaf-fc1effe83f93' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b57a7f8c-5f3c-4488-8990-93aaa4b4afc9' class='xr-index-data-in' type='checkbox'/><label for='index-b57a7f8c-5f3c-4488-8990-93aaa4b4afc9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1be18e37-2795-4d2b-9aaf-67195dbe3424' class='xr-index-data-in' type='checkbox'/><label for='index-1be18e37-2795-4d2b-9aaf-67195dbe3424' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-43f0be5c-4e31-429f-9aa3-393d47783219' class='xr-index-data-in' type='checkbox'/><label for='index-43f0be5c-4e31-429f-9aa3-393d47783219' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,\n",
+       "             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,\n",
+       "             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,\n",
+       "             1850-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,\n",
+       "             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,\n",
+       "             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,\n",
+       "             2014-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d73a17c2-6162-4e41-92f3-3424b146cb08' class='xr-index-data-in' type='checkbox'/><label for='index-d73a17c2-6162-4e41-92f3-3424b146cb08' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-582ae9e0-8afd-4819-9d44-f78267c08713' class='xr-section-summary-in' type='checkbox'  ><label for='section-582ae9e0-8afd-4819-9d44-f78267c08713' class='xr-section-summary' >Attributes: <span>(59)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T23:34:05Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/d9a7225a-49c3-4470-b7ab-a8180926f839</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;tas&#x27;]</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>tas</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>Amon</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:time_range :</span></dt><dd>185001-201412</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>v20190308</dd><dt><span>intake_esm_attrs:path :</span></dt><dd>/mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/Amon/tas/gn/v20190308/tas_Amon_CESM2_historical_r1i1p1f1_gn_185001-201412.nc</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>netcdf</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 438MB\n",
+       "Dimensions:    (member_id: 1, time: 1980, lat: 192, lon: 288, nbnd: 2)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
+       "  * time       (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00\n",
+       "  * member_id  (member_id) object 8B 'r1i1p1f1'\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    tas        (member_id, time, lat, lon) float32 438MB dask.array<chunksize=(1, 48, 192, 288), meta=np.ndarray>\n",
+       "    time_bnds  (time, nbnd) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n",
+       "    lat_bnds   (lat, nbnd) float32 2kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "    lon_bnds   (lon, nbnd) float32 2kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "Attributes: (12/59)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    case_id:                          15\n",
+       "    cesm_casename:                    b.e21.BHIST.f09_g17.CMIP6-historical.001\n",
+       "    contact:                          cesm_cmip6@ucar.edu\n",
+       "    creation_date:                    2019-01-16T23:34:05Z\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:activity_id:     CMIP\n",
+       "    intake_esm_attrs:institution_id:  NCAR\n",
+       "    intake_esm_attrs:version:         v20190308\n",
+       "    intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...\n",
+       "    intake_esm_attrs:_data_format_:   netcdf\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dset"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "great-investor",
+   "metadata": {},
+   "source": [
+    "### Get variable metadata (air_temperature_at_2_metres)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "constant-cotton",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (member_id: 1, time: 1980, lat: 192, lon: 288)&gt; Size: 438MB\n",
+       "dask.array&lt;broadcast_to, shape=(1, 1980, 192, 288), dtype=float32, chunksize=(1, 48, 192, 288), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
+       "  * time       (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00\n",
+       "  * member_id  (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "Attributes: (12/19)\n",
+       "    cell_measures:  area: areacella\n",
+       "    cell_methods:   area: time: mean\n",
+       "    comment:        near-surface (usually, 2 meter) air temperature\n",
+       "    description:    near-surface (usually, 2 meter) air temperature\n",
+       "    frequency:      mon\n",
+       "    id:             tas\n",
+       "    ...             ...\n",
+       "    time_label:     time-mean\n",
+       "    time_title:     Temporal mean\n",
+       "    title:          Near-Surface Air Temperature\n",
+       "    type:           real\n",
+       "    units:          K\n",
+       "    variable_id:    tas</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6a6f527b-e2f7-4aa1-bc0e-28c1195649fe' class='xr-array-in' type='checkbox' checked><label for='section-6a6f527b-e2f7-4aa1-bc0e-28c1195649fe' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 48, 192, 288), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 417.66 MiB </td>\n",
+       "                        <td> 10.12 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1980, 192, 288) </td>\n",
+       "                        <td> (1, 48, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 42 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"351\" height=\"159\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-26ff334d-b432-4041-948d-47865fcc9468' class='xr-section-summary-in' type='checkbox'  checked><label for='section-26ff334d-b432-4041-948d-47865fcc9468' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-3abdb9c8-42f6-41ec-8ff7-e26831ff02a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3abdb9c8-42f6-41ec-8ff7-e26831ff02a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1ebd11f-2331-48cb-a009-b9fe66e19d8c' class='xr-var-data-in' type='checkbox'><label for='data-e1ebd11f-2331-48cb-a009-b9fe66e19d8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
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+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-e515765a-4903-4b8e-b055-ad36f2cd1a67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e515765a-4903-4b8e-b055-ad36f2cd1a67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f25e12a-0f08-4d70-854e-0b06c93dc925' class='xr-var-data-in' type='checkbox'><label for='data-0f25e12a-0f08-4d70-854e-0b06c93dc925' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-c3293032-1842-45ad-9109-fb57b0b5663c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3293032-1842-45ad-9109-fb57b0b5663c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d37d595-189f-4766-b993-057c45db5e5f' class='xr-var-data-in' type='checkbox'><label for='data-8d37d595-189f-4766-b993-057c45db5e5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-e6810e1d-4ed8-45a2-961c-9166c250a7a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6810e1d-4ed8-45a2-961c-9166c250a7a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a495505-37ae-4946-982e-8e61dd5b2174' class='xr-var-data-in' type='checkbox'><label for='data-2a495505-37ae-4946-982e-8e61dd5b2174' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-315e02a3-33eb-4601-9b35-f269b6bd18f4' class='xr-section-summary-in' type='checkbox'  ><label for='section-315e02a3-33eb-4601-9b35-f269b6bd18f4' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bdd24540-a3b1-4fd3-86fc-6482317d84bd' class='xr-index-data-in' type='checkbox'/><label for='index-bdd24540-a3b1-4fd3-86fc-6482317d84bd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cf5f40a1-71b1-4ea9-9aa4-7612a6097553' class='xr-index-data-in' type='checkbox'/><label for='index-cf5f40a1-71b1-4ea9-9aa4-7612a6097553' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f65e320d-6d46-4ae8-815a-89d9873aafba' class='xr-index-data-in' type='checkbox'/><label for='index-f65e320d-6d46-4ae8-815a-89d9873aafba' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,\n",
+       "             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,\n",
+       "             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,\n",
+       "             1850-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,\n",
+       "             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,\n",
+       "             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,\n",
+       "             2014-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6e693a08-e4f7-456e-a618-c831e9fabfa9' class='xr-index-data-in' type='checkbox'/><label for='index-6e693a08-e4f7-456e-a618-c831e9fabfa9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b919d258-73e6-44be-927b-699daa3f456f' class='xr-section-summary-in' type='checkbox'  ><label for='section-b919d258-73e6-44be-927b-699daa3f456f' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'tas' (member_id: 1, time: 1980, lat: 192, lon: 288)> Size: 438MB\n",
+       "dask.array<broadcast_to, shape=(1, 1980, 192, 288), dtype=float32, chunksize=(1, 48, 192, 288), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n",
+       "  * time       (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00\n",
+       "  * member_id  (member_id) object 8B 'r1i1p1f1'\n",
+       "Attributes: (12/19)\n",
+       "    cell_measures:  area: areacella\n",
+       "    cell_methods:   area: time: mean\n",
+       "    comment:        near-surface (usually, 2 meter) air temperature\n",
+       "    description:    near-surface (usually, 2 meter) air temperature\n",
+       "    frequency:      mon\n",
+       "    id:             tas\n",
+       "    ...             ...\n",
+       "    time_label:     time-mean\n",
+       "    time_title:     Temporal mean\n",
+       "    title:          Near-Surface Air Temperature\n",
+       "    type:           real\n",
+       "    units:          K\n",
+       "    variable_id:    tas"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dset['tas']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "rural-reward",
+   "metadata": {},
+   "source": [
+    "## Select time\n",
+    "- Check time format when selecting a specific time "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "heated-sacramento",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "tas_plt = dset['tas'].sel(time=slice('2013-01-01','2014-01-01')).mean('time')-273.15\n",
+    "tas_plt.attrs['units'] ='deg C'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "c6c8e90a-616b-45cf-92d0-c71b53c5504e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tas_plt = tas_plt.squeeze()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "stone-driving",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Visualize data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "23763ffd-977d-43fe-8f56-2752e16adc86",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "experienced-identification",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Simple visualization from xarray plotting method"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "thick-clock",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 323 ms, sys: 27.9 ms, total: 351 ms\n",
+      "Wall time: 352 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f792165c790>"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time \n",
+    "tas_plt.load()\n",
+    "tas_plt.plot()#cmap = 'coolwarm')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "hundred-yield",
+   "metadata": {},
+   "source": [
+    "#### Same plot but with local file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "handed-dialogue",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 22.7 ms, sys: 1.84 ms, total: 24.6 ms\n",
+      "Wall time: 23.8 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f7943263690>"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time \n",
+    "tas_plt.plot(cmap = 'coolwarm')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "korean-means",
+   "metadata": {},
+   "source": [
+    "### Customize plot"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "regional-arcade",
+   "metadata": {},
+   "source": [
+    "#### Set the size of the figure and add coastlines "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "unauthorized-eligibility",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 402 ms, sys: 1.89 ms, total: 404 ms\n",
+      "Wall time: 405 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<cartopy.mpl.geocollection.GeoQuadMesh at 0x7f7940407390>"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 3000x1300 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "fig = plt.figure(1, figsize=[30,13])\n",
+    "\n",
+    "# Set the projection to use for plotting\n",
+    "ax = plt.subplot(1, 1, 1, projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "\n",
+    "# Pass ax as an argument when plotting. Here we assume data is in the same coordinate reference system than the projection chosen for plotting\n",
+    "# isel allows to select by indices instead of the time values\n",
+    "tas_plt.plot.pcolormesh(ax=ax, cmap='coolwarm')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "wrong-affiliate",
+   "metadata": {},
+   "source": [
+    "#### Change plotting projection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "precious-keyboard",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 57.7 ms, sys: 4.09 ms, total: 61.8 ms\n",
+      "Wall time: 61.2 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'CESM air temperature at 2 avg over 2013')"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "\n",
+    "fig = plt.figure(1, figsize=[10,10])\n",
+    "\n",
+    "# We're using cartopy and are plotting in Orthographic projection \n",
+    "# (see documentation on cartopy)\n",
+    "ax = plt.subplot(1, 1, 1, projection=ccrs.Orthographic(0, 90))\n",
+    "ax.coastlines()\n",
+    "\n",
+    "# We need to project our data to the new Orthographic projection and for this we use `transform`.\n",
+    "# we set the original data projection in transform (here PlateCarree)\n",
+    "tas_plt.plot(ax=ax, transform=ccrs.PlateCarree(), cmap='coolwarm')\n",
+    "\n",
+    "# One way to customize your title\n",
+    "plt.title(\"CESM air temperature at 2 avg over 2013\", fontsize=18)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "annoying-cleaning",
+   "metadata": {},
+   "source": [
+    "#### Choose extent of values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "imposed-symposium",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 53.2 ms, sys: 2.45 ms, total: 55.7 ms\n",
+      "Wall time: 54.9 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'CESM air temperature at 2 avg over 2013')"
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "fig = plt.figure(1, figsize=[10,10])\n",
+    "\n",
+    "ax = plt.subplot(1, 1, 1, projection=ccrs.Orthographic(0, 90))\n",
+    "ax.coastlines()\n",
+    "\n",
+    "# Fix extent\n",
+    "minval = -10\n",
+    "maxval = 20\n",
+    "\n",
+    "# pass extent with vmin and vmax parameters\n",
+    "tas_plt.plot(ax=ax, vmin=minval, vmax=maxval, transform=ccrs.PlateCarree(), cmap='coolwarm')\n",
+    "\n",
+    "# One way to customize your title\n",
+    "#plt.title(\"ERA5 air temperature at 2 metres\\n 30th June 2020 at 21:00 UTC\", fontsize=18)\n",
+    "plt.title(\"CESM air temperature at 2 avg over 2013\", fontsize=18)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "opening-poultry",
+   "metadata": {},
+   "source": [
+    "### Combine plots with different projections "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "becoming-tampa",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 98.4 ms, sys: 1.93 ms, total: 100 ms\n",
+      "Wall time: 99.6 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'K')"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2000x1000 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "fig = plt.figure(1, figsize=[20,10])\n",
+    "\n",
+    "# Fix extent\n",
+    "minval = -10\n",
+    "maxval = 20\n",
+    "\n",
+    "# Plot 1 for Northern Hemisphere subplot argument (nrows, ncols, nplot)\n",
+    "# here 1 row, 2 columns and 1st plot\n",
+    "ax1 = plt.subplot(1, 2, 1, projection=ccrs.Orthographic(0, 90))\n",
+    "\n",
+    "# Plot 2 for Southern Hemisphere\n",
+    "# 2nd plot \n",
+    "ax2 = plt.subplot(1, 2, 2, projection=ccrs.Orthographic(180, -90))\n",
+    "\n",
+    "tsel = 0\n",
+    "for ax,t in zip([ax1, ax2], [\"Northern\", \"Southern\"]):\n",
+    "    map = tas_plt.plot(ax=ax, vmin=minval, vmax=maxval, \n",
+    "                                           transform=ccrs.PlateCarree(), \n",
+    "                                           cmap='coolwarm', \n",
+    "                                           add_colorbar=False)\n",
+    "    ax.set_title(t + \" Hemisphere \\n\" , fontsize=15)\n",
+    "    ax.coastlines()\n",
+    "    ax.gridlines()\n",
+    "\n",
+    "# Title for both plots\n",
+    "fig.suptitle('CESM air temperature at 2 avg over 2013', fontsize=20)\n",
+    "\n",
+    "\n",
+    "cb_ax = fig.add_axes([0.325, 0.05, 0.4, 0.04])\n",
+    "\n",
+    "cbar = plt.colorbar(map, cax=cb_ax, extend='both', orientation='horizontal', fraction=0.046, pad=0.04)\n",
+    "cbar.ax.tick_params(labelsize=25)\n",
+    "cbar.ax.set_ylabel('K', fontsize=25)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "026a7b6f-7a83-43cd-b217-e31f90ffe7d8",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:pangeo-notebook]",
+   "language": "python",
+   "name": "conda-env-pangeo-notebook-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/_sources/learning/notebooks/some-xarray-pandas-presentation_Sara.ipynb b/_sources/learning/notebooks/some-xarray-pandas-presentation_Sara.ipynb
new file mode 100644
index 0000000..53b6f0e
--- /dev/null
+++ b/_sources/learning/notebooks/some-xarray-pandas-presentation_Sara.ipynb
@@ -0,0 +1,23018 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# Some tips with xarray and pandas\n",
+    "\n",
+    "- We have massively different levels here\n",
+    "- Try to make some aims for technical skills you can learn!\n",
+    "- If you are beginning with python --> learn the basics\n",
+    "- If you are good at basic python --> learn new packages\n",
+    "- If you know all the packages --> improve your skills with producing your own software etc. \n",
+    "- If you don't know git and github --> get better at this!\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## print('Hey world')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "<span style=\"color:red;font-weight:700;font-size:20px\">\n",
+    "Please feel free to come with suggestions and extra input as we go! \n",
+    "</span>\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "<span style=\"color:blue;font-weight:700;font-size:20px\">\n",
+    "Questions:\n",
+    "\n",
+    "- How many have used jupyter lab?     \n",
+    "- How many have used pandas? \n",
+    "- How many have used xarray? \n",
+    "</span>\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## What are pandas and xarray?\n",
+    "- Pandas --> like a spreadsheet 2D data with columns and rows\n",
+    "- xarray --> like pandas, but in N dimensions\n",
+    "- **Use the functionality these packages gives you! Will help you avoid mistakes. Try to get as good as possible :)**\n"
+   ]
+  },
+  {
+   "attachments": {
+    "1f171b31-582b-4003-be00-7d731d031ab9.png": {
+     "image/png": 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"
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4CZq0Ll4dz1uYJBAEBAFBQBAQBAQBQcDEEYjJSv7jyKavdv0ZkXRMidrRzffXq+f08w+tv+QNI1jrT+6d9fNzaLAoACr39Lgb/m/AFDvrs45c5eXlZZU/LI9qn7/1l0ZSCgKCgCAgCAgCgoAgYAoIWFlbLY7a9OL6b2KzU5DHydbhq5lPTO82qp6yNYBgoTEb9/m9OcX5ZD08sOdPs17AGqgVA60qKSkpKirKz88vLCwsLi4WaqWBIzuCgCAgCAgCgoAgYI4IFJSXPLn5q/VxEQhvb2P75w1vDA/qVZ+K1JdgpRdkj/nsnuMZ8WQ6q/eEjy99xMHGThUAkYJO5eXlZWdnQ63USWtra6szv/rIIWkEAUFAEBAEBAFBQBAwHQSwxSlzXGlZ2Vt7fvvp6Dpk83Z2X3/z+529/OE4dYtaX4J1/YK5Cw/osh7Tue/S61/VzIKlpaVQq4yMjIKCAq7Cq2wrf/b29vxvY4O/uzi8190EclUQEAQEAUFAEBAETAuB09QKllNaihappLTk4fWfrY7djZRD/Lstv+41JyenujlWvQjW9rhDYz+/l0yD3Nttun2+l5Mb+5RNqWit0tPT2YFIQaooz9XVlb9QK9OCSqQRBAQBQUAQEAQEAUGggQjAdvCAwv0pOTPtqiVzIzNiyeCjCffO7DfBxcWlDi3S+dVLZP3Uqs+UPC9deJtiVxxCqlBcpaSksGNnZ+fm5tauXbv27dtDsIRdNbD5JLkgIAgIAoKAICAImCICqKnQH3l4eHQJ7Dxv4m1KxFe3/5yQlJiTk1OHu/n5CVZE0vENp/aR48AO4Zf3GKOyhlRlZWWhu+LQwcHB09MTduXs7Kyuyl9BQBAQBAQBQUAQEAQsCQGUR5N7jrioyyAqdSoneUNMRGpqKl5S6KFqrOb5CRax2tWd9wybqcyN8DVyVOwKWudV+atDS1ZjwXJSEBAEBAFBQBAQBAQB80Lg/pGzlMDrE/ZjOkxLS9OW91WpSD0I1hEdwcKrfUrYUHUzsRhgV8RlwI0dpRm/uv28qhQph4KAICAICAKCgCAgCJgjAiM79XZzdEXyf+IiCP4OI8JdqkZD4XkIVm5xwb5EXRjTUeTo4MIOvCo3Nxe+hsoKdyvYlTkCJDILAoKAICAICAKCgCDQUAR0+qbQIdyVkp+RVpYLtcL/HV5UPZ/zEKyEnDR1T7hvJ7XDYkVWDrKP6xXsSiyD1TGVM4KAICAICAKCgCBgqQiE+QSpqhVYl8GC8EqHF1VXYtWXYPm39SY71FfEu4Jj4eqFS7ujo6Olwif1EgQEAUFAEBAEBAFBoDoCihFxPr0kl0gNOLljKFTRQPUTn4dg8WVplVp9RBqChSqMM3hftW3bVj8j2RcEBAFBQBAQBAQBQcDiEWjv6qXqmFaQja8U+xo70q/7eQhWWUWZSm1XGTiULPC+wqWdwFeivtLHUfYFAUFAEBAEBAFBoDUgYGt9OpR6eZsK3KVQOWEfhB1ViddwHoJVBSkIFosSsTiSo6wcrAKOHAoCgoAgIAgIAoJAq0IAjyn0TVArPLH46de9wQSLm5UGSz8X2RcEBAFBQBAQBAQBQaC1IaAxIjgWSij96jeSYMnHcPRBlH1BQBAQBAQBQUAQaIUIQLAUI2oqwVKrEMlOojO0wsdIqiwICAKCgCAgCAgC+ghojKipBIv7Vb7kqF+A7AsCgoAgIAgIAoKAINAKEaiNETXMRNgKgZMqCwKCgCAgCAgCgoAg0FAEbBt6g6QXBAQBQaDVIhCfkf/r9hiqPzbct1+n07FwWi0aUnFBQBCoAwEhWHWAI5cEAUHAEhCIScvbFJUSl1mYnFvkZGfj5+rQydt5aFcfb1eHhlYvp7BkZWQqd4W3l0jLDQVP0gsCrQsBIVitq72ltoJAq0IgM6/43dWRW2Oyqtf6gw0nX7g4fHCIT/VLckYQEAQEgaYjIASr6RhKDoKAIGCKCCRkFjzxe0RyXgnCOdhY92rn0tXXNa+49GRawf7kXBc7m94BnqYot8gkCAgCFoGAECyLaEaphCAgCJyLQFl5xburIhW76uff9uFJ4V56BsGU7EK8qRztT3/v4txb5UgQEAQEAQMgIATLACBKFoKAIGBqCGw8krwvKRepwn2cX7isl53NOSumfd0c2arIXFRStjc6IyY9Pz6zwK+tQ5C3S59ATxfH83eSm6NS0vOKra3aTOnbUT/PrPziDZEpnAlr3za0vZu6FBGTEZ2WH+zr0qOjR2pOYURMZmRSjquDbRc/114BHq6OdiTj/MHYrCOJOcTD6ejpNDrcT53XMl+xN66sos3IUF8PF/uTKbmHE7KPoZNzsA3ych4Z5utgV5U4Rqfm7TiRlpJbRKSdrn6ulBXgjQrvHEy0zGVHEBAEDILA+fsOgxQjmQgCgoAg0JwIrK1kNpR43dCg+jCJqMTst1ZFncoq1Beyvav9wxeE9gjw0D9ZfX/F/sTtcdn2NlZVCFZGXvGHG06S/rZhQRrB2nY8fWFE4shOHjZWVs8sO5RbfPbbGl28nF6a0Ts2LY/zBaXlWkE/7Ih78dIenXxctTOfbY4mgbuTXVpu0Sebo7Xz7Py4I3bO9B7+ns7qZHlFxSdrji49lHw2zUHdvp211WuX9Qzv4H72vOwJAoKAQREQgmVQOCUzQUAQMAEECkvKlGO7h6PtgM7e55UIc+EDCyPKK9qghRoT7BXo6ZSYXbj2WHpibvHDiw68O7N3qP9p/dN5s6pngm0xWdtjs9wdbC8M9SkuK2dlYml5xbH0gkcW7E3MKW7rYHNRuM77fsXh1KKy8rSCkq82nHj+st5VMn9v3XH4GbRsQIB7TmHp30fTSsor4nKKPl1//NlLe6lg0OsOJSl21be969BgL2srq4i4rF1x2V5Odl3PKNWqZCuHgoAgYBAEhGAZBEbJRBAQBEwIARYPqo9OBHk4nverE6SEvsCu+L08rUefoNOe75cm5zz82/7C0vJP/z3+6pV9oSYGrCFMqJO747yZvd2d7cn2mmGdbvh6BzLEZBX5ONu9O6ufp4vu/HXDg2/8ekdeSdm22OyC4jKnc53GYFeTw33umhBqW2nsu3lMyS3f7Mwp1pHLvMISZVU8GJ+txH5sSnfsiexPHxCAgxrmSxvopPwEAUHAaAiczwavaalPfyNHJ4j2wRyjSSUZCwKCgCDQeASyCorVzR2qOVpVzxSH942nMjkP49HYFYchfm2n92zHzoHkPAyI1W9s4pkZ/fwVuyIfHPB7tzttARwa5KHYFefxABsSeNqKl5Z7jvlSlX7N0E6KXXEIoxoWdNqamXzG1hni66JS/n0wEV6l9qFW+i7/6qT8FQQEAcMicD6CpV3Xm+rU9tkdw0omuQkCgoAg0DgEHM94eZeUa3PEWnNKyipQ1/oHVLUD9gk4TW4SM2sgN7XmWL8LXfzOCVXa44wVsmeHc8TQIpqiwaqSsb+rfRVX/e5n7iUahUo8tMvpQF9fbI2587udq/cnFOt5d1XJUA4FAUHAgAhoBMqAeUpWgoAgIAi0JAI+bU+vEEzILjqvHElnlD3dz1Ac7RZlU+OQdYXayfrv1K3sd3PSLRjUfrZnDHbBfmed2bmqnddSaju+rjqTn/7PzkZvKlx5AU3VB1f16e+vI3Ox2UVvrT3+n292LN8Tx5JJ/RtlXxAQBAyOgBAsg0MqGQoCgkALI+DsYIv/OEJEZxZqdrHaZCK6gbpkZ1u1P9Turc86xOr5V9c56aexr1acumpf7+gJfPZHP8Pa9rF1vnh5n+cmh3X20PHO1PwSoti/tOygqLJqQ0zOCwIGQaBqh2KQTCUTQUAQEARaEAHUON0qfY9wAydIVd2ShJzRGKXmVFV3EWdB3evvXjVoVvU8WQZYUnaORTIz//Tt1RM38xkc9Id29f1g9oAXp3br2Fb3BcYdcdmbIvViNzSzQFKcINAKEBCC1QoaWaooCLQ+BK4cHKAq/e226OwC3ddyavv5uTm5OehUQf8eTdNbzKNLvumo7rvO/Dp6nQ4rpQ6r/PV01hn78CA/lpSjf2lXtM533nR+LIQkaMXcS3sqkY6l6AKxyk8QEASMhIAQLCMBK9kKAoJASyLQvaPH6M66gAsEPvjvT7v3nEonOJYSCMMf0c/XHEhUh2h3Lgr3ZT8iKXfprhhinasfCp5VUWnsExS0k+85flGnU5z5r4OHk9r9+2BSftFp7/JdJ9JWHDmP8uxMBkb8f9ux1AOxmVrdKSkp+7TDvo/et4OMKIFkLQi0VgQkDlZrbXmptyBg0QhgJfzPmJC0/MMHk/P4IuGTSw9R3UB3h+LSiuTKKFm+znYTerZXGNwwMpjIohtOZn68KXrxvsQQb+e4rMKTlSsH+Ur0jSODq7qOnwvdmHC/73bGYSL843DK6qg0Aisk5hRFpeXj83Qqs/AMYTv3nuY6Wh+ZsuZYOg70hIEI83ONySjYl6hTs1GvQcHnD8HaXGJKOYKABSIgGiwLbFSpkiAgCIAAIQzmzexz0+AAjR6hzUqqZFcQjsBKj28FFKGkHprUbUIXLz4gk5BbTFgsxa74SvT8a/rVbR8kh/YeTo9M6MK3/dgn8Pq/JzNgV0MC3F6/om8Pv9NhqFRBzf+XjyryDR/Ml3sTc3/dl7glJiu/pDzAzeH5S7qdt17NL62UKAhYEgKiwbKk1pS6CAKCwDkIwJyuHNpp+sCAxMyCuPT8tNzi9u6OHTyd/dwJlXXO9JIPJD88pft/S8uPJ+fw4WRvV/uOns5QkCoB3AM8XV6d3oMyIFX6JY3u1o4gpVGJOYlZBR7O9jjOk4B7750QSsx0itMST+rdfkiwF4csddROsjOum1+vjrqwW57nWu4Gh3i/WukBhtha+jlTu5eXV2jrH7Xz/YK8Xp2uK6vzmQ8X3jAqZPaIYGJ9xaTlYRx0d7L3bevAJwgljLsGmuwIAkZC4Jw33EhlSLaCgCAgCLQgAg62NnwpWf9jybUJQ+iEbh3c2WpLQGj13me+pVMlDWHZB4VUNboF+aDBOkeJFeDlwlblXg75PLP2hWb9q+jhqkQT5WrPWr4/7d3WgU3/dvbhUpAzfX5WJYEcCgKCgDEQOGcOZ4wCJE9BQBAQBAQBQUAQEARaGwJCsFpbi0t9BQFBQBAQBAQBQcDoCAjBMjrEUoAgIAgIAoKAICAItDYEhGC1thaX+goCgoAgIAgIAoKA0REQgmV0iKUAQUAQEAQEAUFAEGhtCAjBam0tLvUVBASBFkBACxDfAmVLkYKAINASCEiYhpZAXcoUBAQBYyJQXlGxPir1552xWQUlb8zs00EvDJUxi60175ScogcW7EOMxyeFe7nY15qu5S4kZRc9tHCfjZXVmFCfcWG+Ib4uWnTWlhNKShYEzBsBIVjm3X4ivSAgCOgjALVaF5n6446Y2IwCdT6nsKRNSxOs7MLS9LxitgcX7Js7vWeg5zlBSvXlb6n9nKKSjMoY9wt3x7Eh4dgw33GhPtpnFltKMClXEDBfBMREaL5tJ5ILAoLAWQT4hPOaIym3f7/79VWRil119XV9YVqP8HZtzyZqob0uvi53jglBJ5ScU/Twwn0HE7JbSJBaiwWr12f2vrC7n7O97oM/fLLwu63R//lu132/7P19T3xaXnGtd8oFQUAQqAUB0WDVAoycFgQEATNBAGq1Lirlh+2x8ZmntVZd/VyvGxI4uLOX6di5pvXxxzj42l+ROYWlTy468OiksBHVwr63LN49/N3Y7h7XZfvJDPDceiKjpKw8KjmX7fMNJ3oHuI8P8x3Zxdv13C/8tKzMUrogYMoICMEy5dYR2QQBQaAuBKBW/0Sm/LQ9Jj6rUKUL83O9dkjQ4M6epkOttArATl65rOfzyw7lFpW+tPzwHWNCYF3aVRPZsbexRk62/OKyzcfT1kam7I7JwvC6LzaL7cO1xwZ18sR6OLSzJ19zNBGZRQxBwDQREIJlmu0iUgkCgkBdCCiD4E87YhLOUKvwdjpqxfBvgtRKqwkqojev6PPMkgPYCuevP56SW3TT8M5WJikxtsKJ3fzYMgtKNhxNXRuZimWztLxiy4l0NtjVsGAv3OEHBHnYWptkBTTQZUcQaCEEhGC1EPBSrCAgCDQKAcb4f46knEut2s4eEjjQtKmVVlf8x9+6os+zSw8eT81bsCsuNbf4wYmhtjamy1E8nOym9vZnY6UhpkPWEJxIyyssKUO5xebmaDuqq27hYU9/N9NkihrysiMINDMCQrCaGXApThAQBBqJANRqzeHkn3bEJmafNgh2aw+1CkKJYrr0pKa66pyxLu/90p+Hd8dkwlEy8oufvri7S6V3eU3JTeVcOzeHqwYGsJ1Kz1+nY1epNAQLJJfvT2TzcbUfG+o7Nsyni6+reTWHqeArclgcAkKwLK5JpUKCgMUhALX6+3Dyz3rUqnsltepvbtRKaxkMcKxwfHfNUeq1Nzbr0YURc6b38DbJEFmazNpOJy/nG4Z1un5Yp8ikHAjiuqjUzPwSVHEqxEMAIR5CfceF+XT0MLloFFoVZEcQaAYEhGA1A8hShCAgCDQSgdKyir+PoLWKwT6lsuju3/a6IUH9As1Ma1W9/rguPXhBqK+rPTo5jG4P/roPjgV3qZ7SNM+gpiIEBtt/Rgbvi8uCaW06RjyHMmJkfL8tmi3UzxXTIZFLzYU4mibOIpX5IiAEy3zbTiQXBCwZAajVap1BMAZ/cFVPPMTxtbIAaqU1GxwFVZCPq8OH647h8P7wwohnL+7Wu6O7lsAsdmysrfoHerAR4mHHqQyctLaeSC/WD/HQ0R2mxcrEto4y4phFk4qQhkFAHnfD4Ci5CAKCgKEQgFqtOpyEXocvzKg8caCePTSwb4DZa61qhOjiXu3xypq38kheUelTSw48cmHY6K4+NaY08ZOEeCC4FxshHracSPvnSCpOZroQD3FZbB+tO8ZChLGhPiw/lBAPJt6UIp5BEBCCZRAYJRNBQBAwAAJEtlx1KJlvCGrUqlcHtFZBfQLcLdtvGs4x77JehMjKLix5ZcWR1FHFM/p1MACgLZQFHmYTwv3Y+Bbkv3ohHtBssTnYWg8P8cZJa0Cgpykvn2wh8KRYy0FACJbltKXURBAwXwSgVn8dSv4FrVXuaa0VlrLZgwMJIG7Z1EprMlZEvnVF76eXHGRp3mcbTqTmFuHbZO6BD9zPhHjAzqtCPBCcoqi0HIctNiyGo7oQ4sGnVwd3c6+p1o6yIwhoCAjB0qCQHUFAEGgBBKBWKw8m/bIzlmVoqvg+Hd2vHRLI3xaQpkWL5MvKhMh6btlBvk7DFwAB5KELQ7G7tahQhincr63DlQMC2PRDPPDVoD8PJLLhBa/7trSEeDAM2JKLqSAgBMtUWkLkEARaGwL4Qf9VhVoFVGqtWh+10prew9lu3oxe81Yc2X4qA+MaIbKevaS7JX3+79wQD6motQjxwOLD33bHsRHZAXd4CfGgPQ+yY9YICMEy6+YT4QUBs0QAarXygE5rxciqKtAXajUkCI8rs6yPQYV2srOBVH2w9hiKvf3x2SwtnDu9h6+rg0ELaeHMtBAPt47qXBniIXXj0VRCPMRlng7xwOe6x4X6jAn1JX5pC8sqxQsCjUVACFZjkZP7BAFBoOEIQK1WHEj6VY9a9QvAICjU6hwoCXzw3wldCd9ANKno9HwVIivY2+WcRBZxYG1l1S/Ag+3usSGEeCA6vArxcDQ5l+2LjSd76UI8+OCqJSEeLKLBW1clhGC1rvaW2goCLYVAcWn5n1CrXbHpZ7RWRE7C14oQDC0lkimXi46HoF/ob97/Rxe+85GFEc9c3B09nynL3BTZ7Gx0SwvZCorLNp9Ig2ntitaFeIiIy2Kbv+74gCBPmJaEeGgKyHJvMyMgBKuZAZfiBIFWh0AltUr8ZWccHkWq8lAr2AOBQ1sdFg2s8KQe7QiR9fKfh4ks9cySA0R+x0WpgXmYWXInvRAPG46lrT2SciAhm28lbTuZzqZCPBBMa2CQhHgws5ZtheIKwWqFjS5VFgSaCQEW5PMZ4AW7zlKrgUForYL4kmAzSWD+xQzu5Pnq5b2fW3qQmFKv/RXJ0sKZAzq2htAVhHi4pFd7NoKi8blDwjroh3jA8X9UV4Jp+faWEA/m/5Bbag2EYFlqy0q9BIGWREBRKwyCrBFTcqByQGtFtKeWFMs8yw7zcyV8wzNLD8ZnFny56SShwm4fHYz3knnWpsFS+7Z1uGJARzbc0dZGpa6LTEnIKswtKsWZj40QD3zucHyYbxc/19aCSIMhlBtaBgEhWC2Du5QqCFgqAoUlZUprlVlwmloN6qSjVnwV2FKr3Az18nd3fHNmb0K9H0nKWbovIS23+NGLwuxtLSFEVv3RC/JyvmFo0PVDgyKTcqFZqLUwOuOgRswwNqKIjQ/zGRvqG+DpVP88JaUgYDwEhGAZD1vJWRBoXQhArf7Yn7hwF2vtT1MrzFsYBMPbubYuIIxTW0xmuhBZK4+wzm7T8bQnFu9/7pIebq3v88moqXii2P5TGeKBb0tvqAzxgHrv+20xbF19XXGHlxAPxnkMJdcGICAEqwFgSVJBQBCoEQGo1bKIxIW74/ATUgmGdNZRK2xbNaaXk41DABfvp6d0m7/+ODrCQwk5Dy/cN3daz3ZuFhUiq/7IaCEe7hobsjM6858jKVtPprOi4mhKLpsK8YA7/KiuPq2QhtYfRklpPASEYBkPW8lZELB8BArQWkXo3Nj5SrGq7ZDOXhgEQ4VaGafxCZF197guxB39esup2IyCBxfsmzOtRxdfCwyRVX/8CPFA+Aa2yhAP6VgP4VtnQzysP87SCtzhhwZ7EcS1/tlKSkGgiQgIwWoigHK7INBKEYBaLYtIWLgrXqNWjHDXDg4kBncrRaS5qo2NbNagAG9X+3fXHMUJ6dHfIp6a0m1AkEdzlW+65VSGePCdEO6LJpUQDzAtQuGX6UI8ZLCh/+MRhWlJiAfTbULLkkwIlmW1p9RGEDA+AugJlkYk8OW47MJSVZqOWg0JxPfF+IVLCacRuKCbn5ez/Ut/Hobp8n3o+yZ05YygoxCoLcQDfvFsp0M8hPr26ujWehZjyrPR/AgIwWp+zKVEQcBcESDcJUvYftsTl3OGWhF6G61VKzdRtVRzorV67fLezy49iB7rrdVRhMhCsyWhCvSbQwvxEJNRQCQtdFrx1UI8oNNC7Sq46eMm+wZBQAiWQWCUTAQBC0cAarVkX8LvetRqBNRqSGCIT6v2/mnxVofaVobIOoA/1jdbTqXmFt05JgQ/rRYXzNQECPR0Ir7DdUODopJziQ6//mgqn2w6G+LB3RGaNTbMl2SmJrnIY74ICMEy37YTyQWB5kAAarV4ry7OEKEdVXkju3hfM1ioVXOAX58yWEX4xsw+L/xxkHWFrC6ENDw+KRx/o/rc29rSQDxZ2cpGiIeIuGx0Wrhq5RWVotb6YXsMG4QVpkXkUpYRtDZwpL4GR0AIlsEhlQwFAQtBIA+tVTVqhdYq2Fu0VqbVxIQheOXSXnxIh/hYRMl6/Pf9z0/tjh+SaUlpStLgesWXs9lUiAeY1pYTuhAPx1Ly2HQhHjq4wbT4Go+bo8BoSi1nVrIIwTKr5hJhBYFmQYA5/WKdQTCeHVUgI821g4M6ezs3S/lSSIMRIKr7k1PCP/n3BE5yRHt/aMG+udN7Ev+9wRm1shvOhngoKdtyPB2mtSsmk4WHLD9kI+QYIR6IDj8sREI8tLInwxDVFYJlCBQlD0HAUhCAUS3am7BoTxzqK+qESYU4jbixdxJqZfJNjFbmjjEh2Lb4XiE2L0JkvTCth8R6rWe7ESJrfLgvG2FHNhxNg2nph3iAv6oQD4OCPG1txMWtnqC29mRCsFr7EyD1FwQUApXUKn4RWqsz1Gp0qA++Vp28RGtlNs8IIz8fRfZxtWdRIbGgHvst4skp3fhgkdlUwAQExSZ4ca/2bHxUm+/wrItKwWiI9XB9VCobIR7wQeTb0hLiwQTaytRFEIJl6i0k8gkCxkYA73V41aK98fizUxaDNE6+UCu+rWvsoiV/YyCA85Cns/3c5Ydo0BeWHbp3fJdJPdoZoyDLzhNdIGyVjRAPxHdAp6VCPKw8mMTm5WLPd3hYeMhHC0SjZdlPQqNrJwSr0dDJjYKA2SNAOKvf98bjya5RKwaMqwcFCLUy96bFffv1mb2fXXKQRYUEfCd8A5+GFB7QuGYldgPxHWYPDTpKiIfIFPRYoEqUB5wU2Tq4O/LWQGolxEPj4LXgu4RgWXDjStUEgVoR0FGrPXF4shOWnURWVm3w5EVrJYNErZCZ2wUWe1aGyDoYnZ7//bYYwpDyEUNbCZHV2HaEnqKsYrtlZOf9hHiISvn36OkQDz9uj2EjJhw0a2yYhHhoLMQWd58QLItrUqmQIFAnAnzfBmpF1FCNWjEqXD1IqFWdqJnnReKYvzGz95w/DuGvjVULvcsTk8Plg8dNbEwWE/QJcGcjpitflcZ6uLkyxMPx1Dw2VhhIiIcmImwxtwvBspimlIoIAudBgOVRv+2OZxk/X68jKVqr8WF+GAQDJHr1eZAz48s4Zb94ac83V0X9ezR1x6mMx37fP2dqDw9nie1kgDbVD/FA+DGsh/At/RAPAwI9sB4OD/biK9QGKE+yMDcEhGCZW4uJvIJAwxGoTq0mhOuoVUcP+TBIw9E0tzvsbayJ7c7SQhyG8CIifMPc6T2k6Q3YjCgFUQOzoR7ecFT3PemIuCyY1vZTGWyEeBja2YsAEITUgpMZsFzJysQREIJl4g0k4gkCTUKAtfo6rVVEQmGl1grrxoRwnRt7B6FWTcLVzG5GW3nrqGAfV4fPNpxIzC4kDOnzU3t0a9/WzKph8uISUl8L8YAvPFEejqbkEuIB9SGbi4PtqC7e8LDeHd14E02+NiJgUxEQgtVUBOV+QcA0EYBaLdwdtywiUaNWE7v5zhoUyKIn0xRYpDI2AjP6dUCP9fqqSBQtjy/aj1qL4JnGLrR15k+Ih5n9O7LxEW4iaf0TmRqfWUCoOS3Ew5iuuhAPYe0kxIMlPyBCsCy5daVurROBTKjVLqhVQlFpOQgwV4Za4cYuH05pnc+Dfq1Hd/XxcLKbs/wwgz2Bsu4e2wWNi34C2TcsAjg4zh4SRIyMY8m5/+iFeCDsHBuvpLItyupdw8JuIrkJwTKRhhAxBAEDIJCZX7Jgd9wfetTqgu46X6v2bqK1MgC8lpFF747uLC18ZskBAjd8sPYY8cpvGNZJ7FVGbVzg7ernyqYL8RCfjTs8X+MhwG9CVuE5IR5CfVj4aVRJJPPmREAIVnOiLWUJAsZCICO/eMGuuD/2J+LwQRk21lYXdPObJdTKWHibd758/ujtK/vCsU6m5f+8Ixamdd/4rvKJvWZoVF2Ih47ubHeN6bIzOgN3+M3H09A0ayEeevq7jQv3Hd3Vmy/2NIM8UoRRERCCZVR4JXNBwOgIVKdWF3b3u2qgaK2MjrxZF+DtYv/6zD4vLj+0Nzbr78PJxCV/eko3iSbQbG0KnR0a7MVGzJTKEA+p8C0WHh5IyGb7eP3x/oEeWA8lxEOztYgxChKCZQxUJU9BoDkQYFBEa7UcrVXZaa3VRd3bQa3auYmVoTnwN/cyXOxt5k7r+dbfUVisdsdkPvJbxJxpPfjEnrnXy7zk1w/xsPFY6trI1P2VIR4IWsamQjyMC/MZ1MlTQjyYV8sirRAss2syEVgQaAO1+nVX3J9nqBXfP7moh45a+YkDhzwdDUEAPcojF4axtBCmjpWqMkRWT3G4bgiEBktLiIcpPduzYbFdH5WyNiqVoGVnQzzY24zs6gPTwrwoIR4MBrqRMxKCZWSAJXtBwKAI8LWTBbtil+9PKqnUWilqNWtggPjGGhTmVpQZ8ZhuHtGZsAKYpZJziipDZHXv4e/WiiAwsarCdy/v35EtLrMAhRb6RXbyisv+OpjE5ulsPyYUpiUhHkys2WoSRwhWTajIOUHA9BCAWv26M/bPA2eolY3VpEqDoFAr02sr85NoWh9/jIOv/xXJ0rYnFh149KKwkV28za8aliUx0fZnDwm8dkggIR5QaPHRQzoBfC4X741nI8QDkbTGhfoEeTlbVr0tpzZCsCynLaUmlooAJoNfdsYSovC01srGanKP9lcO7IjWwVKrLPVqfgRgVJ6X9Xx+2SE41st/Hr59TMj0Pv7NL4aUWAWBsyEeRhDiIQud1oZjqTmFuhAPP22PYQvxcRkb5jM21Fc8BKpA1+KHQrBavAlEAEGgVgSIUfTrzrgVBxNLyypIhMcM1ApfK4wItd4jFwSBxiKAZfDNK/oQvgFbIRbD1Nyim4Z3lm+6NBZOA99HQxDDjO3OMSG7YjJgWvohHr7adIrmw0mLWLLuThLiwcDgNy47IViNw03uEgSMiwDU6pcdsSsPJSlqxQKiyT3bXTlAqJVxYZfc8XB/64o+zy07eCwlD893tKcPTOwq69dM6sFgojWksxcbX8HaciKdYFqsNyTEw8GEbLaP158gxMP4cJ/hwd4Sd6NlG04IVsviL6ULAlURSMkp+nlnLN6speU6rRVj28W92l0xIIDARVWTyrEgYAQEcMZ6bUbvl1Yc3hWdiYd1en7xMxd3J6aDEYqSLJuEgKOdjfrSDh+XJMQD35aOiMsqr6ggpBabvc0x4mxJiIcmQdy0m4VgNQ0/uVsQaAgCfMoGN9Uuvi413oRdBl8rjVrZ21hP6dX+igEdhVrVCJecNB4CaD6en9rj3TVHiUG6LzbrkYX75kzrKYZp4wHexJy1EA90L+ujUvnooS7EQ1n5v0dT2SDHhHgYG+rTN0BCPDQR6YbdLgSrYXhJakGgKQjMr1wJjwmmil8L1IovlqzCIFiptYJa8QleqJVEfWwK2nJvUxAgAsiDF4T6utr/tCOWL+o8uGDv3Ok9+cZOU/KUe42NAJOxGf06sKkQD+uiUmIzqoR48K4M8dBWvj5p7LYgfyFYzQCyFCEI6BDAW4LZJDsQKeKCKlCSsjEIxqw6lIwLBWcI3HxJJbUi2o1KIH8FgZZCgDGY70D7uDp8uO4YzlgPL9j37CXdcbKuIg8ProzWVTBp8cOzIR5ScjEdYuo9E+IhYfHeBL7+jukQpiUhHozaUkKwjAqvZC4InEaAOIEfrj2mDr7afGpEF28Ww6O1Wn1YqJU8JCaNAMpUNKnzVh7hGX5qyYGHLwgj0KUmMY7wGJ5C/Vy1M7JjOgjoQjz4urIRS5YQD7jDM8cjxENidiGKSbZgb5dx4RLiwVgtJgTLWMhKvoKAPgJfbTrJDFKdySooeXhhBDp8TWs1tbf/Ff07ejjL4mp9zGTfVBAYFuw177JehMjKLiyBafEkY4RCuD8PJH656SRBSoVgmUpT1SKHFuLhjtGEeNCtXUChziLEE2l5JzblaSEeRnX18ag9xENmQQnkTL6kVAvGNZwWglUDKHJKEDAsAvvjs/kks36e0en5HDrYWjM48U2MOjo1/btkXxBoKQS6tW/71hW9n15yEOXHZxtOsNY1vF3bD/7RKWWJMH7ryGBiB7SUbFJu/RGoDPHgOaSzJ+xq68kM2o4QD7h+6oV4cMd0ODzE27nautEVB3Tf6nn7yj4SZ6uegAvBqidQkkwQaCQCrOVhNVb1m1mT9e6sfp61zxer3yJnBIEWRKCDx+kQWVHJuYv2xqMU0bkNtmlDjIDtp9IZkltQNim6oQgQ4oF1hWwopTYeS1sblRIRq0I8ZO6MziTEw5BgT5jWoE6erLkhc0jYHxEJKC/nLj/88mU91cmGFtra0gvBam0tLvVtbgS+2RKNNbB6qXgN747OnBDuW/2SnBEETBMBrNjzZvR6atGBw0k5FYpeVQq6+nCKECzTbLLzStXW0ZYgxmyQJ0I8YD2EQDMt3HA0jQ09Ft9QgmlBo5WTA7qud/4++shFYaKxPC+2QrDOC5EkEAQajwAuDr/viavt/i82nsS7pboqvrb0cl4QaHEEWPZ/qtLArS/J9pPpuGe5OYoToT4qZravhXiIzyzg29IwLdo6v7iMNc5shO3Q6sMltUpROyM7NSKgU/3JTxAQBIyBACGVmerpT/RVKXRVRGEgpFBHD8fdMZnGKFryFASMgQC+g3ypsKCkrErm2I/4NF6Vk3JopghgC752cOAnswe8P6vfzP4dVYBZFaJPq9H326L/OZKiHcpOjQiIBqtGWOSkIGAABOIyC1FQEfKKOMuuDrbM73U7jrZ4P5ydDBqgHMlCEGgOBHBsf2rxAUxFNRb2R0Ti9D7+NV6Sk+aIAH0U35xgI8TDC38c3HYyo0ot3lgVyRxyYje/KuflUENACJYGhewIAgZGgPXM1wwONHCmkp0g0EIIEHH0uandGWi3nUiPTM6tIkVMRj6mQwn1XgUWCzjMKSrdE5NVvSL44L2/9lgPfzd/d8fqV+UMCIiJUB4DQUAQEAQEgfMjwLJBQlZiPHrnqr7f3TT4/gldR4R4o47V7uTDhdq+7FgMAoRmwOe9xuoUl5Y/t+wgMZNrvConRYMlz4BlIoDnU5Xv/VlmPaVWgkBLIEBsd2zfbCVl5RFx2VtPpm87mb7mSMr/Detko+cN3RKiSZmGRAAj4B/7E6rkaGdj7eJgg9uDiz3ODzYEiOcDX1XSyCEICMGSx8AyERB2ZZntKrUyMQQYawcEebDdMSYEF/jC0nKXagEqTUxkEacBCLCK8KbhnV0cdESqkk7ZOjvYSBCseiIoBKueQEkyQUAQEAQEgVoRwCdaHLBqRcdsL6Cm0v/0pNnWo2UEFx+slsFdShUEBAFBQBAQBAQBC0ZACJYFN65UTRAQBAQBE0Lg6NGjl1T+MjKqrvk3ISmNL0pqauqcOXPeeeedgoIavvGgyj948ODdd9/9888/l5fX7GBufDGlhKYiICbCpiIo95s1Anv37n3kkUeogpub23fffefoqFtvXFZWdu+99x47duy+++67+OKLzbqCZiT8gQMHnn322ZycnCoyh4aGvvvuu7a20llVAaaph5mZmY8//vjx48fJ6OOPPw4JCVE5Lliw4NNPPx0+fDhXnZycmlqM3v27du2CYwUFBXl4eOidNvXdr7766scff0RKe3v7jh07Dhw48LLLLvPza3z8p3///ff7778PCwubPXu2Qjg2Nra4uLhTp042NrpVmXRBv/322+rVq2Fg06ZNc3Z2NgWMNm/e/Mwzz+Tm5lpZWf3zzz+qtzQFwUxWBumzTLZpRLDmQIBp4qlTp1RJe/bsGTZsGPvp6emcpx/x8vJqDiGkjEoETpw4AezV5+v9+vWjQxeQDI4AepSoqCiGdnL+/fffH3roIXYY2nfv3s1LMXLkSAcHB8MWunHjRjLs06ePGTUovIdpmNZLgNj69es3bNgAJW007xkyZAhog4OnpyeAMKm4/fbbw8PD586d6+Liwhlra2t4Vbt27UaNGmVYjtvoBuXFXLx4MU+LnZ0dmKSkpAQGSpC/88ApBOs8AMllC0aAsSQiIoIKMjGly1i+fPnQoUPp+hMSEgoLC2FXdHCq+lyNj4/Pyspi2urt7U0CFCpc5S9qAOwdnGQ/OTm5qKioffv27u7uTD3pg7jKoa+vrzaiUCgDGz+KIDeu0mFZMMj1r9pFF100btw4YHnuueeYu0+YMOHll18GHH5M6wEfPIEaXWOHDh3atm2rcq6oqIAQ0yKwAcBkGOAQBQlDV2lpaVJSEoD7+/vTENzOXdxLW5CGxiJndAa0fv2FtKSUgAaegABoqG/vuusuxvL8/HxAA6JevXoxzJeUlCQmJoIkzypjP2BylYe8EQgzY0F9Rc49evSIi4tLS0vz8fGhyShFQ1W1MpdoPlpNtTLi0Vi8UAEBAXAR5FFXtbuMupOXl8eTQxHXX3/9Lbfc8r///e/rr7/et29fZGQk1J/z6k1HZjQ6oIRsWo2ys7ORHJBdXV3pT/iBNhgCwoUXXkhKOg1qhHoMZHgUgYWU6jHmOb/gggsAgcSUQkOofoN9cKNL4V72+akuCNUa3RStA85kZXAdIRIuW7YMeVDgLV26lII0gqXeQVCiLqpSSAX7VP0eUiE5V0nGGdVtVgpu+X+EYFl+G0sNa0NA9Yz0XxMnTlyzZg32C8ZdqBKqFHpVug/2uZch5/XXX1+xYgVX6bmwDqDex56CCwW9yZdffsngdM8999ABrV27lhuZmM6bN++TTz7hkG6oW7dub731VpcuXciKq5999tlff/1FEQwbdMfkhjmy1Y7x+k0DCPwYfhhBOc8AD7zs0C+D5BdffMGoBv1iGKOLx4WF4ZarW7dufeONN1B9QbDgZCRGwfDoo49eddVVzLYx8jLe/Pe//8XKQwPRv2OFZPx77733GCAZ7W6++WaIhTYi6stj8fvqOR8zZgzjOgZx9DRocHlEFf5YZkEAAyLKFV6B999/n+kHzzNgos4B4SuvvDImJgaEeY/wFoJ5KIThx9wIwih7QBhScuedd4IwVIPM4XCc55VhxsIrhslp7NixpOd1oJVpJuY8ZEiyAQMGvPTSS4zotOCTTz6JXu3NN9/kdcOUzCGlN08DQZIABIrfu3dvhJkyZcrChQshDXBBBAC6+fPn03tAsKgj3BFkAIpL1BcbK70K1eH24ODgp59+GsMr53nlT548yeHgwYOBi6qRft26ddjgqPWHH34I7Ndddx0P86JFi+hzyOHzzz9fsmQJgJOSJ/+2224DAcW96Gp++uknWBqGXR5+ElPKRx99xNtEYoP8eO9oKXg2LwsvDnnCzlXONNyff/5Jwx05cgRYKJQ3kUvTp09/6qmnIJeo+rAnAhTVQXLqTqdnEKlMP5OzUwfTl1UkFAQMi4A2luBoxeSSaRZDDr0Af+kpmEcyiaREqBVeKbCr/v37cwsjBymZnzG9JhmDDSeZ1NKTwgnoibZt28awjZsFh3Ss9Dt0neQDdYAK0B1zC74XdFXkSbdIcYatl1nnxljOOE0V+vbtqyqyadMm+CuoKhsKJAlLE306V+m+P/jgA4ZklCuoE5hh//HHH8z1Gcy4ykgWHR3N6KgILu3FoP7www8///zzuAGhBqDhGMBoBVVQa/sLqaLK8BvmAOzAb3j4gZTnk5G7c+fOnGREZyhFZaXoLE8+kGoIw7c4BNW33367a9euCmGMXyAMLVAIY1dSCJMMqkT7ov/gVYJ7kTk8gDMUtGXLFrwhaWWEee2117iXViYll2AMvEQke+GFF7Zv3874raYrXGqGH3WEHECeqCDFUV9qwXvN7IjDV1555ddffwU06Bcqpf3790MK4RxcohZUgScTmgXj4alWjyVowFGoFJM08CQB3Qj5jx49+tJLL506dSpTCCgXDyetoLREdC+wLooGVWZ94EZPohgeBWGvBBwebJgrrQYNovNBEi4Z6kcPhgcFL+D48ePRsZEtmKjMEQbyzQxn1qxZUECeDfRYUKsHHngAlJiFfvvtt1RTMULmPCDGY2YowUw8HyFYJt5AIp4REWDSyQtPLzZo0CB6LnpJ+jU6R7oMSqVP5C/zVyZn9IAzZsxg9vzLL79g/uN89+7dmavRS6qOhlGfThC1ivIUZgygW2GYIRmJ6ZH5e/jw4VWrVtHpMMdlCs4Yo3w4Wk93Awjn/TGUQlJJpun8AJZeG+0Uk3jYAEMvV2Gr/IVR7dy5kwGJuTutgxGHk4xzalhCDcDAw9B16623ooO88cYbuQpXuOaaa9CFQII5pLlpXHZa4Q9VELVG4YpGkLeA55OhkUEaQKALanbBwEkaph/KXI7ehXEdbqT4FnMDXgEQZviET9xwww0kBmHmD5BaBTgtRfNxHj7Hi0BWNBb433TTTZykgSiUEtFpcRWSgT6Gv0xvuKqYCsSCEZpDKA6EGPMx4nHYPD8eSN5Qfn///TcUEDcp9keMGAGVgfrzRlN96k7PgKoGkUgPlSQNeHJID4DChkcX0qMqpRDmLlg+swI6FigRPcYTTzxBj8Ehd8GZ+IsZkWRUH3ZFhv/5z39gnKwrpLFoBaX3wvSmVEro/OhzwJYb+YGq2mn6X/pANGQUyjuIUlk9GEilcoaO02FCE2l0GKS6iv8+bBvSjKs+7yOzIDSdqOu4hUP18jZdMNPPQQiW6beRSGgsBOjx6d979uxJr8HckWKYH/Pyq5m96sQZpFX/xRACH6IXYzgnpdKvMCSQgEO6Hma03KvIAeQMXx8OGTnomHCPIA3dMb0hBIvRAqMJKnd6LowySlVAAvmBgBo2YEhqREf/BIXiPOAza2fMZmrOPlZdTq5cuZIx+IorrqA5wFl17twI3+Wqaji6fnxZGKhoa07Cj9Whaim4AiMB51vbjwEYBgAsEFkeQh5L4ELnpzQfkyZNUoCgt2CHx5txkR3FyYBXIQyZ4CQAKkghWxzi/cMhzaEQZh6idB6MxLAERllcvEmm3iPKpQl4LxSl4E2Ee2Edo1xaCrc8UmK75C8/3hr4CrlxizrTDH8xTFMKHAiWg4aGOmL8wjuQrgB7HJdAD7shSCpazxkoJtXHS519rH533HEHPFVpvDij/D4xJio3KUXgyI0eg6v8wA3VFzvkzF8wpxuB0WJsBUzyAUaVjL+HDh3iL78HH3yQDFUTcKgJU3mxSX/QzfMO0lI8BvR46klQambyRRjeQa7SXnRxMD/V43EexOgDqRdVgB0CGijRuCqHJslkJjeLD5aZNJSIaQQEVE/HNJEeAfdqenw6CHRa9B2aGUKNN0w9lXqf7gOTAbIwReMvVAxNPjsqEy4p1wQGBroSVGLMZclc3auUASTGh0ONOvSY999/P/uclB8I0Ckz0WeHrhwA2UFlQp/ODgMwjcKPlmIsQVPIOKTYGGRLS0xKDunu2dHIgdIcKL7FCK0YrbLMMg6p4Z/0rerHw49iCd0tBJTnE+UQfAvEFJ1VQztEYceOHcDCikL+wlCxwLKjIayoD42l2LBCGOqAPphktB1/NYTR3HBIidAjhmTIHIeMytBi8qEsDml9XgdaGVWlamVOogjhLzKgaWOnOX/wA5z8KBF9M08OQDHvQufHA8YlRYOor2IMdB2kRHhFbpiS8YiimQNV5aPGg8cTjhmUZIqDsqMwBFKNNfJkggZFqDme6qa4l5YiPWSUv/QqyrCr2ovXQTWZ6mSAVDUBKZv4QxJ0iqp1mMloudH1gQBCIhgPD4foiSGLVB8uBdWDwSs6znwS1ZqihmBy7bXXaplY/I4QLItvYqlgrQjoTxOxXDBOsJCQaRYDD6ujlf1OzV9x+KVHIyO4EV0kczI1ZqshnN6NH1cZorjKZBStGId0lJAD+k3V2aGv4iQzeNw86SuZrONOoZgB5+UHAlBSNSNXbsKcUeyKHdYNMIqjLAF5NRShEUGvwCU19cdmAT/mUI00ZKX0K8rmwmCg2Njll1+uMFfUGWuUallubFU/NCvUV62DAxC4PvYv7FyABulRHu5MGNTICrcgMTYyNbprCCtGpXyWQVi9DgCuEFbjK68SCKODUYf4iZMVzaoJADtRrwbnUV/xXkB5aWU18WACg16ZS6xaaP6WwvilJlS4f+GBhBjaD7rJ8j0OlSKK6mMO4xBIleRIi+6KQ4Bl3vXDDz/gGACAimhqFFbVDpS0nNUrgMoKNSFMVOmKePIVqjiMkxJDOY89PZViwGr5M+cVe0Ohq+YYWp6N3sGFDg0Wk0+lsyQfHgnIMR0djcijQjXpKrmKxROvU9in0jtCLklD+quvvnry5MkqjcKq0cKY3Y1CsMyuyURgwyDAvIqei45DkSEyRQsFwVIaFNX9cVLRLHoxOlPmmqwB5CRUTPVfakTnRnWohnAm38r8oUYU2BXsjbuUoZBBiDNMMekc6Wqr9Noka80/AGFEYSDRnGwYaOnB6ak5j9aQHYgUQwsslrmywooBgCEZBzhIFYmV9Rb+BP2iXejxSQbZ5So76iqaSEW/0Ey0QsCBkaUbVFwxJ3awCbK+UmlTeCMURVAEgqv4ZQMmblXsawijWVEIq8bSEFaAawgrwEFb6XphAJgIyQp+zDRDuc3xaqhW5qVQrQyz4SRNjAmeoZqrLdJSSnvE26o01lRf+9EzqCcQ0DDMMVvDHws5ef2BBdU1jy7ckZ6EHdBQN0KeAF/rdmBvylkKggJxIT1PrKaUIn/eBaUPo7MiE3qtb775hqxgVEwzOFQLCFCtcRL0FG2tLq0mdoN2oIOs3uUWlFJMC9W9dIY421ELaDEEC/8q+jQ8IBEJafmpZICmFHuQSx4zziuyiKiqt2yQJGaaWAiWmTaciN1UBJQunbFB9QJkRy9An66c1rUBHi6F1ooOFJU+ow69AwOJciJhwFb6LaVuoVdVfEubjCrjArM3ul3yZ2KHzxCDFkoU8qELpuvE+7WpNbGg+xWeDA+a2Q5VCiMrFIpFUjQKagNGGibxymeFMwyBKAbo6JVqhDPqXmVXwqikRkE10YeZ8QMwRYXJRC0NsyAI61UVNBCMzfqGJFDC9qrWZmpr9Hg+0SfxnOO/zCSBB5hYDGgp9BHG5KcQVpoYDWGaDFFAWCnD1KtB67BsFkd1xmZUMiwoU0sWsHYRngBigcWc/KEaUG1eFnSWStGISDRxvepm0ESKr8AR1SusnzcsgWcSz3R4Fb0EPAl+ww6uV3QF+AtCDXkmgRpyCX9Sej6FEhkqkgE+kC0YJGuK6V5gM3RBytTIjtLUYpgDCgCBBENr4Kk8tFAcKAseipRLcygNOnyInorzmO30RW30PjpL6BEEkTmklgkyw4xRSSpqqCaTxPLgtUUMngeeE54WngrWk7744os8VEw1qQ6UmgeA5SZCsDQwZUcQsEwE4Dd0cxoZopL05vSPjPFah8VJ3NUJ/IPiCkqEAwF9JSuW1WSaHJis053Ra5CSnpROhJ/iW+jP6TEpAiOUQpC5LBYQHBoYM+guyYSFzeqS/AUBJriM5SAGf1VDCycZ4FVQMTSLqAoYiVmOxNjMJeBlSTwmXfBk9OIbd/TmLCNXWaEbICtIA4f80HupnNVICUvmkLFfaShVmtbzl/WzqKkY9TXPa+rOFILRlCFc0xUBPuvaGBF5I/BNpl0gpgpSGovRvTrCPPw1IgzgOFERsIBgELglwTwYkrXWIX9aWYVxYjCGQNDKmJMQRrUjw7Y2EWq2ZoJDQJWoo3JBq14utAN6ASuCGiIzRkweQkDjLp5DCBb8jGcVwsGSVVy1MCMyvyJDrU+AX/LQYj3EX42uhnuZQtAuNAE/RUR45pkelD/LAABAAElEQVSGsUSRaFsQF8gu/Qb9DPLQyWCYg3pqTgh0U9Big+jFAV+9cQimWLJCgBrBhikaQsn0hh/naUEajh90ireY5QichBpC4nHAolMlMc8GEGmvtsrNsv/qdO911PCX/WtuXPgyCT6f8di1fS6EIDPvoV+D0iqHuzrulUuCgMUgoF6T6rPYxlWQwQla1rh7W+1ddTQBlwzVNK0W3joqXgfyddxVx6U62svgZdUhhgEv1fZGc54nsz4PZx2YaHLWJ42WuBl2mPPAg6F0aCJhYMww0SWzGAX+h71eX4Da8NFPY177q4/tmP7d48j86qQ77xp8GdZbZgJwR2YscEqtLmIi1KCQHUGgVgTq00XWenO1C8KuqkFy/hN1NEEdl86fr6Q4HwIGh7eODOu4dD4xW/J6bW90beery1qfitcnTfWcjXQGtoc6E30bWjfswijtUL6gAUVIVG5VCq0/DlVuNPdDIVjm3oIivyAgCAgCgoAg0KwIQKTwuMKQhR5LLQnCCIgKBzsgXqfNKooJFyYEy4QbR0QTBAQBQUAQEARMEgGc7nFhJNoqBjLcxfDNIiYF7mVq0bRJitzcQgnBam7EpTxBQBAQBAQBQcDcEUBfxaogFZYChRYci5+5V8qw8gvBMiyekpsgIAgIAoKAINBaEBBeVUdLy1KmOsCRS4KAICAICAKCgCAgCDQGASFYjUFN7hEEBAFBQBAQBAQBQaAOBIRg1QGOXBIEBAFBQBAQBAQBQaAxCAjBagxqco8gIAgIAoKAICAICAJ1ICAEqw5w5JIgIAgIAoKAICAICAKNQUAIVmNQk3sEAUFAEBAEBAFBQBCoAwEhWHWAI5cEAUFAEBAEBAFBQBBoDAISB6sxqMk9po9AYWEh3643fTlFQkFAEBAEBIHGIUAoeZP6RGOVWgjBqgKIHFoIAnv27HnssccspDJSDUFAEBAEBIFqCCxfvpzvIVY7bSonhGCZSkuIHIZFoGfPnpdffrlh85TcBAFBQBAQBEwHAVtbk+YwJi2c6bSiSGJ2CPDl0fvuu8/sxBaBBQFBQBAQBCwDAXFyt4x2lFq0KS+rEBQEAUFAEBAEBAETQUAIlok0hIjRVASsbayamoXcLwgIAoKAICAIGAgBIVgGAlKyEQQEAUFAEBAEBAFB4AwC4oN1Bgn53zgIlFWUl1eUGyfvc3K1tkKHdXbCQKllbSRMwzkQyYEgIAgIApaEgJ21SXMYkxbOkp6D1lmXwpLiuIKU5qm7h72rt6O7VlZJcVlscZJ2KDuCgCAgCAgCFoZAcFt/ptYmWykhWCbbNJYgWGZJTkl5afPUBFWZfkHlpRXNVrR+ubIvCAgCgoAgIAiAgOlSP2keC0CguLnYVQ1YVciiwhpQkVOCgCAgCAgCzYOAEKzmwbmVllIuLKeVtrxUWxAQBASB1o6AEKzW/gRI/QUBQUAQEAQEAUHA4AgIwTI4pJKhICAICAKCgCAgCLR2BIRgtfYnQOpv2QiUl5dnpmewqWoW5OenpaSVljbTygPLxrZxtSsqLKQJ8vPy67idVqvjqlwSBAQBs0BAVhGaRTO1FiEZ+E8dOxl78pR/QEDnrsH2DvbGq3lKUnLcyRh3L4/g0C7GK+W8OTOURh8/WZBfQEpra2tnF2cPL8+27m7nvbGeCcj5k9c/sLKyevTlp7ll6/rNi39Y+Ngrz7Tv6F/PHJonWU5WduypGFWWnb29a1tXLx9voz4AhqpXUnxi9PFT+bl5nj6enbuEuHmejRVSYxEH9x749qMvJkydNPXKS2tMEHngyNKff/vPA3e5ny+rGm9vnpMVFRXJCUnRJ07ytd3OoV08vTxrK7ekpES91AGdgjp1Dbazs6stpRmfr2iTmJCYkZpGFXjXXN3a8vTyLlepEaBlZ2YlxycmJybb2Nr6+bcLCulk4p8rpgppyamxp6KzM7MDOgcGhXS2sbFR9eIBSEtJ1a9jx6AAN48ann8qnp6SdjzqGIm7hHcFHP27LHhfCJYFN66ZVa2wsPDTNz5cu3w1w2pxccmwcSPvfepBJ2cnY1QDWvPd/K/W/vk3Pf47386H2RijlPrkWVxU/MU7H+/bvsfO3o4lAaUlJbZ2tmMnTbjuzpu9fLzqk0PdacrLyiAu1lanvyOUk5l9/MjRkuKSuu9q/qvHI489e89j9N3WNtblZUhd5tPO78Z7/zNy4pimtA5jAENa1+5hxqhRRnrGdx9/tXrxCprMxsa2tFSHKkR22NiRdRSXn5t77PDRfkMHqTTwj6OHIhm3XFxd1JnIQ4d3bNg6bdblJkuwGC/Xrfz7o1feRWD24UxPvTGnR79ecIsqFS8sKPxo3jsbVq2zd3AoLi4adcHYux6/z9HJKC91laKb85BYyst/XczUBdoEBqUlpXCsK268esrMaY6OjkoSpjrLFyz55cvveft4YJhMlpWWBQQHvfPNfN795pS2/mUV5OX/sXDJdx99pSRE8gmXXHjHY/+1t7enC/3j18WLvl+g8S2yffrNOQOGD66e/74de95+bh5a28pVTxVPvzW3z4C+Vi3X61aX0EhnhGAZCVjJtmEI0E3/8sX361asmXLFtBHjR+/buYfe6rO3Prr7ifv1X+CGZVp76pTE5CP7DwV16ZwUl7B/974+A/vVnraZrtz5+H3QoITYhMgDh9YsX81E+I5H7jULFY4BARp90biBI4bkZuckxiVs37Dl/ZfeYpYf3qt744pgPPjqvU/jY+Le/e7jxuVQx11Qh/fmvrF7844RE0Yjs6e3V1J8QtShyG69e9RxV/VLB3bte/nRF+Z8ME+7ccKUC8N6hDPRr57YRM6kJqX8773PO3cNmfl/V5cUF//w6defvz3/pflvVNHZqGnM5n82TL16xrCxI3Zt3r70p9+dXV1ue+juppBmEwGhRjGmXT2jU0gnNJr0Kl+//zkPyVU3XUsPlpmR+ebTLx/YHdFv6MCBIwb7tvdLT02PPnYyIDjQZNkVFYw5Gb1m2arJl0/tM6hfG6s2K39fvuaPVYHBnWZcdyU9NrUjzQ133+LgdJpEBnQOqg4Lne1rT76IyvzOW2aXl5b99MV3781987m3X2RSUT2xhZ0RgmVhDWqu1clIS9+1ZYebu9ul18xkTEWxtG395r3bdiXFJXYI6mjwWkUeOMwgcetDd69avPyHT77u/UlfJt9FRUX7d+7Ny80dPGq4pjnDAHRo337MiJ26BCMG6pCdm7fHx8aHdgvtM6i/45meZe/23c4uTl26hdG3bv7n38CQTmTIPK/fkIFaBxp18EhcdEzvAf28/Xyq12j0xLH2jg50W3HRsQ/ecHfsiej8vDwI1onIY6eOnxgxYQxGqO0btnIG/RbJYk5EH9wbgTePt6/PwOG6LlvLkyrs3babfEK7hyGSrY1teXmtXw1Cdb9v157k+KSAToGDRg1FZpDZv3svBh1N8YOWBbpDjXoP6MvUXCvI4DuUOOai8WTL2NyuQ3s0mvt37dUIFjqAvdt3gbCXr3ev/n30rZy0y45N22gsjBTd+/T0aeeLtEcOHMLcVlFRvnbFavLsO6i/Z6VtIic758DufTHHo73b+VAjDTpm2Ds2bunWp6ebu/uOjVsZXTp3Ce4/bJDWyvr1ZfoOu7poxsW3PnAnNk11CbWEZvFBjVEpwGF7O/u+Q/rXOPbk5uT+uXAp+rqdm7clxsV7+frA9TFex0fH+nfwb3vG2pKRlnFwzz6YYofAjmG9uvv46WqHUXXHpq0JcVS5Y48+vVSV9SU03v6/q9bywj4094neA/tSCo/Huy+8DnsYPGqofqE8nLu37sQedOnVl/PMB3YO2rRmw56tu1ISk9p1MC0Ltb7YTdkHkEEjhvB5sBNRxx+79X76k6lXXYZuEv0WWpxRF467+/H7oJiqCNq9KWU1w710IPM+e9vFxRnNHMVREToxXo3p11yO6hKHTk5OnXWZ9szXKBLTZvquCRdfOHT0cBIUFBS8N+cNHgMhWDXCJScFAcMjkJWRyYABF3H39CB3psL4ISXGxifExRuDYO3ZutPB0YFZNf3F6iUr8IKCP2Gd2rjm37V/rn781eeGjBqmKvnDp99sXbfxtc/fZchnLv7pmx9hxWKEW/7LYjqI+597BB5ASoZJ/vYe1O+nz74l50uvnbl2xd9wl6ffmNOlWyiXsHnNn/cuRqVPFvyPwzp+KG/gQ3AIZxddR4zX1E+ff1tUWPTLlz9gUxg3ZSIE699V675892O0JrZ2dihOsDvgVqWICP7srz/90qE9B3CYwAbasVMAxNHOruapFEqFj19/HypAVoti4jp2DsQsC+H4bv7/nFyc3/r6Q+UxczLq+Icvv4NXHJyyDskNeAm4EmLjybB7n14q28MRBz985Z30lFTf9u1gWpgtZt/xfxdMmwzVIOWcB57G2Ort671h1Vpgv/2Re0N7hsPPQMPa2mrJj7+TSVBIMATr8P5DH73yTmZaBgjzyDELv/Whu8ZNnkiC3KzsN5+ZB8KMjhzm5eSlJacMHj380ZefquI5VFhQsOK3ZbibTLzkIo1dcYs20pDt/Fffpe1ggbTdp29+ePP9t19yxXTai2Ta7+cvv4/YuRdb0YZV6+H03fv2hGCh08Jt7u1vP1IEizbidoTx9PZEt+fm6fHiR69x+ML9T+EvD3HZuGptSmLK7Y/cM3HqRVrORt2BNvGqtg84TZKCgjvB+Hdv3VGFYOGTlJeTy4vc1l1Hyl3aurZ1a4vBOjkh2VIJloId45eHtxdPJq4OZaWludm5sCsuzbxhlsauOLQ+48yk7jLBv1SESa+eYDoTMP0DOjlYNRMSaD0PYX5pGZMQrMB6KU/v8mDs3bGbLtGvsp/kLDy7cn54qnpiyztTc7drefWUGpk4AoX5hYxDIeFdeRURFQtCSFiXg7sjGPMMLjn9wpZ1m0ZfOA4yh8fAqsV/cghbwjECc8/fS1fu2bITnRCdCC6cm9as7zWgr1+HdskJiT9+9g3ztidfe54uBpXVZ29+hBHz8XnPqmF1z7ZdKB6waXYICmAspPf8/K2PDu07oAgWnk+4GWFBQE1VY40WfvuLlbUVVOZE1LGe/Xtffv1V+vbB3779lVlj74H9FAHtO7jfU6+/gG6AmeWpYyee/+8Tfy3+UxGsZb8s3r9z3+w7boQ0QAphflvXbYIbVS80KzPrg5fe8mnvd9fj98MVjh2OeunhZ5cvXHr7Q/cMHj1s+a9LsKKiKKI33L9rH3PQoWNHan5C1XMzyJndW3ZAnuA96O1wBL7qltlhPcPJGRm+/+TrlIQkuC/EEfry5buffPH2J8FhXbt2C13/1z9w8Sdffz6sZzcaF+UKQ76DoyPMCc0K9oun3niBTNBLcRW7XllJ6eOvPuvXvl1uTg6N+L/3PqtUbp32ePv3r7X3P/9otz49kOTbj77asWELwpCzfgVRKZEVqlaotv55bX/pT78h1X8euHPo2BEwP6jeb9/83H/owCqz9stnXxl7/BS6H7zN0N6hPtRyUDvU5b0X38Tl/4nXnvfx80GpWVZW7tq27R+/LqHKD7/0VM9+vZATIhhUqWGtcruRDlkd4tvOT/Mugp0jIRODKsWh4SguLm4X4K+GXt1L3a3r8cijsK4qKS3skOkBtBh1JuwE3ox7OKTfzcOtc5fOqqYkaHPmSxM4HULFTB8B3sGdm7bhlTWhksdzyCsA43/+v0/Szzg6O425cNzEaZO0OYaqERbkooJCHgAP79PLINpVLq/JNkLHboIYCsEywUZpjSIxDaIvZuzUKt+uY3smSdhQtDOG2kG3RDeBJzJ9RK/+vZmLH9yzn84C9oD+AKqBWgsNAR3izk3b0e70GtCb0fr4kWNY5WA5vv7tkASjoaeP14kjxzBOqUUx5HnDPbcMGnHaSjJ+8sRvP/qSuT42Agr6+4+/mOQxxNZWixW/L7NqY0WV6W1HThzbPqADd2k9b4++vS654lIooLodmoW0IIZ4aPg6dArAUZpL9HSLf1jg6uZ6wbRJSiqlS6uxUNgMRpxxUy6gIiSAyuBye3jfAXgeTkX/LF/997K/KJfBAO2Rja3NyImja8zHgCdZYQfOuAwXFxZ17BQ4+AyYyYlJ+7bvZt1DvyEDVHFUEPvL38tWQrBCe+hIGHYr/4COUGH/gA4qjYenjubS42NFVWcwfUIOJlxyEWQUAs38+8qbrn3u3sf/Xb1u+tUzVBrUkMpMyeGwcSO2/7sZCluFYKHBwgzk4OBQ46ydqcLPX3yPOa97317ot9gAGbRPHTtVhWCx5FBHo62saFBNSCWG+rt3x56M1PRJl13cvU8P7WHgUnivbjwem9b8GxQc5OffXt9aqn+7MfZ5xtJT08J7d+eRUPnb2tsxfOJqU6U4Zk2MrwFBAdp5mga6iQlbO2NhO2uW/bVl7aZdm7YBEcb0y667gq6jqDCZRuzWr6dSWTFtm/vgM7B2Vfc3v/6QZ9jEcWDdyfaNW1f8/sekyy9RHqvQZaYxBXl57t4eCdHxrCb5aOe7KMunzZqh/6CWlOh8+em4tLkZWkxHZ8e83DwTr7JBxBOCZRAYW3UmZSWFxTlpxdmpTj6B9q6n1QANRQQ1A6MVDEa7EX8aXkt9jbp2qSk7TPdZ+cKotm7lP/AnsmLyffTgEbzd0Z9x/prbrv/ynU9ZltzFMRTHIzRqA0cMpctgDkriLWs3Ruzcxw6ePdzCeih6CkVlONmrv84lRf2Q/OIrpy/7aREDD4ahXZt3YEwMDuty5nrV/+e8P4+RGFNp5P7Dn77+AQaXu594ANlUOsYzjV1x5uCeCBzh6dQYqyAKqHYYZTmPdxEDWNce4dpCLRgAViR0NlXLa9MmrjIsAoqWXVt2qqvUkWGb/fCe3X3b+UYdOMJgQE+Kx9LYKRNrZADVs23KGcjoxKkX4pxO1SA9LzzwlLLfxUfHkS1sT8scYajjqaMnGO97Dehz2ewrVi76AxKDShL+hCsMYmuJtZ3EuESaEuqjXYVjQXyPHYnS0qCb0fa9vHXPc3GJbnmg/g9rF4MlBLekpFj/vNqnESvaVKQmp77z/GtqTFXJ0lJSqieu+0xCdBztzpOjP2hxC1rVGddf+dfvy/dQ5RG6KuOGrFWq7jybeJVSeKKYVzBwqqxKi0tQ6YX1OkfJxyW0GjzS6jFTKdFycUbZvpsohmnefvLocXdPz9Be3ToEdBg2bpTSv/IOwqRjj0erKRPPLWZo2gvNpZoXmWZdNKl4xf5dvRbD+vBxI2fffqM6z7yFxQpMxvihUWYS8u6cN9D4ojjXj9SAbR0izjwQFbi6EaUXzLvKegitLAvbEYJlYQ1qrOqUFRcUZSUX56QWZaee+zettFA3H3X0aN//9o8bXbyTkxNTPSgLcyAUA/RERw9G0hcbMCKUkk3n3p6YjFZmzR9/6UvL/AyCxZlxky/44ZNvNqxeh/4Dwte1R1inSsU+mnyuXjr7ih59zi4TY/jE0qTlo+yb2uGoiWNWLFyGlgX9R05m1ojxozCmaFer7Ph37ID1kLGf1WRb1286tPcAdh+NYOn7WWNBm/fEXDQoN99/B8ZEhqtn7n4UUkKG+Bvxl0ta5uxzSQvToJ1nR6fbsbNlidCAYWf1alZWumriNHPhpRd/O/9LGAxRcHKzc6dcPk3/XiPtE5gALRSZo+kBq4jte5b89BvGXGa9nLR3PGtBo9PnIWGwp3/Hsnb9XTezJJ6gCRj4UCHc//wjw8eNqi4keOrusj1rlAEfHgZ9a6z+PjrF6plwBtMPrniQDNpCo9daSrX+nPk9hj9ttQRX8cvR0tRzx9rGClsSda2Snqa77o6bJs+Y+sNn36xfsQbn8Qeef5SQFlWSGemQdWS4jvGq6lqlTRs8C7H6tT/jZKMVyiAKmJBaSD87IB+1/zDvCPRUS2NhO/93z614F0A71D9VO2Ugo0Nj5SBuguhyWMoDGl9/+IVZECymc5+/NR9XB1wb9YmR6hKpI70Ti15hk5BplsicQ7Ds7bhaXFTEQ6LQYObMjsE7dpW5qf0VgmVqLWKi8qRHbY1c9FodwgVfdIe17dnxr46UNV7y8PHCSoK+BKeT9h38GdExDjI4tau0x9V4SyNOMpRu+3czf+9+8oGz1rqKihcfee6vRcsxEjk5O+NZwmK6jX+vh7ugGbrr8f8q5QFaBIyJibEJF8+cVk9VAZ68rLdftWQl9sfCwiJCyNRHZkyNdMTM+ZCzxvSHIg5mpWfi1Dx+ygUkYJgHNPxy2HdxdcVYE3PiFAOe6gpTk1MwigUG17B8Gi83SinMLwgJr8FCMW7yhF+/+uFIxKEt6zZ279dLs7vVKJIxTuKfzhCOmgQuBcfF6f7w3oNQCtUcuLuhjEQwdUiL4BF1/7OPohh4/8W39m3bPWT0cDW9ZnQHSfR8CKk0iIkx8bAqpVvCnx0CysLDBlUBJcQF0ycv+N9PWFGZ01ch1h6e7jzMKBfxqYcx15EzwlfKX4EprcZkUBlceViEARGsEjdIVfm/Tz/UZ2BflAc4/WD11sx2NeZmqJODRw1DWRh7Mka5oJ2IPErOKNVU/gS00+ktbGxQdLV1c8P6n5WZiV4Qt5u8vDzoRW2Oa4YSrwXzAX99TbOSxKWtS7dePSBYS3787drbrmcmWdnotZD3FpS+WtG8OLs2bZ//2nv9hw1Eoa7/nEMQK8orNI6FbwP+BjyT3pVeibyzvFakp6aDRg2L2LWXybPKHic8krFmuVppFnhCCJYFNqoxquTbc2zqgbXpUdtqzNyz6xCv0CE1XqrnSXcP9yFjhv/8+XeLvlswecYlm9dtZAQlZkzd41M9M9eSQdpgDPT+KJP0ww0MHD5o4Te/7Nq8Ezcjuoz+QwZsXL3u9+9+JVBWz3591O1M4Aj8gzqqfcf2aEfoehj2sGRdfMV0Lf8qO1CcQSOH4vy+dsWaAcMH1bhQX7tl24YtdM1x0XE7N26lM8J9R99WpSVjB20ff+mzMIdhh1ry40LWxCmCRc9F3B1cqr/+8PMrb7wG/vTN/C9rI2pwEQgKfhUQwb5DB6D4YshkOIeakD/T0PEXX7B62V+sBbvi/67W18ToC2PY/ZNRJ3DJZ4QmjNDerbugidffdZNawTcBYZau7PBVAODj4LLg65/tHewumj4FAfDHR53Ve2AfguBjq+KMg5MDSir6d2bPBM7GFoxrrbuHGzQRdyjYM3FA+g7uz4o2AmURTXvoGF2VG/SbecPVOzZsYy0hs3bCsmNRZYDBljrr5tnMzokA8toTcwkhO/u2/0MqvOkP7TvIqlWIl34pakBiKNr0zwaaG4cVVn3qJ+g7eIB/YAc8e1g5wZp5QqKzVGL27f+H/pUBDk6D/xx0nFscnJwglPr3Gm9/5ITRv337C1oNDLjwJzS+iN230j0u9mT0W8+9OuqCMTNmX4UOkpd60fe/Lv7xtwunTcIYnZKQPGz8SNwrjSebCebMA4y3wOplK/GzRC2NolFnY83Kjj5xygSl1RcJx4YP570DkQrpFrp57QZ1CcMCRnk0q/97//MR1MXXO/ZU7PqVa1C6X3zVdFxXScbyWJwmWYhDNzt28oQfP/t61ZIVuHjSIy39eRFvgQrwoV+WRe4LwbLIZjVGpay6TL4n69Tt2Aqr5G5lYxty0W1VTjb0kIkO6+ZQt2z651/GUcZFGMY9Tz6g4q80NLfa0rOePzE+YeqsGfrsisREH1i3cu2/q/8ZNnY4JRKTGs6REBMPsdBUAgyTdz1x34cvvY3/Mj0LtinUGCMvOG2UYVaKa3mVcqkUftlfvf9ZTlYWfsqMplUS6A6tULA7cS+r+jnCsmDnYN+jf6/bH75XadHtHOwwqWAS0u5FvEEjh7DUkQEeDkf/hZlP8yKaOHXSgT0RhJkhkBhaH1wi8MRmwaC6HQ5HWcqSSLkg/Mlr73/z0ReFb37ISiZqgRe/Ilikx+WCxYkY4FDp1Sy8JlOTd7C4IdiWdRvYAIX6Ork4XXv7jZMuu0TlPeuW6zA2YXJd+M3PXGWIemjukyqEFQqSVYtXfP/xVxAURycHTL0Agr7H28ebmTdhOIhzSMWJsT5g2KDbHroLg8XCr39iCQL5EHoKQx6aP0qBoCCDvt86rc8ZLKnV6wfyT7z2HOgdO3IUZxqseLjuAuCVN15LYqC75rYbUIs+defDSEXpUBCMR1ziAePxw+NQ5cnCKyzCfy/9a/WSlSR46MUnzrSR7mlB33P/c48StYGv6xQVFtva2kD0oVY0KPViZSXkzNHRAY44bdZlxm4jJTB/3b08AO3b+V+98tgLWFEx7F5/1y3KnB0fE0/8sJP4xlWUE/fk6ltmo17FiEnDwdF7Dex720P3KG2ilptl7PDY8KjUVjXCs81f8OX8V96DghOwjQ828BjwDLCWpfrSUdMBBG2T0q3++uX3mlRYuh+a8wS8iu9PELlG93jb2uBEO2LCqOtuv4lOj5S6JR1HT9Cf86gzeX76jbkfzXv31cfm8Ojyrt1w981qbbWWp6XuWFHhOur2y/41Ny58mQSfz3js2j4XpqSkpKam8kC0b9/epTJITx33yiXLQyBuy8KTf39RpV4BI2d1Gvd/VU6qw5M5iYVlRTVeqvEkXsN0zagc8GtBe6R5INWYuMpJLwc3P6fTK4G5VJBTfKqs6rpxQjhCm7CXVfGFwthEcASGW6xmOKQzYzty4DDri3GjgVfpF4Sr5sljuCWl0acQSIllj2psxtKEOw46If3E7GOfuvGSq7GJPP/ey9WddUjA8hyK1tbUIAO8ighDSm1DAvyC0ZNRkP7tmemZx49E4VsKw6Crwo+eYUwLBY4bKaqO7KwslCIYxdAFkr+6ynI8rJx4S8CulKiIjSKHVU70jJgXqbLmIoMLGm7m+BvN+/QtfdqhbjTsXwydNP3pPK10WjraCIT1SQPL/gk8mxif6OTk6B/Ukdqp3pxGSUlKQTeAKZb2Cg4N0aoA/njdYW2kvt16d1fEmmAH5AOqDPn+gR0VS6NoVv8RmULXrGfsF4BDy6L30tJUqTVZgSembdSENBCl4zWvZMa4GRcTS9Pk5+ZDFhlisTJziZYCWDIkW5UbvF/HSMrLWXDHY48XC2eI2qCMvHTRLD4gbCy+8whMDFvc/qgp9WUAq4yP5RUcFqKewyriGe8QaXmu8KfBaQ+NVIeAjkp/hsWZiMGwSRWYFwFAFQ9oUmI8Ik6BwZetGK+O9c+ZNqLJaDhs2VWUlPqZ8ADzOtOaNB9cHGUPdm2eGf2HXD99i+9TqeqLQ5kAdO4SzOQtISaO6uTl5UPxeVvxm9T8F3meic9HzFU1Q8bATc8TezKWx8Y/wL9uXX6Dah3mHsiktEG3GCTx6mM7pn/3OFm9OunOuwZflpWVlZSURKft5+fn5qbT4amfEKwzSMj/50MgJ/bQkd/nFWWfsxLK3s1nwB2f2tid/lRClTwaSrCq3N6gw/oQrAZlaJDExA544+mXL7ny0lseuKO22a1BCjJGJr9/9wu6umfffomPexgjf8lTEBAEBIGmIGDiBOus3aEplZR7LRyBiorYzb9Gr/0Gt0bd1+KtrZiRqCoHX3BrbezKwjGps3qo4gjoQChIPt2F9wzhcMyIXTHLxEqbEBv316I/L7x0Mt5jddZVLgoCgoAgIAjUgIAQrBpAkVP6CJTkZUYufj3zxG5O2rl4hF36SG5C1Kl//sehe+e+Pt1rWAyvf3vr3C8uLObzNfiMExCctc36oRxMHxCsXV9/8Dl2xtEXjb/qptnKDGf6YouEgoAgIAiYFAJCsEyqOUxOGHgV7AqOhWQewf1Dpz9s7+rp3ql36sH1+cknQy66Q+ekLb9qCODu+s6384uKinGjMTuCgifBF0u/x3lZf1V2tSrKCUFAEBAEBIG6EBCCVRc6rflaRXlZ9PrvYzf+TNxKjIJBY68PGHEV5kEwsbK27XrJ/akH1zn7dmrNENVdd5zlq3zZt+70JnVV+8ycSUklwggCgoAgYEYICMEyo8ZqPlHxZI/8/dXs2IMU6eDmG3bZo26B50RidPXv6tq+1q++NJ+gUpIgIAgIAoKAIGCSCAjBMslmaVGh0iO3RC17u7QgBym8woaFTn3A1kl9EuNcsSq1WeeekiNBQBAQBAQBQUAQ0CEgBEueg7MIlJeVnFrzZfy2xZwifGjwxFv8BxOmXLyszkIke4KAICAICAKCQH0QEIJVH5RaRZrCjPgjv83LTdR9VszRs0P4jMexA7aKmkslBQFBQBAQBAQBQyMgBMvQiJpnfikH1h5b/r76DI5vz3Fdptxj4+BsnlURqQUBQUAQEAQEgZZHQAhWy7dBy0pQXlJ0/K+Pk/asRAxrW/uQSXe263eRmAVbtlGkdEFAEBAEBAFzR0AIlrm3YJPkz085deS3V/JTo8mFmAuYBQ0becHR1q7ZXOHtrKs8zFZOtg5NQkduFgQEAUFAEDBpBEzaRbjKmGTSQIpwBkWgImn3SnRX5aXFZNuu/+SQC2+3tjMwI/FzPOdLyQaVv2pmBMbUP2VtZRXo4qd/RvYFAUFAEBAELAkB+nlTro4QLFNuHWPJVlaUf3T5+0QKpQAbe6eul9zn02OMMQprke+caxVp2dI1MWRHEBAEBAFBoBUiIASr1TU6XxI88vu8wowEas46wfAZTzh6+rc6FKTCgoAgIAgIAoKAMREQgmVMdE0u7wpiXJ38+8uK8lJE6zB0RufxNxHvyuTEFIEEAUFAEBAEBAEzR0AGVzNvwHqLX1qQHbX07fSordxBZPbQaQ96hQ6t992SUBAQBAQBQUAQEAQagIAQrAaAZb5Js2P2H1n0WnF2KlXgq4J8W5AvDJpvdURyQUAQEAQEAUHAxBEQgmXiDdRU8SoqymM3/hy9/rs2FRVEtwocNStw9Gwra5um5iv3CwKCgCAgCAgCgkDtCAjBqh0b879SnJseufiNrJN7qIq9q2fopY94dO5n/tWSGggCgoAgIAgIAqaOgBAsU2+hRsuXeXxn5JI3S/IyycEjZEDY9IftXDwanVtz3lhaWlpeXm5nR5BSw8c4IeeSkhJra2vyr7tSFRUVO3fuTE1NHTJkiJeXV92J675KVhRKmiqV4iSXbG1tkafuHNLS0nbt2oUYAwcOJOXevXtjY2PHjx/v7GzILxrl5ORs3rzZx8dnwIABdctj8KuqXVS2oGFjY3NeTAwuQ+MyRPLCwsL/Z+884KMqnjieS++9h5AQQu+9S5EiRQQLNlRQrNhRQeWPiAWxoKLYFSsISFOQjlKl9xZ6EtII6b1c8v9eNjwed5eQXO4ul/Duwyfs7dsyM7tv57czs3tqtZrBtbe3vy7Z8fHxBw4ciIiIaNGihd4eaY3hDgwMRAh6C1hCppjSTGBeUgcHBy1SkUlBQQFlHB0dKxcILzsleQUQnSnedzPLCl6QCQLRu7wIoRUWFiITCugtY2aCq9IdownNjJScLyY8H93qzAStySDKiNeE9HWnhG6bdTdHAVh1d+wqpJxDgjGbf724YxElVCrrhv0fatD9TlIVVrCkB5cuXfr6669Zah977DF/f+PfFBoXFzdnzpyWLVuOHTu28gWOFWHevHnbt2//8ccfawiwcnNzP/nkE7QITHl5lV++yoJF+xcuXHjiiScaNmxY+SBQbNq0ad26dQNgsUz/8ccfixYt+vfff40LsBITE+nlpptuMj/AOnfu3BdffCGEgKBYhZs3b37zzTcHBARULpnKnyIrPpXr+MpbqOQpCubw4cOrVq1KSEgAFbm6ujZq1GjkyJGAp0pqHTt27MUXX3z44YclgMVMY8LzEbU2bNjw4Ycffvnll1KBSlqrlUfp6ekrVqw4cuRIZmYmgxUcHHzvvfc2btxYEMNs//XXX3kK1GjQoEElL/Lx48d/+eWX1NRUpnGvXr1GjRpFa7XCUc07ZXPy999/sz/JycnhHUcavERdunSRWj5//vyyZcuA1xkZGbDp7u7eu3fvwYMHg1qkMhaYgOzFixeznWNYeRmZ3qxC0LllyxZmvi7BY8aMYUeqlQ/LP//888mTJ3kZeUeYEh4eHlpl6uXXujqb6+VgGIWpgoxLUctmZcWdoDUi2ZvdPsUtRP9G2SjdGbcRNu7PPfccphrW5fvvv9+4jYvWUAmsg3l5effdd58p2tfbJprmn3/+YSV98MEHpQKo1d27d2PMQDlJmTdsAi3Leo3iwZKBGQDsAuCYP3/+77//DnAxWCyfffbZ2rVr9WoCg9uUKtLsm2++mZ2d7ebmBqjauXMnoLlnz56VAyypukigcW+99dZvv/1WArVNmzYFbYBatEpayFd05PTp09esWePj4wME3Lt3L+oTk+pPP/0k4P67777LBiAkJMTPzw81zCT/4YcfMItq0Y+6RdGC1WCc6qtXr6bAnXfeqVWsTnxlun711VewyaQNCwuDaxJsnATA4inQ6o033mB6gPUZ35iYGPAKn4EDB1oyg9u2bZs0aRJjFBoail1q69atS5cuXbhwYdu2bQFef/31ly7x/fr108pkwrz00kvUBXSycdq0aRPDzf6Bt0arZP37qgCsejWmKVH/nVk5uzg/B658mvWMHPG8raPhysmcouEl5GWeOXMmb12rVq1Yss3ZO+YHFDzrIJYqFxcXra5ZK4XXhgR6AgQgCrBVBQqwFQMqAQ1BUXqra7VW+VeaYjmDfeTAPlivsV1vCwBHPrAgKkKqKIaL08nJCabYYcMjaYiU2wmoQj4Moi+pZSJjj16adTNZzTHtQAywgyX4zz//RO/eddddoiSTBMnAJss0wpEbIMUQoLFAYzwSXDAoTCq8GwiBFrAZiLGjMO0gEKRBYUkaiCItLQ0BUowEHVHF09NTr0zAByAJqvMXpQJ6pnfMNsKHKwhmhtAO1eXTRs41PWKvQu9SDCLhiOnE7uKFF16Q2yYpBjEQDHcSPYJluiCTMdVLpLwvY6WZJP/73/9uu+02DDAQzF7llVdeWbdu3dmzZ9u0aYNYMHgMHToUIxw9MohgR5Tr6NGj5QQwlABfWOaVx3AFF8CRjz76CMABg/KSdSINyN68eTOTYcGCBVijmQlnzpwBYgriMXNiwMb8w+4RkxWzjgLYpJEeaUtmEEs/A3fLLbcwsow75kaG9fvvv4cd9oryPTDTALvs6dOn2RtoccTGA8R5zz33CIjJ+8J7DezGPq1Vsv59VQBWPRlTflLwwsbvE/ZqthTcHdpo4GNBnYeTrCvs8faiZtj8TZ06FauAOQEWi8I777yD6xCNhUJFt+Ejk+QGYSyF7733XnJyMukmTZqgXYKCNHffY8BgP/f888+zeQUQUB2f5uuvvw5AlKpXK8EihUJav349CAOFzVIF4JArWr2t0S8LH5SgpdBbLNnjxo1jWRTgjPTw4cMxy2PLoVnWdJTfM888I/QxOTjm0I4IH9X++OOPg1309mLOTGjACNS+fXsWYqlfSMVGgmdKhOyw4k+ZMkXYRcAfn376KXLjEXIDbcAIxpWXX375xIkTyAR3MO188MEH1AJvfffdd4ydkAbFXn31VeGMBmiiNp566qnY2Fh257QGdhk/frwWOKAp2kTHAHroYsiQIYJIRkp4T8TXHTt24IwGQzBtUK7MasmJJgrwF7/JN998Q0dvvfUWXGPwmDFjBp5fKvLB1EEZZgVjRybFQH40Qhl0OQXAKCITlh999FFi8qSWTZoAi0t9Md/gmikEm3TKKJBo166dgK3gic8//3zXrl1aMmTICHBEjLRDeUSHUWTPnj242JifJiXeFI3zDgJ/WRZAV7DDfgYJiI7g8f3332caEGmAoHhKPvyCXUxBiXHbZF5hfJJ2IB06dOCNYDMAU2RK+XSKt5fhmzx5MjNTiwbeWeYtdkrWHBK8L8BQCt8IAOs6obVaklK+WqYE8lLjDv/4okBXTt7B7cZ9HNR5RB1CV0KqLLWsxWz70ChmkzMmhxEjRmCx57W//fbbWfeffPJJrCasIIIG1DDqDX3Plp1lEfs2SpFiPEW/sjcVGIhdOFHJ6AzAllRXiwtADBFmxDlJH7SjVIaOAJfsDkGZKHXWX/wsbOvZHEtlKkoAGkB+oAq2iRjAsAQA+ERhLPl4LgCIoMa+ffvSCxgOt454unz5ciLeQF133HEHuBAQAI6sqBcz5MMsBBDShCFk48aN4JI+ffqIfuECFMWKD48EebAnBglhCeApSh0ugEpPP/00xiRMiQBlxqh169YMGSqBKnyABShC2OdDy+Sg1GkHxEwV2qEKoWBvv/026GrYsGEgvKSkJMC3rkzQlwcPHmSkOnfurFcsiB1iMKFhfoOkU6dOEdwGgNMqDLDDj4aiGjBgAPQwQBRAVVNdzA1IggBCmihJ+As9oryBwrDMTGvWrBm98OJQmEytxk36FYkx09iWMJfQl9Av4CMCBClK/k1eZ9QqAtR6KfjKuwA+FmRTBjnwlzfRpGSbqHFYZvoRXccsZc7ImWWVIOahR48eTFqBrkxEg4malaOo6OhoFmcYYaTk3bGyzZ07l3eKt0aeT5oJzJgiH56KRyLeVPed0qpYP74qFqw6P47JRzedXT1XXagBJX6tBzQeOpHfb66jXFXdI2YUBsElhIrTFKoadMXyh55gq401CL0uWe9ZNZ599lkWGrbjKDksXmgXQSrLB0snKhDDCbYisBr6huVV70oK6MHoApoRxKPsyZFKAimwebD6YGjBS0WsqIh0IZN+K+GXxe6hhx6CPLHqobToJSoqirAJUQs2gRQCCuDWAUHilmKVJB8ljUcGrYB6g2yUBBirkr5M/WjJkiW4WoALSAbdjJUI2EqnACnisYAXMIJwyOEpwBeASCwdW2rECDphdEhQHWkwQIwpNh4SDI2gHPXPwQKQE+YfgBfDhwOLdjCcSGZLEAymMgANAgHx82FMtcwqaE3q0gKFRcvyv4zsa6+9xmYdpAuGox3ECzrEnKblQKFZ0DwaCCuj3LcotYbOZjbiOAMiAxZpCu7gSGA1ZinTVWJZqmWGBA5BvEUALMKfGQIkzPuCTICevAvCIggZiIh5CNDUIglGULGSRYenOEapKG0MtMpb+FcABEiXWTd79uyVK1cOGjQIYM2gQ7aAjCBO8aaDRTCgCnbglylqZmRssCTB0wLo33333VqN8ILgi3/ggQfY2Gg9YrqyWsIp2xvxiLnBVOGd1SpZL79eg0PrJYf1mCl1UT6/fsNNV6ArazuHJre+0PS2SXUXXZl/pNiN4Qxi4cP0DTohAcLAdESmZEUDD+G4YemEPFw2rCAYGNCgglqqYPhh+eAr+g/4guZDzejlBWVMBDQYTnwwPGCPkUqiqKhLpgAQLNngKshAk0llKkpAPNABqwYr4NGjRynGaigVDg8Pl/wRHM1jpcNExFM0HAm8ZkITwAsgrHYjYDDJgDkQArgKxlFXqHBIZesMtYhXCIccSCUNGiONoBAXkUAoORHaIuAvj7Q+gGNEijQYLB5RTEQZg2Klkjh3BD5AIEAx8rG1SE9FQswWCvDResRX4BeWUbAFgSZYd4jTR82gWRkj3cKV5+B5YbLBrCCY7uCUKoB+ABwwbuLEiZi7mKUVsVx5+wY/RUcycxAU/eKhxuwnvTJabUIzcEork68a2cmkJ9J6S+rWtbQciMdcChbHTsmMBb4TnyRgpVgrpNFhGgDo+bB5wOzKVLE0XvTSQ/jBhAkTeA3Z/onlQirGPk2cbyBUS6yT0iO9CUSBEOroQOvlqJJMxYJViXAs+lHOpfNRS9/LS4mFSmf/8OajX3XyLbdYWDTdlkQcSAjNB0XShps0yweOP3ZdglJUqWSlYBlFq8k5YEGRI5LK1xeQDYuUiN+iERYmTBrSTk54u0B4UvtoaNIiskrK1E2gX7F1AUfwEsKIrksRIAIXoiIsSGs9SJFMyXRPGvoFWNTtxTw53bt3J8idvgiYxfhEQBsmK+KTREye/HQeOANGkB6LNTgVHAO4xN/HMTQWekySkpdKTrlgGSOfJBCgCeMrYJwoKWE4vkqykjdCmkATHiFqRkfamktlyCTNU8J7JYMlqFq3pFSlogSwkkGRkyRKAvQxvv7222/EZmEsAWKCtLDqVdSO0fOxJhKyTbMwS1Q7seocLsOOxesDuIRs0SNCQCtj5dUigHkoXjQULWmeMgS8jNLboVW+rnzF8MwcxtrKB/kAPcWgEBUgOGUBwUwLOx9//DGH6eoEX2z8GF/WGYL/QNVaNLNpYRvAPhOIqfWIr6wnfBhZ4CYLFDls6lhd5cumbq16k6MArLo4lKWJ+1efX/8Nge1QH9hxWKNBj1nbXqP46yJX5qeZXbiwIaEkhA5jEcTMQKYcSEnKWJdCOV7RfVqtHAAB9OBhkWqJHTCqVGggKV8rAQRhpSYGAm8UsIPoUTyA8jIV0S/CUbGcSUoOvSipRnkL5k/DMiqcQYEdTCNYtqBBAqOk0dws02gvAWoBppxRwvSIHIhdA0Lh1dUlW0A0sKzEMkMP6pJDt4pAlbw1BgVnLv47ILKIKZE/xekD/eQDfOVGysrxt7wFKQ38BUEKh6CUKRIYI4keI1yPYwrobDol4r6isdaqa8SvwFOilWfNmkVQGs1i5eUaFAmw4vJD1AyH1hyGToyUGA6BzuhazDyYCfmrFxYbkVpTNyXmLV54XkkcZ0wtJgCzizB/XjSmBIwzcJChGwxuatoMa5+3jB0OWwXeLGz5uhOM1YawM4zNACndLnibYB9pSGZgXlKKGbDZ0G3c8nMUF6Hlj9E1FKoLcjBcnV39OejKxsG52e2vNh76tIKurpFRlb8AR4jMRQFwBgotzlLCtaLETERGRgqPTJVbMkJBsALbd8wS6CQ0DToVrYkRS27T0tsNah4lh7riL7CDC4r0FtPNRO2x9uFSZMnDmEf8OwqvIv+mbnVT5LDTRSfh32QUsM0AMYFZ4E60EVtnDhWiuQEcICROG+BewSwEGazd4EJ0G+wQD8SAUhEZAmgwINEgX6nFh5GFa7QFFgW+8ogIJ8C0FIBVRaZQM5xIoHHQLTeZgRKgHHpQoswiRg0vJzZFhgYaoJ8umGBaIIO+yGGmIXP4gmDqahGAN5O6jAs8YvIEYorBQqUJljkfSnQ8tZgw5hk76MRiwRhBLR+2BLw+ZIp7vDgsglgogDQYJny4SECEl1EYRUusIXQiQAKw+EvsDhOPAQKqMoHxoWtJoE58ZSIx1owOo0waYw9vMeAYjuAR4AsXnIaBfcTCVOE95a/ls8akIqATwzAWZXAhrDHuzHbeHUE8BTAeY6GUbnET+bwIhPaLYsSZkQB/s5mBcaYEC69WecsXhWEUKhYsw+RWO7Wy46O4RDQ/PZHuXYObNRs92dFTEwKsfAyTAOqNwExWfGwAXNWDYmCVZz+NkhZqz7BmDatFLDBnBnGKcYcCYAu9hasF7w+7xsobZP3iHDj6nv0x2hcvoa5HSW8LbC5ZN1lA6Rdogv5GI8otLnprmTST+xhBPyzHaFwwB+iKg98Cl2CREqSSiRoD1nCkQIT/E+TE8OFyYlsMXmQcCeGHO3hByeGi4uoNZPLII4+wrOPsQFYIGUiKwmDd53woQXjV5QuHCCQBsHBHCkQOUAD0cBqfISAWB6my9eeMOnMJglGoeFi0LDSwBqSgDOYBLAGgJcLI5JQAsLg5ghgX8mEH9Qx3RPDgjxMsgxdhGS2OkjPAQibvq4pp4BGSZMLwpoBlYZkzkghQnAMg4I/rQxEC+dDDMGFYFacjgR0MBMY/hMZeAihGgL+4FYmB4FgGPjUGsYpkWFQx5irXZMA7iIr3CHTFiHPEQVhDGRqeEqHFIDLEzAemCvxaFAt6ieE4LZ56xhGrMAdKRBnGnXVDbE0J2Ac2sQSJl1RqBNstR6rZLuIW5E1hD8DuiPhIJgxTAoEAr6XC9TihAKw6MrilpXG7l0VvmldaogmgDul+R1i/h7jvqo5QXz0yAQqsU3InXfXqV1qapY3nLHxiRWBBB12xCUO1oxIIo+beF8l8DSXs2NhvSU3iAUFno8/IwaxC5AEKQ3rKIwwtWmsNTylPRVSjXAVSDKyA3hXt8whNz1kqDFfcUMAjYJN0eA0rCDtIgJfoC/1ER6I1jhCydaYWoARoyL3wnGqUjiaxutGURBI0QImk5nHuUBiFx/6bo0+oRuJzWUAljsyWgEER3sF6jbggG7644lwEokEGRibOPIJFsF2BlrAHgD7FJOER+oy78nHKgHUoxmE9WKYuCz1YB4MKaaHtOHmHqmO4ORMAxiI0nrgZMaAUgAYyJa6pRY5egdA+7jmABZLHAQT0IfgGeQp0C+7hfCLHM+mFcYE77uISgyLalHoBJlIARMJJRkafrilGp8LhAmGAErQU4VZoLN4LwA0TRty4IVhG1REuDV/SKEv0myLBrMM1icZF2uhLpiK4AQ0qGIcGkCUTjNtMMFcwpVHGsCz44s1CmKIkUAOuQSEgRV4c0Kc0201Btknb5MXkbB1wBOsOcxIcT0iccAXSL6OPiBgyYDGjzFRhcClDsKCFA0qWC8EFqJqPkCFLqEgzb8HWWJHZz2iJF1SNEUvEtjJh2BqByJnDWDrZ0yINvf5ErUbqwVf95zskxhYd3TRuybt8/W705PvaDkIDsbFmArE68KpLxZSESSVQlJt5+q+P0s7soRdbJ/emIyd5RV7HqmFSeupE4wXZxQ6u1wBQlAGmEVQR+pWXnBNYcoXEU1YNAVlqnUE2wdXFl/hfwAcCKFSXfovi/brEM4gSPpYXhguEoFduyJOR1RIOw02OfA7IW6tWWugbAeC0KqJRIBhFVXlHlIF+imlVl3/V5aISluUVTZSGaz56BU6PeicVLCAlLUHBu4W8dzUX1HVfQ+aDmKWVz4eaU1K7LTD6YtrLySAT9rVGX16gDqU3nN078tcpEDxryJNPdRkFsMZrz/sLppRvua/RQHWIvRuH1IyYI6eWv1+YpblIxqNhm6ajXrF3K79Q5MYRQs05xS7Chd1sqohh5z3HNKK1wPHVclb5ipRWJXKoXDdXUpFHFsV75aTytKJhgouK5KY334gLfSVNgeH09q7FZkVMyYvptlMJy/KKJkrDdSWM651UuixAW1V4NxELRm/2uq8h8+FGMN4w+rqiILOSCWP0sbCEBhWAZQmjoJ8G4P7FbQtits5nM4gODO19X2ife/mxOP2lldxKJcC6hueFE8JY5nGyYMGutLjyUJGAIgFFAooEFAnUSAIKwKqR+ExXGZPVqRUfZEQfpgt7V28MVx5hCiYwXN6ErWDBInqACFN5TJXhLSo1FQkoElAkoEhAkUDFElAAVsWyqb0naWf3nf7zA0KvIMGrcecmIyfZOZv1h8Zqj3VT9Yx1GmjFx1QdKO0qElAkoEhAkYAiAZkEFIAlE4YFJEtLiqP/+Tlu5x/QorK2Ces/LqTb7fgHLYA0hQRFAooEFAkoElAkoEigqhJQAFZVJWWGclxwdWr5rKw4zf0oDh4BzUZPcQvRXGCtfBQJKBJQJKBIQJGAIoG6JQEFYFnKeKWc3H565Sdc1A5BPi16Rw57ztZRuQjDUkZHoUORgCIBRQKKBBQJVEsCCsCqlrhMUpgfvTm/4dvEfato3drGrtHgxwM7DsVDaJLOlEYVCSgSUCSgSECRgCIB00tAAViml3GlPeSlxPLbgjmXzlPKyacBbkGXgIhKaygPFQkoElAkoEhAkYAiAUuXgAKwanOELh3ecG7NF+oizY+3+LcdGDHkSRt7p9okSOlbkYAiAUUCigQUCSgSMIYEFIBlDClWvw11Yd65NXMvHdlEVRs7x4ihT/u3GVD9ZpQaigQUCSgSUCSgSECRgCVKQAFYtTAqOUnnopbOzEuNo28cgrgFcQ7WAh2m77JAXVhSWmL6fjQ92Frb2llfnc+lVlZ5xRrToPJR3FzyDAAAQABJREFUJKBIQJGAIoF6KQFHW0dLjla+qpDqpfQtj6nShH2rLqz/tkRdBG1BnUeE3zzB2tbe8ug0DkWX8tLy1YXGaet6rXg5uPk6ekql+MHBiznJ0lcrgF5GkRWwS/lUVwI2Kmt3O+XQRXXFVn/Kl1qVZBRamWKjpEyt+jNLaoeTxu4hlvzzcQrAMt+0KM7PObPqE65joEuuYIgc/rxP817m6742elKXlqrNZcEq4Rcbr/mUda0uLfw3ufhYZkl8XmmhKVTENV3W1y8qFxubBs52Xb1t23sqSKu+jrI2XyWlhdtTig9nlFzMLS0w1bujmVqhzradvew6eClTS3sIlO91XAIKwDLTAGbFnYxa9l5BxiX6cwtp3mz0ZK4SNVPfN2o3gKq8+TEl8fks3Nb+jjZBjiobSzYnW+g4oVxL4vKKo7L4Z3sw3fGuBipXZd2w0MEyFlklyQX582PU0bk0aO3nYBPsqLI1/s/Ml0+tk1nF/DuQ7jgmVOWmTC1jjaHSTu1LQJnNph+D0tK4nUui//2ptERNZw163NWw3wMqWbSQ6Sm4EXsoysjPnXu2NE9t183b4dZglbPNjSgF4/Fccqkgf2Fs8ZGMvIwi52cjrawVqGo84VpYS7w1mncns8i2nYfj7Q1MDXo0YI6pdSwz79tzzs81sVJ2QRY2HxRyDJaA8TclBpNSLysW5aQf+33ahU0/gK74weaW97wVNmC8gq5MPtalVvG/H0NPOIwKdrw7VEFXNRe4tb+D88TGtu081TG5hZtkwW01b1ppwcIkULAsDnRlPzDA6aFwU6MrWMdC5jwx0raDp/piXuFGjY1f+SgSqB8SUACWCccx48Khg989nX5uH314hLVtP+Fzr8adTNif0vQVCWSfSc06nmwT6Wrfx+9KnvJ/jSVgrXK8MwSNW7Au0arIVEE5NaZSaaBGEsCxXrQ3zTrEyWGIGWMYVFaOdzRQudsVrE9iX1QjBpTKigQsRgIKwDLJUGCvitn8y9HfXivMTrVSqRr2faDV/e/au/mYpDOlUR0JZJ9NI8+uu48SNqsjmxplqFxsbdt6WhWXqolsUz71UQLFxzNhy76/n5lddZiZ7Xv6WKlL1aey6qNcFZ5uRAkoMVjGH/XCzMtRK97PjDlK04CqZqMmuzdsbfxulBYrlkBOdDoPbUKVa/ErlpGhT5AqV4yoY3NtwpwNbUOpZ7kSKEnR3KtiE1IL7w5mM7ouuWymi10sdwwUyuqLBBQLlpFHMu3M7gPfPS3QlXeTru0nzFXQVdVFXFxUnJeblxiXkJOVU1xcXPWKWiWLszRrtLWnnVY+X0tKSvLz8gsLa38R56augvyCgnzjm4KOHjg8fvg9H0+fpcs+OccPHR076I7P3/kYAvQWqDxTSLU0x/DR0dt+2bjk5eeV/cvPLywo1EwAQwjU27ypMiEbUjPSMhIuxudkZxcVFl5Xqru27Li3/6hfv5xXEU3JiZdWLFjCi1BRAZPmi9tMVA7XORQC48ze9NS0jLT0goKC0pIKh4qS8BIfezEvN7dEXZlnWeWg0Ud19DqV4qKi8tmbl4dk+CqfCUWFV5+KYqZ48U0xMeCC1TIrMyspPpGVk9GU98KKnZOdk5WRyczXeiQvxouMBJgqqckplrD2XkObKb/UmgVLXVSArpNY47JNlc11XmmpsGUmStXFF/6ZF79rGeQRxh4+YHxwt1EkLZNaS6OK9/PQngNrlq2KOnoiMy3D0dmpU4/O9z0+rkFYqOGkqvQI/8Lpc9OemdKxR+enX3vR3qE2r3i9fCn5g9ffQTd/+utXjk6OhrOpU7O0TKVVtJChC1F4FT3VaUwnQ59UdQpVO+PE4WNvT5omqjk4Orh7egQ3DOl9c9/eA/tWuy1ZhfjYONb01h3byvKMlkxLSWXG7vx3e+y5aLVabWdvH9miyUNPT2jRtlUlfZSUlObm5qJvRBlm/tEDRyKbN3HzcBc5R/Yf+uWLH6C5cbMmlbRTi49QqysXL1+zdOWl+CRCIIIaBI24e/Tg24ba6KzhOVnZi39csHnNptTLKZ4+Xn0G9bvnkbGu7m61SLwpugaFLPzht5WLVtC4SqXy8PIMCA7s2L3TwJFDnV2cEdc3H83dtmGzvGv/oABefHmOBaYzMzK3rN20ec3G6LMXQI2+/n6aEXz0AbFenT4etWje/GP7DxcWFjVu3qTPoL633D7C1lYPqDi87+CC7345eeiYja1toyYR9z76YPtuHa2t6799R48szDPMp/76PPXERnlfdq5+Dh5BPs17Bra/mXs45Y8sP52fnsg1V9nxpyDV0TOQX79xDW5q+WRbDoW5uXm8q6mXLo97egKgauOq9ZtWrU9JTp3x2UwHR2OCD+4jzc3JYbGodd5ZlNkR5uVorhpSPoDC3Oyc/sMGdbupR2ZGxunjp7Zv2Hzgv70+/n4t2rY0TD6Ant+/+yX2fMzHP39hWAuV1GL4vvlw7q7NO0LCQ5+ZOsk/OCD2XMzGVevQrJXU0n105uRpbI2vvT+9eZtyNnv279O0ZbPABsG6hS0kJ+rYyV+//JFdysvvTFUXF8+b8828T78GEYaGN9SicNn8P/76fdnNIwYPHzPqn9UbVi1arlaXPDbpKVCIVsm6/hWQwQS+/cG7ARDsFv77Zxs7xtycvDEP3wdrhQUFPL3/iXHBoSGCU3YRls9yXHTs4nkLIppHvvLuVJW19dJfFi2f/4e7t8ftY8ewQ/jt6x+P7D301KvPBzUI3vDX2p8+/943wK97X+3bs0Fps6bMcPP0mPbJO1i5vpj56bez5772wZu6s8XyBVJdCmsNYOkSWpSdzL/suMOxW39u8+CHrgHhumUsM+fyia1nVn2qLtBoSt+WN0UOe8bGoY4BxKoINjc5GiudS2CEKcxyHp4ez06d5OXr4+KqER1q9diBIymXktNT06ursarCi7wMapj9GQZwrPpsK1kf7R00ax8a9PzpczlZWU1btbh4IYYCaAW0aUjDBmKnzmKRculyQlw8NhJyoDOscSOxbvIIA1XMuejsjCwvX28fP1+/AD+H65mpoAQ0kBgXz+IVEBIU1jjcoYwSiDm890BZ447nT53F29KpVzdPL0+MH2XlEygQGBLUsHG4fPtoa2OLsyn2fDT2KtR/o8jGtnZ63ndA3snDxxydnBo3j8QGAw0XL8ReSkjMy8nzDfQLbRTmZkZ7Q3iTRj3694adIaOGNwhviNo+deyEBLBwSDEQqZdTnV1dUFSwLG2CGYgLZ85nZWZiPGCf7e3nwyb7xKFjALXC/PwDO/fSZpNWzVzd3BhWTTvRsWmXU11cXYNCg6V2sOodP3AEMdIsU4ICjF1E08aSbYlGpM+GlWt3bNra9aYeL0yfjJWC/Fbt2wwZPUyCDggW4V9KSGJuBDYIQp2wfZeqiwR2nY0r16J6o46cAGpjt8MSkJ2VxcDBghhNCIY7THGQzWviG+jPTONRSnJK9JnzmekZHl4evgH+lBfvjlYXpviK3mXu3TXuvsbNIml/1P13vvvy9EvxiVoqE4J3/bsDwu546B5ovn3sXbu37Di4a9/lpGS/QH9TEFbrbTJXu/bpcdPg/v1uufn1J186su/g8DG3OTmVB7S179qpaatmtU5k1Qlo1rrF1NlvMcriRWMXdPbk6f079oy6706WiAM79w0ZPRz0TIONmjZOik/4dMaHndd2k69CPMJ0hxvxrvH3deimOUR/z4SxX7736ZG9B7VmS9WpqkMltV9485Pe4p53bewc8jOSs+KiMi4czE85X1KYe3LJzA6PziHf/PRUq8eS4sLz675OPLCaWng5IwY/EdBhiCnwR7WoMlHhgoyk4wun87vUfq36+rbq5+RdvhUzVncoVKkpnHeggaJCazt7PXFUUrGaJ9CC8z77dvfmHelp6bY2NvaODm06tXvspYnevj6ApIXf/Xpw974BIwbv2Li1LMKmCLvCI88/0bVPd7om+Ob9V9+KOR/j4++DCgSW3TSk/7hnHrWzszt17OR3s78En6H8iDxAu7DXB7pVQjDafcX8JbhdIImubW1tet3cF0rE0jZz8psPPf1ozNkL/67ZiD6e/fNcdw/3X776ccuaTShmOwc7W1s7Vrq7Hxkr+T2TEhI/mjbz/KlzRHu4ebqPvPv2UWPvhDY5DSC5JT8vXDxvPstfo2aN+frXwmV///Enzi+K2dnZt2zfauJrL/r41cIB2OxMzWkyaVacOXlq3pxvTx87iYsNKAwwGvPw/f2HDqQMcOT9198+e+I0eCg3JxfoOf65x4JCQ+a8/VFSXAKI551XplNsxpz3WrZvfeHMOSxPZ06cQshkgq5op++QAaQBK9Ofe43hxuUXeyEmPzcPcXXv3+vFN6dIsIlifLCArvjtD/DQbffeIdCVyJeK0Th2nR2btiBSMp1cnCk5YsxtWhgLv9LmNf9Q5qe531vbWHfs3vnVWW/s2777i/c+/XDe501aaqzgxw8e/f6Tr6LPnsfTxOCi817/8E0m1awpb6Ht8LvBMpMBlnWNB4Iqo/9t3qaFtY3Nnm07I5o1JlSOhIe3Z0QZ2JL3xUsBWAT2gXrJxzPo7uFxMTomMT6hvgIsiX1eeWtrGwxXzFWrKwBLelpXEiw+TVpcdcU4u3CK2JZpz5ROuKjZ17Xr0kHwwsYSjHV0/+HLSZcCQ64xvu7dtot1lR2jKBneJIJdHKEadUUINaGz9gGWe4Omtg7OHlYtAtrcVKpWH10wPTN6X0FabM6lGPcQPSEI/ExyYXaGg6uXiWK21IX5RblZDm7e120/93JM1NKZ2HUYACff0OajX3X2D6/JYFh4XUdPzRuSl3IxZstv/HMNjPQFabW8ycHd+HdNnTt1NiUpuU2XDp7eXqYTC7aBLev/WbPkr54D+jw55Tl7e/uF3/+67NfFRP+MfWK86Be4Q6jBe99+7OXjtWrxnz/P/X7z2o0dundC9WIjufexB8MiI8AfoJkZz0/dvmELKCeiaeS+HbuphSJkO0sE6PnTZ7GiV84I5f9csBTzyaQZUzAa/frVj+CtVh3aEPQgKn7/8ZeopeemvYQJzS8wAB/En/OXDL3z1ocmTsjPz5/z1odrl//doXtnKd4IlPDoS0/3u2UAxphpT09et+Lvbn17NowIk8gg4hi4tvy3xYNG3sK2EkPL6RNReAHQ2V9+Nc/H33fTqnXff/zVF+998tqs6Ta25giRxDRyYNc+sCwWHQJ3ILht5/YQzEgt/XnRiYNHX5wxpXu/XsCL9ybPmDPjw+atW4K0tm7YfPpYFA4IAAogKepYFFrB09tz2uy335r0Pxsb6y8W/SC4Bg18MWtO3IXY1z+c0aZju4SLcW+//AZj2qV3d4GT6OifVevveezBt7/4ABvk3JmfbFn7z7A7R2qFVWGb4R+GSfSoJE954p+/N6xdtgqpjh57V1Zm9qxX3yJuvXPvboydvNjjLz2dkZK2f+fe6XNmtmyn56xxQV7+pzM+IDx86oczWrZvg5GAnYCTszOxX4D41z6YzgSD5ROHjzdr3VzesknTIWGhtz9w15Kffj9x+CgvSFz0xYefe8zTS/tVJdSMTQiFRcgO2hpn09mo0wI6m5TC2mqcUH+wNVD4bNQZYISbh4fgXdDDVoehFGkWENtrdzu1RXMV++XVOLh7P7s7VksAlruXBmYB8TE5M7JMg6S4RJqKj42XA6yioiLi8LDEe/t6i44Cy14ZYk+r2G+dLlb7AEsuPjANOhuARWZucqwcYJWWlsTvW3fpwOrc5LNWpSVEkTsHNA3pcadfi27CYpR0ZMv5tZ9TsemoV70jy2E1X08u+zj97H8kQnreF9qTqPPyT8z2pfH//c6Xdg9/6uQdBG6L37s2cc+Kgow4MlU29q4hbdwatPAMa+UV0e5KJen/0qRD68+t/bKEUH0rq4B2gxsNecLGzpihQlJPlpNw8AyQE5OdeIZ/FzZ+7x7a2q91P5/mve2cy6N05cUMSCcnJc//5icPH6/xzz4q7DcGNFKVKtgh9mzdyTKBQwobAFXwZaxbvvrIvkMsCvihyAFYDLr1liD2ZCorgMhvX/2YnpKmOQxVZgnq2KML6w7rpqOjY0hYAzZwmemaa4S8fLypSIBOQLDG09e289UJWRFhB3fuQ1OOvGc0frr8/AK2hkShbfxrrQSwyEfLBpdpaJYtgKC7pzvIgDTY6Obhg7F8YOaRABYmnA5dNZGkWM4GjBi0/Nc/WA0lgEUIzPo/V//0+Xc3jxgy4cUnaQHCdm3+Dzj43LSXcZXytffAfts2bCHMIub8hUZNGldEuRHzt6z9d/eWnWV6KA9Obxk93MZaQxhohljy1p3biZh3kM2t94z+/J3Zfy/5E4Nig7AGjAIxW8BxpN2lV9eKSOIIxakjJ/DggK4YIMxjjzz7+NsvTSM8aPidI0Wtxi2ajhl3L7MCMISFjBherFlaAIuZgyGN6EDhTdbqDosUoA0ZMjqE5rC5H3rHiE/f/OBc1BktgKVVUffrgd378U2Puv8uvEsqa1XDiHIzL65bWAZk4w8Ni2xE4JpuXdPlMFt63XzThj/XHt13uNSqlOgxQZ5WjwV52G+K5Z4g7IVALs4Ia5WsN183r954bN+hpISkU0dPWlurBt02FOe7urj86tRvPvwccCyYHXnv7TU8wGFmoe3dvotNWp/B/YShlJkcFhlO6BVvik+A35njUSw+kARulBOGAQ+gid1LLKc8wpDJi8MmSl6svqavkYVFMHnl6LiDu69Ej7og7/jidwXwEpmlJcU5CcdPLZ2R1m54k+FPqlTW7g2aqQs0Y5Z+4bAEsEqKCtNObSkp1sCg1FM75QAr7fRuytu7Bzl5swctPb3qy8tH1ojGQVel6sKsmH38U6ke0AFYpWdWfpp0aB2FbeydGg97xq9VP1Gx3v0tRYDF+dll/7KK87KJLVMXaC+OmbFH+QfcDO5yW/jAR2roIQW+vPHMZFQUYZX+gddAOqOLl+PlWWV4CLuRaNzVzbVxi0gCm9CgYkVgaQhqGCIOg2Ibd3F3hTZ0G+VZN7du+HflouVEn6BuMTbg1mQ14RFWFkJcN65ct+OfbRyuwQmFIhRdVPQ3/mI8j+a89RHrMgligfH9XUpMwnWIaY2cZm1aCHRFGhWFGSArI+ujqe/iWhLl+UtcDn/FB2rxDIo0ph0AFiaZKw+tLpw9z34U19Xwu0ZKMROx5y8AyNp0aiuKOTk7se8sKVHjgzMPwLr9wTHD7ri1uFgddyFm5eIVs159+4nJz4ByYi/EIlg5TkVVQx5qDIMBdrv+wwYCkv77d3uPfr3GPvkw5kaJU3kiPkazfUKMQmiadFgDBvrk4eMSwAoND0VniFp+gZpRy8/NF1+lv3SNoFAeei8TASjjGgOqcl5VGk3qEo8ltVDFBDFneBXB7qAreRXCWW6+dQjqHBDftW+PcRMfxe4oL2DSdOLF+NnT3gOhvvHpuzHnLvzwydfvv/4O5jScs/J+NY5+Wxv2S1Im8XNMNrlRR3pUPxLbN26BEUxTGF/vnTAW6500l8jHiebtV67XTGqbN7owWSs48tyiXWv2MyKUE4vvYy89jZ+aGAPehW79eoLyVy9Zyd5S3juzF28yLy8mLpGP5x3PqXGPLsl7tKi0ZQEsLkBPPrYZAVnbOXk0vGrxjt35p0BX3i0GhPa808HdJy8t8cLGeVmxB5MPreJXaALa9HHy8nf0bpifGpN+joDWh4SUMy5Gga4cvELxORI+j+/PzllzQrg4Pyc7/ggJr6Y9AQQFmSkCXbk36tr01mfxP+alJ2VePJURfTSw/UDRlPQ3Pz1JoCuXwMbNRr/q5H0d149U0TISQMd8DWDKyxLISZ2fU46fNJkCS139S1R7lchWqYK7jW5409gaoitifr+cNQd99sSUZyNlvv8q0VD9QqwLIibGwVGDYMRHgKcr32BIJfCNyJGWS3APIUHrlq/C1NRv6MCwiLC/Fq04sueAKEYI1+SZ/9u9defaZSv/Xb3x8N6DxNYQpX61Wd1UGWi7e8JYeZgU8SvChENxV1dXWSVNaaz0I8aMkh96b9goTCoD8iAoVXwVsE8inkzsIvjRcC39tXD5Ey8/IwCHg5MTSlGyyiAKeRWpZdMlMPaIiHIQkr2TI7iHLfJNg/o7lZ0PcHYuDxYWBCABdDzuQyT2zOuTeg/qt3LhMow6eAxf/+BNKTpETq04ggCP1/ClkSX/yj+ijPiiquCaFTcPN9QMx6My09NxEF+pWv6/mEIEnQwZNUx+soEAdq2S1/0qLo66BluV1cGGNHHKc70G9OGM3p4tO7et2/z6RzNEEPF126x5gT8XLgM+vv/9HDyk7bt2bNw0csaL/9uwYs2d4+6RN44OZi4lxcVjtULmiAUbKuE4Lm7ymSyvUefTz73xcudeXTlLwdqiy8yIMaPrVpC7YIEowK8/+JzYqaemPMe2TWTyBnGq49sVvxDLwT4Nlj9/92Ou1/G8FmDxbjINQFTsnEVFzHvMBN4gXfnUv5zaB1g5ybE41woykjNijqWf3ZN3WRP7FtBxJDHjQtwFWanxO34j7eAZ0nz0ixirSIOTWt87fe/cCUU5l6M3fuvbvCsR8V5NeiTsislLPluYnWbvqtnPpZ3TKDzfVgPSTu3IvXQ6Pea4X3NcilYZsVGsyyS8IjS+G/AWf/m4+EcQfUXCySuQf4SFlWVf88fRI4CfvlHZ2AZ3HWVtU+Youua52b+UlhYX5GKNuxYeaQxOAkLBHQl1vkBUOaBY45JItHuTkS+6hbSoYbME1nw8/f3U5MvYrrDWXKMCa9h0BdU53SMiAxJi4wWe47TLqWNRODXQB6ISuk1XvfEoLSXtyN4DRO9OfO0FPFagmaW/Lpb3wwrbnRCiTu32/rf7o6kzuV6ycoAljuU3bdmcCGJ5O3rTLGeYAVi2ME1VpLZRgSAAaKOF/f+x6+Bs5lWrMD4ylAF3FP29+E+WTuxGFKB3jCKEgRNGxlduRMQkBgqVVyTfPB/hXGA+EB4QHtmIZZrIdKlrbqPFwgfl7I/JBGl17tmVFR+b4tx3PuZ8n8ZVWoaPMDRKSFHwhSWJ8RIqMD6GCzDzmrS8up2rYMClnjUJ9t99b7mZGDjwXHhkhNZcJeKbwxnEfvUc0Ns/KPCamrpfyqxlkhdJ6zkRZtyDwBFCiQWpAHuDTrDcoQ2ntD57e/bW9f9yPkMyRkrFTJHAbEYUoITsQyPCOCq4f+ceLYClOdjo5oKTFHuet4MP06ns5KZLrUwnU8hBt01M4ATy6+bX3RxuLca7jRt64qsv6BqGCa4SZnUu2uV8KOZwraOsvBpErB7avT856ZIQAoegSQQ1MPIZKcuUcO0DrKM/vSAXjbWtQ6Nbngts11fKzE48j0OQrx7hnQS6Eo84YBbQcfjFrT+BsfJSE7jWwbNR+4RdC3kKfvJr0Z1dKbhKUzG0eUlhngZgnTtQDrCiNeYr7gMVdjIX/1BH77D81OjEPYu57SO481CMZJoCej8qVWjve/U+MVYmGuWKYekKSMLgVJCjvoqZyL8CofDZlYFFA3tXqWwdXW0dXGydXG0d3TTpsn82mq/a/+J2Lb24XSPhKx8MV6PC+j0koeEr+dX+H6/KR/+bGXXk+NinHgY6cP5cNIEpCDtNtZurWgWMEHiX/vt3G5e7ENXOZmvN8lV4+tDN191k26CfNU6iYrQ1Wu3YgcMXz8dI3R4/eISn2DCwNOBOYpXhAI70VG8CfLB+xeqv3p/z/BuvoJlKitUsSQRwhDZqqFseyu9++H4kBuXcbImNDZcijjzfAF8kJspzjvrgrv1EiXGuh6sC/YMDI5s3lZpi08lSeMcDYwiu//r9z7DAEUPdsl0rqrMTfeGNV1CfVOdp87Ytwyu3vUmN1jiBx5aVGoPH2ZOnCIbDDcrFByIWuGvfntgCiRMnHIoCRHmzGtwyegR9EiTOQs8xAmCNPYHDKgCQAzInMI65hIuKEHi/IH+GALzSumM7wrnwJKIzCJjjJCbOtQHDB1WLdhq/d8IDoKtFP8wHnxGcx40PJDjNAORl8jw2aSJiXP7bkjseupt5hQUx8WICPQIT5R0xSfAd43Q+uv8QA81XrSsh2nfrxEHUzWs3YRcBgnO6k0s0CII5fugIxqHgBiEahss8yA5aZjl5N8ZOt+7UlsOPHEcA0bJYcUyMUes9SLNoY4TmfAbmQwLdmEtAwL//+GvLun/7Du6/7789XNDAuVTpLihj06W0Z2QJ8PqXBSHYsgHL4Nb+VI0Vis0M2wZeMQLe8ZGzUhGjOXfmp+TcevftvBqU2bxu0/EDR1mamPAc0V3w7S9sALCw4lJf8vMi3KPtumpMG/X+U/sAS0vE4YOfDmzXT56Zn5YovrqHau/sHb3K3XN5qYkALI/QZgS/g8Yyoo8AsPJSk/AYUtctOJKjhwm7rTR4a+jjOH3Sz2o29O5hnTjAWNa4KrTvA2dXflhSlB//33xQml+74Q16jMKIJbqu+V+oEpYkDEsaa5OuP67cZ1dmbdKJc6oWASieMrTkanMVMLlo0NK1EKq8jL0zAqli+9yhKpV09ApqcuuL7qGtpJyaJLCanDoeReTT97O/lLfz8HOP33bfHfKcmqbLwKjEcN8h/fPy8pb+vPDVx19EkWempROXit8NYCTcahV1h1buNbDvoh9+e//VtzF3Ozo7Dh41jHZE+UN7D/4xbwE7deJ7EmLjUJOc9tJuChMq/658MKHd//hDS35ZNHXiywSfcfaeW50mvTlFL8CiEkEe9z3+ELcqvDz+WUwmRDYUq4unzJwmASx6XL3kL65gwI4FELxnwgPcuH2lt/L/MfgDFN58/jWuCZj87v8wFD38/OO/ffPTq49PwvaAvQHKJ7zwpHCkatU1xdc/fvqdf6Jlbg4b/cBdd40r38zc/9hD3Gg1Z8ZHAA5+uIODlk9OeVbE7HNXJyfaOKYAOsHYw3E8zEuAFcTChWF//LiAs4Qs9I+8wP0aPV54c/J3s794+6U3cO0B66kCgxgeqssO0O2lt14FYHH2k4stwKMcjKA1ABxQGgLAHFztvXPLDghjNAFCb8x5Vwtg0elNQwbs3LydQBYMUcSwc6uWnBLYfOHNKdz4MHXiK0S3cC0cY0TsPL62P35aSHfcjAXLWHw5rMCkldc1Xfr+Rx/KTMsE3+Mi5DXhfmDeo5F3j6ZHQrI4mVGYX0AEN/SMHjuGAwq/fvHDqsUruLUBGxtvtHnMbKZj/8Zpec+2XYTNwe+bz78ucc1lKLjgMZyv+H0pewzORTItW7VvTaQpR3dFsQ1/rjm85+CIu0c5uzQETnH2mUC9Fx58kttkmDD3P/agsCVLbdbXhArLcyW8LTq6adySdynw3ejJ97UdlJycfPnyZbbLgYGBLtfbkVfSLI9OLP1I3OTeaeJPNg5OHGw9/OOkwsxEB4+QDo99xn1EUvUL/y6I2/4LX9s+/LlbUISUTyLlzP6TC6eSCB/8TEiXoSSOLpiRcW4nwVidnvyKU4fn13ziEtii/SMfFeZk7PlEs1K3f/QrOxcPkQ4b+FSDbpodsPgUZKXFbPn90sG/yr+rVP7tRzYe8ghxOleKXPM/8UmVRC+pr4VQ6sK8aypX8wuQSeChq1alcguTxuZkozE1CQhV9lUjPQlCVLOnSotnRB8++usUigR1uS2s/0PXPTh5ISsxX11QaZPlD9kMoZB0ZyM3jurapfU26O3g7u/kJR5Fffhf5vFkt/fbWtlqywFX3XtTZvAbLM9Pf0UoJDolABPFgLrF3YPeFV4n8gnm5ag5dgLsPaLlc6fOsEY0CA9Ff+NmAjxxxAw3HDngMxrh2CDamo1aXk5O9NloYp0DAv1DG4VjadAim4sx33pxKhiLOAZa42kZJXmYKFCZQB9UKS5I8YjD7Zw/0tr6Ux6owaUDKZcv4zTUXInp7oYJViPMuHhOPpLmjga+RjSN8PDyEoHSuEETL8a5uLkRJy46jYu5WJCX5xfg7+7lSZvcIQkBxNeHhodxNTMGGDnl6tPZuV+etR8S4DDkKtqWFzAsDTphAoi6bIKhxN3DDduMYF/kI1VsWsAp2OS6f8Cr2C6TD48MBLocOxZkS9JmNee2T+4RAABx2E3EV1E+Jyvr9InTQB8OEgoTI10QV8dNY6AW6fIFmkUUGBQl2KrFHciVIcbgSt2wiHAgHbY0QRXTA4McVOH7pk1GB8sWj8C7nIpA6yBbWkPg2VnZ3PVKxDw3OnL2EC7AIsRHQ5imu1IrdFhcTFxifDyj3LRVc1CahuWc3Ivno1NTUpkVcpa1KKzu17xfoosPpLtOa6nS91OeUmucXWXy46hlUoU0DA0ICtTEw1lZkb//vz0cMZMuMGOZTE5M5ogZLvLAkEBhb5PakSfUZ7JzvzhrPyjAYagxp5a8C9OlMc4xcAEhgW7u5SdLpL4YYkIembpXx1R6ZtkJrnomFkKLRpZNjKlsMDiBwVV/bDXZGLi6ughLsyjMu8yqgslKWmOZrlySzGRo1CxSs0xVeVev1bvW16YeodZlUUNa+ab+uuHs3pFlqnDWkCef6jIqIyMjKSmJpdLf399dNgH0QwdTEydv39bJRZiRGg16ImrJdG5JiNm6uNHND0hlnP3KXSTYfqRMkSjK1RyJ5yMdOfSK7AzAwnCFuSjj/EEeeTbuzF97Fw/ngGa5SVEZMccxvWjqEIDVqPy0lPjq4ObFgcSgzsPid69MPrKayyAuHVhhbWvXePDDooD4iy2K+zb5OWduGZXnVzeNW02OlmwchIVJ5pWTGZzwh5oIM1WLbEfPAIxYkSOe52BBtSpetzDKsqJYouvWrUoBFC1aFkWFmwnNR+yOePOpy6uOJuP+Rq12yOemA61M+cYL3c+KyT+pjPTjcezRuQJHujFBKkCC1RavItapLWv/5Qr4IbePkDBEGSXOTVo245+8CmmpZXk+5YEI7u20jYgaYV75GTvdiC48g41lvkIakf/gI1/xPQE0+Sfvy9RpwMd1jzUgVXAJvlQtYsgHj+Ku0srnK6OsywvlgZu67bB11KIBSWrlaHWBr9bL28urazmylz9lWMFb/JNnktYM2ZWfHeQrAkffYJSSimGpuuYolsoKfM+vHPJPKqNh2cMdr66UY+YEukRzZ0REuFa/5He7qac8E/MnF9nzT55Z/9LAZYGYdVljiDWbmSs3beoWsNgc9rf8q4g87grhn96n7HP4Jz1CAiw7etdDqUy9TNQ+wJLE6tu8S2JEd+BR/M4Fvi17ScYqV81vs2g+uZdjvSKu0eu5yTHikZNXgEh4hpcXyE6Kzrig8QN6RbQXj7wiu5YBrKPFBRpjkp2Lr4vfVdUoyvDXNSCs6a0Tg7uOOL5galFOSvKRtRGDxsljv4igJ5ZLs6/U+VjbOVzBTG5aBqcyI9M1EKrmcUs6/Zs8w97dr/2jc7mcwuQ9GbsDnI/4WbA/YU5ALQ28dYixe6hqe/zWMte1c8Mn8TTAtXseub+qNZVyigQUCSgSUCRQdyRgQQCLvVzE4AkHv9lDhPeZVZ+1G/+B8M05eQdg3SFuKWHP8sAOA6XfzynKy750YCWixqvITaFC5i6+IfZuAYVZSSlRO6libe/sFhIpHnk2aoerMSfhlDhGp7mgQbJS4ieV0mWlgVnu4R1Tjq2nEdyXUqea7tz9Wo/lAvcYLQgFtOJooeirvv4FaNYJdCUGs7S4RHXl/nFOBXLpOS48LjIg8FYyX5l/pHCp8AN2GGwwsxMLjPXC/DTUpMeSDI3htvRSQU0aUepargSyNSeKsLNqO9fNQLHYtNZCx2bgTeniRpSAZQECZ5/g4J73x237GVNT3O6/Q3uMZExQ6pEjJkUtebMgPe7IL6836HW3o6c/xwZjNv8M+qFA+MAJOPLKR0+l8mrSM2n/skuH/ibHs3F36SYF95BIjigWpF8syk3lkbigQdRKjzlxdvXnHuEdPcJauYc041xMVvyZ1BObeOoS0FyOrkR5HGRG95GJlpW/RpGAY5BrxrHkkoR8m0blZ/dwqXTt3Z1/Rmm/Jo1gLeccnNbN4DVp0Mx1Sy5qDMClOUa+7MPMXCjdVSSBkvQiHvHuWHsRlmDWT0mmpmuVi2VpJbOKQOmsfknA4qZyaI9RyYfXEe0eu/l732ZdhGnKt3m3oqEvnls9m9vbo/54Qz4EwT3u9212TUyGZ0R7ABa/GE0xQrKkwrjkPCK6aS52L3sElpIekchPucC/pH1L5ZkqG7vGQ5+S54i0uDaCwHPdR0qOJUjAOVwT+KI+nyMBLEugqn7QUJKssV2VFpbUD3YULrQl4GBNjvpstm1Ld+1HJv6uPqGJqbUJrXsRCCYWjNJ8XZVArUEERw9/58DmiE0e3sRXzg9GDHkqZut80vF71zQePF6INqjjQEfvwPRzhzLO789JOunoFersHxncZYT8wndR0jOspWiZr17h1wSB+rboXZB5iXxn3zA7p6sHswnGihg2KSfpPA7EnMSTFHDwDPZo1Dm4y3BnH+3YTMLnD3z9OOFWrce+Z4rfORZcKH9rIgH3Fn7WdjaFGy/ZdfZSuV+xbtakRaVumQSKT2UVn8iyslaVlhkbFKnUPwmonDVKoXBbil13H2s/B7MxyOnUov3p1v4ONmHlVmezda10pEjARBKoNYBVdk7w6lFBOXs+TTvzT54j0l7hrflnZXU/QVTEAukWEDlcWNDhkdl6n/q37s0/3UfcCx/U4WaRr4nQwotTycnPUnVRbgbFTix6s82DH9SJmCRdlut3jr2XY8CtTROWnsj7KdrpwTCVh4KxjDDg6ujc/PmxXABiHeBQkphvVVyqewuGEbpRmqhdCYiLe4pKNO/O+HBrH3M4CtUxuXkLYphajvc2NM0NM7UrU6X3G1QCtQawaiLvStBVTZoVda/buK2Te+NbJp75e05O0rlTKz5ocef/tALka06D0kLNJeBzU8PkU/HFRzNyZkXZD/BjW2wd5KgAAkMEm1+ijstTR2UVbr/M2VmHEUGgK2J0SlILsTcY0qBSx5IloNaEmtt18y7alZr7QZRdXz+bCBebYCcrOxMEn4updYqplWJVUuowLMgmrPzCOUuWkEKbIoEqSqBOAqwq8ma6YgEdbsm9HBO/e3nqqZ3R//4U1n+c6fpSWjZQAtxuNT68aPvlgpUJBX8nGtiIUk0mAaKeHe9uYNPUrXBdEtkllwsUgCUTT31JArCsVY5jQm0auxYsjStcrxlrU3+41NTxnlDbpnXsRK2pxaK0X9cloAAsA0cw/OZH8lIupp3de3HHIiffUP825R5GA5tTqplCAioru96+tu08uSFafTG3JKlA3+Vlpui4frVpq8KAYR3qZBPpqrLXRECrfDWGq5LLNbpot37JqP5wU1pcquL3D3h3OnvZtnBTn8nRvDt4hE1xqsFWZR3saNPAWTO1yoLr648cFU4UCVhZKQDLwFmAJ7HZ6Mn8vA+mrDOrPuV2ePcGLQ1sq/5Wc7VztDfX3WCOttcGi3DLuX1ZtCy/fezjYdWt/krZ7JwVBpXms3aklZRL2OwEKB2aSAL56sJctVWpjcqOm2/452Vj1cXDqouJejO8WXVpSYFac6cDb70GDCqfKkuAG84YZa3ittxmZK3zs2Jahcz1taSUM8pF/BUdEhDtaHPt2n4NJRY9+grAumasqvXFxsGlxd3TD/3wfHFe5snFb7V7+BMHj/IL5avVTj0u7OPoUVvcWVupgpzBVsrH+BIobuiebHXYNlVtTAmXWpUUcrdW+apqfKLrb4sqG2uVrcayaJTP0dITxXa2Ee7BFg5cSpWpYpTxLmvEAse6iuNrgZTLh0UBWHJpVDvND/O1uHPq0d9e41whP1DYdtxs5VChXIi1O/trt3e5HOpZ2s7F3tbFruBSTs0lzG37SRvP88vcORfSi7O0N9b1TG4mYoffBnAKcePuN//+4S5lN8DVpKOS4hJrEJvFm4Usn8KajIJSt36MrwKwajqT3Ru2bjzs6TMrP8lNjj61fFbzu6ZVdsVDTXtT6isSsAgJOPi75EZzWUkp2t1ggnJjMs59dyDvouZ6SXsvJ/eWfjVpzWAy6nrF4pzC3NhM/qVsjw0a1iR4ZNOaGLSIwbIui7Sr62JR6FckUOsSUACWEYYgoN3gvOSYuF1LU0/vjt40j/h3IzSqNKFIwIIlAMDKOZ9emJLn4Gfgufr8xOwT727DLejXp2HI6OZ2no4WzK6lk1aqLuG3oaJ/Phy/8lRhRn6j8eW/cG8A3TSlslX0ggGSU6rUUAKEBxi+W6th3yaqbjTPvYnoqyvNht38sFek5hd74nYuuXRofV0hW6FTkYBhEnD01xwgyL+UY1h1TF/nvz8AugIKhI9vr6Arw8Qo1SIMy7NtQOu3+jmHul/eGpN+yPC7FXDaWhsvokui0CiJkiLND1Ern3oqARXRzPWMNQVgGWdAcQs2G/WKs18YzZ35+7PM2KPGaVdpRZGARUoACxZ0FSQZCLDS9iVkn03z6hTk27uhRfJXJ4mycbJrNKEjYCt24TGDGSAGixYMrm7Sita2Ff6Ah0n7VRo3jwRK1PXtJ+Qt9EUyz3AatxcbB+eWd0+3c/bgp6BPLH47P1253NK4AlZasyAJCAtWQbKBACv7TCrMBAyKqHc+gVoeIyxYbs19cL8WZxt0YoCzWxoXoaIXankcb8zuVfXNQ2ilvEjGnMlc09D8zqkqG1tMnScWTlcX5BqzdaUti5RAdHT0rl27Ll++XIvUFRVp7gSq/AORp06dqrxM1Z86BJS5CA21YHFmEGjlElZrt3hUnVOjl0xOTmYsmDYVtcxNRVUZ0Iqqi4OEGglX/0PX3H6gAKzqS06poUhAjwSUYEY9QqlJlntoq8hhz57+azYXkEYte4+LspRDhVWRJyt7dnb2kSNHTp48mZCQ0LBhw549e4aHh9vYGNkpABLauHFjcHBwjx49bI0RzLtgwYJ58+Z9/vnngwYNqgqnVSmDfl2yZAklkUD37t3lVdLT09esWUNOZGRk586a30SHnddee23+/PmNGzeWl9RKjxs3btSoUTNnztTKN+yrnZuDtYMtNzUYVr0oo0C0IFVn0Ddv3iy+Ojo6ent7MweCgoIcHGr0c4clJVxYWGr0WSTopOWsrCwm7eHDh1NTU5lUHTp0aNasmZOTk8SXbuLgwYNPP/30ww8/PHnyZPG0uLgYCrlQUXz9559/Xn311YULFzL6utWvm+Pgqzl2gISvW1K3AAFYZFrblFOiW0DkFBYWrlq1qqCgoGvXrhEREVKxxMTEbdu2tWrVqkWLFlKm3gQtLF26lEd9+/ZllKUy8fHxW7Zs4d1n9KVMy08wExjWqKgoSGUcfXx8QkNDGzRo4OKi2Yeo1WogdUxMjJwRZ2fnkSNHynMsM52bm3vs2DEm+aVLlxhZhgbu5KTm5ORs376d1XvIkCGCX/lTkWa4eUf27t2LKJgz7du3t7Oz0y1W/3IUgGX8MfVvOzDvcuzF/xbzQzoXNn7faOCjxu+j3rUI7nnzzTdRLc2bN0c/AS+ALM8888x9991nbW1MO2tSUtKMGTP69+/Pe24UgGWKoWA9euONN2gZbf3bb7+5uV39jTbglHg0YcIEAbCAI+h1E2GICrlTWTkGuOTFZ1lh87iCDCosXIUHsbGx8OXl5eXp6ZmRkQFegWsw6+uvv+7q6lqFBvQXWbduHWrvueee0/+4Zrk7d+785JNPDh06FBgYGBAQsHr1asj+7rvvUEJVb5gqc+fOffDBB8PCNBGcfJj/DKjh0/466Eh0ov+vAFjXtWDl5+fPnj0bjct7NGvWLA+PckskZrn33ntv0qRJ1wVYtCCm8YgRI9566y3QhiDo9OnT5H/77bd1DmCtX7/++++/9/f3t7e3v3jxIm8lK8wrr7zSpEkTUP7y5ctXrFjBJJE2DMBKywdYvDuffvopkLdRo0ZMyB9//JGR/fDDD6W9HJwyEzZs2MCk7dWrl16ABfufffYZG1Expl9//fXYsWPZY0iDrn8u1otcBWCZZBj5+efclFh+Cjp+1zJnn1B+HNok3dSjRrFY9OnT57HHHmM94k0+cOAAy/TPP/88dOhQrQ1TPWL6OqywigEH8et16tRJFMVmsHXrViCIXPuizrt06WL+HaHmKqyYjMK0fHvvygw212Hy2sfjx49/4IEH2OZi0Hr//feXLVvGrBg2bNi1par6jc3377//jlnFFAALFPjyyy/j75s2bdptt90GWAc07NmzB7VaVfrKyv33339sJ+BRAljYLBlx8w8o5BDhzt/rAizBICxjr2JCApJETnX/0gJ7KnDqgAEDqlvXMstjS8Ymx2uLVXvx4sXAjg8++EB6W4EmrVu3FpRLBkvLZERQxVKDjfbLL79kQkIwCJLNAFsIYQhna/Hss8+yG2QvhBW2IkZYwajCDAdJU4wtExO+X79+1X1TKmrfkvMVgGWa0VGpmt728pGfX85JOnd2zVxH72CPsLam6ametIoB5u6775aYAWaBqzA78/ZKmSZKxMXFYXvANUlfYBogHd431kQ2Xrhp2JQD+/DK7d+/n0UBXYJOZT9KebaqrDuUlNZKPAUnTpxAZ5w/f56FCcPGTTfddPPNNwvKgQuofHQJCYqJPS67WGlTq8XgLbfcwlYend2xY0fRBV0fP36czR9LnlQYDQ15jz76KF4JMgFh//777+7du1nl2U9jEaQL+pLKkwAcoABQb/fcc4+vry9GfiQAg/gf8fggAfapfP3zzz8hHoUh6oJUfv31VxT/E088Ac2O/hqrAzc1GBFg0bjY17Jk0zXKG5ZF7/AFU+TgRcJkgpdh8ODBwnbCSG3atAkPY0pKCiwzfGym/fz82HAjZ9Z0MBCN4CSFO0YZjwZCox30R9u2bXFtiHZg/+OPP0YTCBkC8kJCQviK/AUN0l8G+qOPPsL49NJLL91///0iHyHL3cQYY9auXXvmzBmYYhRuvfVWaJNaEIkdO3b88MMPkIQGwsLRtGlTWoNNHHDSgILbYI1MLEYwhZsGkugLWyamBeRDs7wvuLwlu4JWL1X/SoQ7hasIsCZOnIim/OKLL0CEzCLdXhgObBt4l7BPY4Zs164dU1Eyd1Ee4MsYMcm7deum1/ih26aF5/BeMIGx9/COMKAMGYuYu7u7IJtRq1tmG0xuDJBkHWcv98svv2C1YgsER7yMeLHBWNhxK4nvZLVkkWR+Ct7vvPNO7Mq8gDcCwDKm88XCp76ZyeM3c1qMecPOxbO0RH1yyTv5afFmJqDudsfbi7cefMCyq3fhNiJr4Cd8bSzxLCJY0dh0PvXUU2AaukCJskHHBPLuu++iTdHHaEpUL75LrOLAMkAACmblypVyelCEqFXCcVq2bEngxZQpU7DGiQJAFuo+/vjjhCPAF8sTzkownLy6PE0jrGg0AoAQ+VTMzMxES+Xl5UklAXM0kpaWJnKwwLONRoAgVCz8gCRpfRQFgBHPP//8H3/8AYqiDNqdr3h2aBloQnkAHB2hJP766y8QldQRG1ZWW/AKyJLM8psaDA3DkprVmwCewjiPevfuLQogZ4yaQA18Kzx9++23gU1CMkLOOBkBH0iG0SRNGRAhc4nFHe3OR8gBtUfwE8NEO0AohmDOnDmMNb0AZRhump06dSotIxnUCWYqJKNFJDIERtMCmFvrkfgKtkCMuHeBRDSFNQ5LBrpWqzC6ikzQM6YOKBQ4+MKFCwwoXYjCyJwBhUf8p6gxoa4Ey8zeNm3aQDaAG5a1GjfgK9e4U4ufyqlKXaASGAsWsGfoNWAA/pAnbw1oGHZwJoIm5S1jtGP3QvQSKE0MgfxpnU6LHZF891VH2ZGvHgwi4aHELZDJ56GHHsL3x6IhXkO9DPKIEC6mN7tNUUA4Clk/9ZavZ5mKBcuEA+rg7tfirv8d+WVycV7W8YVv8kuFto6amEflU5EEsEOgPzAwsDCxduMt4jWuqHDN89G+xIafO3eOmGKCYOgUoxF2DjLZbaMY6AKFzVqARUEsECg/YAf7NlQFGzJWnCeffBIsKIhhVcUCwbojlle2aI888gh4i5AaUQCbx/Dhw+kOvjCGAbawJBGRQNe67LCW3X777S+++CJAAVMKGgjh4DID2IHzdMuTgwLGhg8w5S/FyIFHSYZQhbEKPQfUgwYCaMgBsmAIueOOO4iBg2WsEfjpCJgAwRAUTwJkCdSjKRAh5e+9917+8rX8pgajAiwALtABKR09ehTDDHpXWGXQ37gnMLktWrRImEDgAtER+IL9CeQHXyBjgtKQJILiQ4JAclqDfUJhIJgPppR33nmHNvE+YzKhGACL4WZXDdwUZbA6MMREKPMVVIRtCbSq5cPCBMgQAJ7k9hhRnb80C3mgNyaJiJPDEvDTTz9hoxVfpZL0i/CZP0wbyREsPSXBfMOoxoCCm9FS5IgBhWWsoVi5gOBwWomGk7d23XQVY7BEOxDAHAaR89qyFdHFmhjkGFBGjfLIBMsotlvQvJg/ZPJy0QL2DHA8EtYrgevSbFEFkAmzl2WBrRcAHaMyuFmiEPMzaFh8BVwyK6RHlp+AcjYn0CmZbMUKw7vA4FZEP0LgTcGwJ0V6sJjwSkobwooq1o98Pct6/WDMQrhwC2nRZMTzEJOXEhu1bCbWLAshzDLJQE/wYVViK09kBk4QvpqOVFZDPDgs98QwCYiD/qP3s2fPSsYGMMeYMWOkpRDPILocrSDM3Rj/sZrIKUSdAMhQyagN/FNoca3TQ8ApgXhAbJhAWLYgQ96ClAZV4MBiPRJWLixV2F3EoUK0rFRMnsAYACMoXWlZl9AVxbA8ffXVV4AS0BWqnZKsjMiZRyhvTDLQDJjjK0CEZVEcCxJGLKw4uHvAZAJsUaaGNzXQgu4HsrHtoXuw/zEumBKBOxRDhgwKKlwCNFi2WN/FgcqBAwdCP4gQQw4GFSqK0dRtH3cVSh2rj7AVUXL06NEUBgRLhZGwQFfkYHrhL1BJeioSTEtEx1jz0XrEV+FyBX6B3REpH0hlNPmqW7jyHKAwRMKsIJjCYkAZGpQWMA4Miu0KFvhU3lRVnl6JwapSnDy6Uxix2AlgZkOwdAG1UkeQhCiwhjK1/v77b94FoCSFpQKk0btsaZhsUgvS07qYYAaCelkxQP/shdglCnOv4IX4fTaN4gMqrUMMskYx2Vh/MO5i26465axUvCnMBLFfpSIJZCKfBlVvrc6V1LM61DkeLJxgv9YDcjlUuH1h+rn95zd8FzH4cQsnuBbJI+yGjSwvJAqVIAaCIoE7kmnB6ISxrAvvDxYp0Tj6knAZzB48knJ4KqkNoWul6AEWDvSo9BS0RDgCfiVYQBECvwBqWhhRAihioaEXCou+tP6Sj9eSqFh8Xti6MBXgJJKMYVqFxVcMHvQLbpNIkhfDDofjjGax0gtkwDLHbpsyOLMw5EiFUZYAAiwQfDAa4cfB0EJJeYyRvaejtZ21wTc1SH3JExg5sJ9BIR98gnjrgBEvvPCCAKmYFaXCiIJHYAtYwCKFnQkHIg6Lb775Bq1GI9KCLlUhAfZFMkwqCXcShsUwYVqQijGgUloEBiEKKUckqEILDDcfrUd8xYYB/UA9cVBOKmDArp0BhRGwuNaAMidR4USA4XRmemBGxdOtF+1JvVclUR6DVTUXoWiQzQm2Q9ysmDdE8KLUEbiKiGamDdIANzP3eERaKkACvphUWGq5tYGINMbUKEhR3oU505hdifPj0APvKZsEaZoJGpic0momppY5aTO4L+Y/FnG8vbxisFatdhhQJjBYHEOXqMjmjeWFN6ha7dTRwkbY9NRRzs1JdljfB32aaU5uJ+xZkbj/b3N2Xbf6YrVleWVVYpPESsSKjJYyHQuYPdDTtC/ZkFj90eVkyvedcimWsXsAAEAASURBVN0G4qE81hRBFfszNuWSzsCJhr2HcGZcIRix8EOJ8nIWtNZc+SPdNMsT7iHyCULH8kQsM+BAt5iUAzgAz1WkyLGCYLvCKkZwMbYcaqGSxUKPLwwIJT64e1hPWQGRA8YwsCaWJHyFKHXqSn2hGwnD0vwc4TUa8+pzw1LSHADbQQBcszrDOPnyWChMI8L+AQs8Ig4dQIYRi1pgXKiVBkVOBsqPfNZ36SlDDwiWb8qrMkBYblClWPsAQPL2RVq4ToCDYOIrQt2CVCXfim6VinIYUNSbAMFaZbCu4TImQJCYGFjGBSkxpVWy6l/L78Gq5k3ueI3ZBhCJhYdakh6CBR+DXzFNEdHMq8Fc0ksJw4cfnCHAXcvbpBcZ661ogZlYp/73v/8Rb4CVVBKFRCfzmWkjPnUFYPH24Z0XoZnwpcuUxJ3eBK8n4Q3sQxhZUUAs6boLo97qdT1TAVhmGUGVqsltL7kERNDZuTVfZFw4ZJZe61InIBU+EsXoPGxFoBzJJSQ9MmICgCV8fzhiRLM4cXAa4iHikd6OxB4dZ5lQZqhqAo2lkigYtD53d6HzwEY8qgjrSFWum+BAHKAT1wMCIYincvUDvECMOGUkC5xc6YLVUACc+kH5oZIxtNCyODcO3mL1R52LD2keofkIqIcjjBNIBsjLWiknGIBVUqAuytQfECYvaUAaYSI9nIas0djkGBQceZIxiSAk8BbCgUjBIxqLSDLCrZAAdfmLMuADs5KdiXGBEgK8YEqQRMAfKqQi3V8R2YwCdjU25bhciWeXF4MYJi1SBanT7xWJav6X/LZSeYinKTCxtL+XHokEBPMUZqW3g/bFhwI0iIsTlsnhQIPElFYjVf9arRgsqVlQFHGH0Ik0kLbIJ3QP9y5uMsy9FGBCMihSFa0EjkKUNxOy/kW7a3Fat77yarBQYCvFho1LQb7trJwRpqK09BFQweizgIh5u2/fPua8WHYqb6QePFVchGYaRBs7Rw4VHp73fGF2GocK247/2Mn7Gl1lJjostRu8A3h5WI7Z3mEYIPKasycAAhx2piMZDIEvCdMC9hvgC+oK+xNmHoK7SUsqTU4A+2wigfB9sF/HRAGUQW2gJkUZbDysHTiqiHAin+AbYJa8ugFpTFaccMYAgIaWjtRV1A7xQ2AOgAhcQB5KFwoxIQjVDm2wjJC5wRUicWVy0o2ge/yDOGhYPfFrsBQSZ8YoECtGL4RDsT5iP0Ma6HKwjrxrKc7dzqOmbIpmsfcAm4CtRHvgtmObC46BZp7iAuOoI+4/3IgcTyPoG/Bx11138YgwcOYMswURYceiPGQDrbAkgRTR9Lhm8IpifsOChYGBM6G4rhAU9ifa4R4KZCLnqypppgECIbQIDMqEAXqyR4dsiMGjR8AKdh0CutFMUAV+AiTh5wUpyhtn5qBpaISxgGtmC83KC+CAw2+O/HkE/Vz9gPWUux95WQTL7BDw/NKOmHvyugakS9Qaa2QVr2mQ2qd3rswQPj4pE04xgkI5njKAJucGJOwllZEStMA85GQr2FfKVBK1LgF2ViyJxJsCj5jSgh6+8t5p7bW0SOWgLhG0jD4REexesOexyLD+sIxgamUfKEVZaFWsZ1+vWS7rGW+Wxk7ZocJpmkOF+dn8UiEYy9bx6gETS6PWzPSg/1CKaEc89FiPQBW4sfD3G91Vz54M1tDBrOkk0LiEsOBRQkux5UJngzkkdQucwk0pt2aRRmuiuYFl2L1Q0jjdWIMEgqEiW3nsW6hw9AouEjxc7NuEMFlrcOuIfskBrOD5ErYiUUD6SxlKSlZ09o6Qwe1HElzjKRhIlMc8wFdBJKgCFEI0FaHrgBUecRGX2HeCt6Q1kbON2F3YSnKFBHH9SIA4eqrgcmL1JKRJvvyBQUEAjA7KXqJQJMRNDXgJXZtoPKc1+UA/XAAycCfBPriB7ohelygBxDBqPMXIgYkIYxUIRnANLmT4wCgwxcwBkxFlTCPIFkwDFuEsG1XwQEEhj6iFcDAKkonhRPq1AEYEGuQYiGElh3Z0WaN9UBpShSQuHmNeMVsYdOH6QVzAIBADY4FhhoEA+wpqRZtSKB58EUnGdOIqBw6xgvbkA0ovBHKhkMSAQjBBikwDWEZ7obTAmrw7vCxwQWFdOquVU27Bul4MFtMMc6b8ChVIwj+LQBhB6KdT5MD8h0Ju1+QtQ+xk8qIJehhKBCtKihzedGIu+WAJEydIRH6d+IvkmTZwJNYBLZp5yrTkqXRSQauAxX4FD4mgMXmQIpNQjpWZDNj1mdvy3RcjKwUOgqt4F9jmMWN5TZjhLCkIxGK5NiJh5db1ilpcdHTTuCXv8vS70ZPvazuIlxn9x3qN7OqKC7ki1mor//LxzVHLNFsBj/D2re6dobJWMK5JhqIgu9jBVVu2YB10LRoL6IYJquYKySSkW1ij2MDYsCI0VLgWaZnHkqM++i/41qYho6tnaDw8ZWNJfnH7T4ZoNah8rbkEkrdEX/jxUKNHOvj2qrYOS9uXcGbunob3tAoYXNnvWtacSANbYK9SYxBpYNdKtWpKgMW2ugtsUU6anYuezUw1ezZH8Q1n9478dQo9zRry5FNdRmGiFuGD7HvlRgFtDWQO0m7sPnxb9uVQYezW+RkXDp5f903ELU/d2PIwE/d4vjB38w5g6mCLzMGl6r78ZiLUYrphfURQHLvDDoFhD2OSLmnlNzUY9Sos3V6UnOpJQFhMr9hNq1XXsBisanWhFL5BJKAssAy0ArBqYbY37HM/vwZ9+cTWhH0rnXwbBnU28Je8aoH0OtslQZdcN0AoN+G0+GJwnNVZVsxEOOE++No4bYDfDe8PgUS6HfMjOSob64KkHN1HSk5tSSA3RnPvfM6FdN/eDatLQ4n4qZzruQir26xSXpHAjSkBBWDVxrhzqPDWF/PTE7ITzpxf95WTd7BnRMfaoOMG6pPYCKJhiLIisImYgBuIc0NZJaICWzd4lMtviCvXux9VWasc/JzzAViEmVUz/qe0LJ7aUOqUehVKAMjLM36Eu8ISFT9QLFgVy0Z5okig2hLQvIrKx/wSsLZzaHHXG/au3vhhTi6dyT3v5qfhRuuR2EFCpxV0VcVxJzCZe7w4oc0puUqEBsBS5xUV52iODlT94xjgQhUT3e9QdTLqZcniHM0NFFyfYQB34rcIq3uK0ICODKtSWmLUK9cMI0KppUigyhJQAFaVRWXsgvZuPlzcYG1rry7I4ZcK+b1CY/egtKdIoEYSAFdxRKjyJoBKFChIrp6X0CVcc9As52z5D1RX3oXytFoSyI/XrCTVhbyiC3GTu3U1LxqtFnk1Kcw1xDWprtS1cAmobOqbb0GZr7U55VyDmjQZOQkK8tPiuRyrtET7Fzlqkzilb0UCVZBA+U0N1QzD8mituWPi4tITwidVhX6UIlWSQOqe+JzodGt7m4JLuQbcsF/+W4Q21XT3Vok0YxSyVLqMwZvShlX9u7dIAVi1PK19W/RpeJPmRseM6MPn1nzJT3XVMkFK94oEqiMB6a7R6lSy4t4svz4N8+KyLvx8uKTQEGdWtbq7QQrnnEuL/uUwPxDp0sjTAL8tUlJisG6QqaKwaR4JKEHu5pFzZb2E9rmXixu4HyvxwGpnv4ZBXar3a5qVNa08UyRgYglId41Wt5/Qe1pnnU69vC0m+2xq8IimYAKNt1G55ai6crSyUucV50anpx1MSlp/jt9SDhvbNj8xOysqBb+trat9tdpTAFa1xKUUViRQuQQUgFW5fMzzlEOFL2gOFcafOrf+G0fvBl6NO5mnY6UXRQI1lICDrzOoyICbGmycbFu9cVPs4uOXNl04963mtyA5k6gALAOGQwROUdHex6nR+A7uLX2TNpzjK6c7XRpV79rG8hgs5ZoGA4ZBqaJIQEcCCsDSEUltZBDq3uKuaYd+eK4wKyVq2cy242Y7+1b7DpvaIPw6fWYV5apLzeQAcrCxd7K5+ot4pVal6YXKuYHrDJBRHtt5O+RdyjZE2iorjzGNHLv75kalF0RnFl025GYBo7BQpxtROdg4NHB1DHNzaetb4mjDQBR7a2I/MhLSbAo9qsVaXoFmCLJKcwsLNIcb7G3sHaztgL3VasTohZPyUuVtFucXlNqXn70wj8XT1trWxdZRTkOdTpeUlmjRz+LpYF09Y6dWC0b8WpCbXmBnUyK7KddaVWEsk5eDe63Pz0p4VwBWJcIx6yOubGg5Zvrhn19SF+SW/VLhJ3bO7malwASdpeRn5qsLTNCwnia9HdydnGQAq7Q0MfeadVlPHSXLGBIo8bFTn8pPSE1WOV7nyKH+3nytrHxdrHq51LcTRPq5NUkumxiOceaUZFjlatovcdPcmpGZkF5YzVcgvwxgpRVnW+eZaV9kiDiYZWozk1eYVVgmWS1y2cblFJcWaeMVrVKVf+WtUTkZ9OJU3m6dflrl417udi7AX4vl1XIps1iRmY4wl8DGTUe+xHHC/PTEk0vebn3fuyobZYBMJ2+lZeNIwNrXXn3KqiSl0CbEyTgtKq3UTALW3vZYnUouV+9yMk2fxWWHbCz2FGHNxGLE2sUnMou2pagv5pZmVRkLVNw942Ud5uwwMMA6qP7YySpm9wZ68n/2zgM+iuKL47n0RgJJCKGXEAi9F+kdBUHEhoqKgn8BGyoq2AAVlWLBXlAsKILSpPfeew29hZLee3K5//cyybK53F0uyV1yd+x9+ITZ2dmZ997MzvvNe29mFf1tXZ3tH9q1bq+nrm79LenayYtrvm5478slPiHbuhhSqLF/CTgGaA2HmphMBwVgWUlvO6kcq7jm0iMl/Ynj9a31HKyScmOJ8hps8ktvZh/QWsdVPi7OTX3KaH/KTcrOvZ6ecyQh53ii24Bqrn0DHQhGVH52IQEFYFldN9bq+nBazLXok1sij633rFq3Rqf7rY5EhSBFAjIJYMHiqjT2ElklStK8EgD15pxLBg2UzG+b/y1CRcEb6A2NQ8ZvV3POJjvW9HAfUdtsJluNQ87ppIxF4ZlrIjTZGrdBQQaaV7JtTAIGY8dsjA+7IlfVcPDLlWo2hqfLG+fGX9hvV8wpzNidBIQFqzT2ErsThfUwpBKoN7ZkXkLxqRwHxUVooCOz98WCrpwaVfKaEGI2dEVbKgfnZj5ebzRWVXbJ2hylDtcX72WAJCXbmiWgACxr7B02FYY++J6bT1UcL2eXzkiLvmqNVCo0KRLIk4Cjv7BgldwhpQjQYhK47bctURP5LkLFgqVPampN5opbKjdH90dqWQKDqtip+Ehth1xtK/qaV/JsTwIKwLLSPnP1rsKXCp1c3NVZ6acXTs1OS7RSQhWyFAm4OKp8XRQXoVUNhFL6bQXAUixY+vpSfSVVk652bu9HfJu++2bIc25cyamOp/piCr5dM1SnVFHRElAAVkX3gOH2vao1CLnvdczHmYmRZ/79MFedbbisckeRQEVKAHuJJjFbk1Wm/eoVyYDdtV06v61wEaoUgKVvPIglhDk9g/pacazhwffSNPF38mxvP9+LUwCWvjFuNXn+je+q22cU5CSFn7q4+mvlS4VW0zNWR0haamp0RJRGdjpfeZIo7CWaEkb8lCeF1tPW9avhKxYuPX30pCGS1Dnq6MiydmUp/bbCgqXsYtPXN+K8K5W7ZZUmLkgav6PXKhU0ienr87LmKbsIyypBSz9f664H06OvRZ3YFHV8g2fV2jU7P2jpFiu8flDC+mWrTx05ce/Dwxo1DzUjPVcvXkG3Fa3Q0clxxDMj/ar6F71liZzwy9fWLF6RlaUNQPb08qwaFNi0VfNa9Wq7uZfyFBx1Ts5bY1/Lysx+7/MPg2pWtwTNxuuU7CWlPsjn2qWr//29RLTi5u5W2a9K3eB6jZs38a1S2XjTxu9mZ2Xn5GR7eHoaL1a6u2q1+ua1G/t37Dlz4nRiXHy1mtWbtm7RpXc34zTT+3M/+27YYw82bd2cdhnt6alpbh7uTk75p01uW795zrRZX8z/vn5Ig9IRpn0Kv23lkvttAViYr0wLwQIIHjtweN+OPe27dOzQrbMgNVede+vGzX3bdp89GZaWlta4WZO+gwcE1aquKnLmOozfDL+xaeW6c6fO8grc1atr27s6ODvbpEqCl92bdxzZdwghwGkVvyo169WmfwOqBqgcbwOyyJsRx/YfvnT+Uvjlqy4uLrXq12nbqX2bzu0KCcc04QtpW/pvbm5uXHTs7i07z50Ki4mKadSsca+7+zEsBcEJcfEHdu4LO34q8kZE9do1egzo1axNS2kYy2lLSUresXHb4b0Hc9XqNh3b9R7Uz6uSt7xAobThc9sLFbOFC5sczbYgWDPSqAoe/FJG/K2k66evbJrn4VfLr1H+XGbGNqyqqiP7D/329dzUlNSu/Xual7CsrMyoWxHUmZmReensRT5+F9KkkZMzc4JzTo4ZDgw0kdrE+IQtazaiSxo2CTkTEX3jajj69Z7h94549gk3t9uH0ZtYG8WYxPsNuTs1JcXbyLRlenUlL1kAsEq2Z03eTlJCwobla2rVq4MyTk1OvXzuQnZ2NgDrjY/eqeLvJy9pehq1t3bZyivnLr34zmumP2V6ya1rN/353a+JCQmo0uq1a0bcuLVny67a9esYB1g69WN3/PHTb0eOG1UvuL64BbIc+uhw3yol+8qNTrVcOvq7aaN5snJVrrd1fNFi8hxchCpnkzQ8KvPf3xfSZSTA9BLAOrBr7y9zfgB7hbZo6uTouPyvf/du3Tnxw7fqNdQFi5fPXfzi/Vno7w7dO8dGRX/5/uyR45+5+/7BcnpsKH3u9FmkwRtdydd33/bdiXEJjIRnJz7fqn0buGAobvhvzcpFy4HXwJSq1QLjYmIpf/HM+VYd2+gFJdbA+4Wwc9/N+JKB3bJ9G9Y8G/9bt33dFnqzeZuWzM+fTZkRduxUy/atGatA6r1bdz3/1isAZR3KmVq//ujzo/sPt7urQ66T0x/f/cKC5H8Tn/epXNYRrtOQFV4qAMsKO0WXJEcnl9AH3zk2b0JmYtS5ZTNbjPrUKzB/LtYtavvXMZHRn7wxrXqtGmkXr5idm5Amjd//agbVspSc8uIkJ2fnyTOn6oIS5sK8Zaih1rlfaMWZVy4/U/tkkef0Zjo4BIeGTPniI0pfvxI+6dkJW9ds6j6gd4NGwbefJxTDQU9b5Bb6qRwcHR2x9hXKzLvIY0W7pC56S+To5cVQYSP5BSHVZd1I2P++uzHt0BBL5x9mfb12ycoDu/YNGHqPvGktzUi5KE9FxIUO2LVxB9AtX2KFH9Ffj6yzjAsH68s30z/H2Pbhd7OatGgmKGRcVatR6BAjKuGWkS44vOfA8QOH00Y+qCUyj8LgxiHBjUKKMqiHHsGyXmkAsDhh/6IDfluV6eeDCwuWXNz60hnpGZ9PnXlw177Ovboe3n1AXqRF+9atO7V/dPTIyv7a70z/9Pl3K/9eenTfYR2ABS97tuy8euHypBnv3dWrG9bc6ROn/PTpNz0H9vHwtOHvATwyemTH7ndhUV6zeCVAc9n8fxs1DYUj7HnfffJlpco+b8+ehsFPSCw9PT0zPdNq0RVE1q5Xp0X7Vm/PmhZQjS3tDuv/W/P9jC//W7AEgAVT3fv1HP3yc3Ub1ufWres3XxgxZtG8P4sCrNPHTtHX9z36wNMv/49+nzfnR+rpMbBPx+52bilALArAQgg28HPxqqz9UuFvr7GpkC8VtnpmDjk2QHcJSczKzFr4y59BtWr0GTyA6amET5e1+LVLV1YvXnn+9JnM9AxMKQPuu6dlhzbYmaJuRf4w+2t0iXYNt2Ld9SvXPv7+05TklN+//Rk6WaxvXrU+OTHp7uH3rlu2unOPLvc99oAgJTY6Bi6ys3Nenfqmu4dB9x/OwU69um5btzk1Of/r1PExsWuXrjpx+Dhws1qNaq06tO0/9G7sIkkJib99M/dm+E05q2/PnOrh5fn5lBno2adeGMPimLt43Fb/s/xc2LmMtLR6IcF97x3QtnN71Dx0/vjZtz0G9MZDsXbJqogbN5+fPCGkqfbQtbL8VHmHufO1nLJUIn8WyFinfl1ycDmJfAS+dc3Gg7v2R96K8PH1CW3ZDJuf8IcybFb+s+zAjr3xsXH+VQPqBNfvdXffajWDfvnih0tnz4PVJo/TWrDGvDIuuHFDgtU2rVx/aPf+qFtRPpV9GrdoKtWTEBs/853pA4cNwsSI7wNjZ7Ua1ZF89/69BA3SX+qc9+WPeJZHvzJOQlfclaMrHCL4v+gIhlCDxg1BwPUa1tdBWhT497e/8WN+P+trnCaNm4c+9fwYjAHL/14y/s2XaudJgE7H+HFs/5GY6Bj/qv6Nmzcd/sTDrq6uKxYt3b99D4YQ/8CqdRvURWM1aZmP8wSdBWbFzBL4bXNyTTmAIDMz09unEljB2cUFmCWJhYSnp+e4N16Uctp0bAvAwmAs5YgEAsSMQbpZ65b8RUQ4no7uO4TQuvbprlPY5i5ZuXXp2535AfMeYJTBvOLvpbAM/MKKI7HjkfeTLq0wwcTyzEvPSYTVbVDPy9s7Iy0d5zi4sP99t1c+GLHqBtePi44pugzgtWWc1G8UzODn175bJ4IBTh05rgAsSbBKouIl4BlYr9GwN8MWTctMig7754PmIz/muKyKJ8usFBzed/DQrv3vfTH9QthZs1ZcfGWsJmdM/gBNMPjhYZV8Ki3/a/G3M75846O3WYCi/86eCGOJhiJHU3bu2ZVgKVwbF06fS05IwmgR2rJpaIvOzdq0+PP7XzesWDtkxP1MqTSJE2TP5p0PjBphBF1RLCc7G9CGI8y3inbRDw2fTHr/yoXLfe8dCMg7sHPvnz/8SivPvjaedjt17wLU0BbLzJz7+XcEebi6u+GBOH/6LPoeUrkVHRE56+0PkxOT8TT5BwYs+/PfT9/9eMoX0/G45eSoL5+9kJKYdP3qdSZElpsl8mdRud4fkbkqb2ft13LM8cOegUB2btqGw7RDt06iyrVLVy748Y+WHVo/8OQjsVExS/9YdPLQsY9/+MzVzZUoqD+//63fkAH3j3yIbjp19KRGk4sxCECDzmZOBzNRiV+eq3Hp/H+Wzv8Xxrv170Ury/9cfCv8xuQZUyiWo845dfh4+KUrVQL8Bz0wBCS3bsmq86fOAlzECl5iDgTGkKgaVK1Jq0KYRiqA2/ez9z6uVrPGfSOGJyUlLZw7P/pWJL4VHbeIX4A/8o+Pje/U466adWuDnyCDyk8fOZGRrhUm6gp3Ob5IRl3n3t1uXruekpSE2Wzvtl3zv/u1z6B+sBxx/daxg0d07ZpaC5bW3Vyi4zM0alyExfsTfX19x096ydXN7dDuAywwJK6LJoivcnF1JUBH5xZ8EdODnCv5VuIW70uVAD/+0hc6JW30ElyF7dLF1cXZ2SktNQ17J4xgn6N/bZQjyMZXmJGezpqkqNWN2Sbyxq3OvbvqMAgUuxV+kxHLRCQYJwaABItP25WD6ZQrFizTZVXxJf1COtbr+8yVTT8n3wi7sOrLRvexLrfh11VHoMxB330y554HhrAcP3/qjM5dS1+u/ncFlqFnXx036MGhtFWjTs3J/3sVCwEASzQdExH1v4kv9BsyUE4JMQrjJ03oMbC3mFaAVj9//j1Rn81at6AYwaEs3QYNHyJ/REpjmcAeAxjCSYSvBP9gYHWt8QmTwIWw86zzRr30LIaKbn17RkdEo1AHPzQUP0vHHndRJjsr6/dvfyF47LHnnqIMLgmpWlTXrk07wE+PjH4cUwf5GPNnvjV95cJlkqXq8J6DxEBgcis6UUr1lDSBOldfTdV+Ldi0IB699c//bt6ieX9lZWSCFDHsffTDp1ikKAnoXLFgadWgqngrsHaQw18KY1Ac9OAQJmsk0Kpju9Yd2+GgwRkhKieNTdHJyRGDlshhjC365S8Mky+9OxHlR2YlH5/fv/mZAJE2ndqJMo5OTjN+/Jy1O5dExwOa8e/oACyixGjRy9vL08tLPCX/i63im0/maHI1WKFwBItbv301l4CbNp3by0u26th23dJVhDyTz0YH+S2RBjfDY5e+PV6Z9qZgXORj2szNVRMZA8uu3V1B0kWfLY3fFhdh3i62orUVylE5FGzI0DpADf0unj2/ZfWG+o0atOqgjUOS/xilhEg3bd1M0sfEudMjbJ+UF7O5dGx0LDtpACKbVq7lJW0YGsIIgSmGKFOKiEZgMB8/dBTjluAO07JZFjmWlhXz1bqlq1l8Dn7oPp22iP6c99VPzHUPPjlC5xYvMgtI5iifgphC3mgsfAAynZJ2eakALBvr1pqdh/OlwqhjG6JPbvasWqdWF60GtYMf082vX/2Eh4UoV/m+m/Jhjen+4M69rDXPnjqDOYFGmRT4i21AIgCnYbsut837Ih+DRMcenSUl0a5LR0xfqPCpcz5iPsJ8RbwFS3OpEnkCdfvBq++InDGvjsMV5e7hASXYvVj2YW1iVuKus4szGAIPIAtBKZAFB9bG/9biFerUo4u8TtL41G5cC2e3TsT1m3/+8Bs5UEK1/GVmF4Wx+rC3y4zoimq1ET9XUnPjshwDtYaT0v1whhLekZmViQXo0tkLf/34+6gXx9RpUA/LDfq4W/+eEshAPvjUDu/Zj3DAoLhgfpz19d4OrfsPvad525ZSj+iQcfn8JXIIJ2dng7iFy2bBT78f3ntAAljsBBToigJiH19cjPbLvvIf2yOIq2J1o9ceAfzCvoVthq0Me7ft5kFcJ/wF3ukALHmdetMXz17ArtOkZVOJcVEMJy+I+ec532O9I3CtRbvWRVnO99uWyKwIPvY0z5otPi7+h9nfYOUa+/qLhgAE0YMS1yKqDlQq5dhigrEE2US4V/L1Ybn14KhHGWm8fZrcXCx5giPgyIIff+f1F5ezfvnKkHysRwLMilhkcZq/POX1yn6FolOwz/3+zS8Hd+4b88pYXOqGaJaPKoY0EjFU0p7yFYBlc72pCr7nhYy4W0nhJ69u+dXDv5Z/Y10Va3MsQfCebbuw3Ez6+D0Ck/lHMA2ZeIJY/ImgIosyxVqTFRWLrT2bd6gKNgkDd3LUt90fGDOK7vb39assz8TOgeLftWn7reu3Th87mZGR0aZLIYuFnAvsKJM+eY8YnXfHv44NQ5gEUDAECTEhi9BRUV5Y14VMyKFakAcuxTETxrL9UF4nacwnKcmpJNg3LvGCesYwA+oShfFGuZs7lLjAIZVZFoBFRK0IcofOQ3sOzH57+oqFy4gSI9KIHHyagn7+enh5AD0T4hLYbIh8Pvnp8x9mfr170w52ObXr2vGVKW8QJCQVlhIcpgAQoTxTvMhEgPQge7ukMj55TitxKTAu3SHdFQmCwDCMZaRl4AnSucVlSnISvj20LNvEJBszwwkXc9HCxnMwcKKhfXx191vR+7D84+xvCB/esWFr687tXps2CaUury3fb1uiwDgsWGUwQEqtw/s7417Hi02AIME3Ur6UoBf8AvwwcUk5URGRuIYlR5KUb1sJsH6jFk0Cg6rVrldb6g483ZX9/LBSM8NgpaPvZv48h0E1//tfl83/x/oZBEL9OPtrNgxOmPYGSyA5wcw2hD9u+G/tE+OfxiIuvyXSrOWwbDHBssATOQRXcCkJp+gj9pSjACzb6828TYVvH5/3SkZCxLnls1o+OdsrSM8UZluMXTl/iWCO6a9PkZP9w8yv2Po7bc7HWoOBJX8sLgl/SUpMZFNhaPMmpjelYzZgJsUtBbI5tHvfvu17AgKrNi0cdyyvGQMSPqaQJiF9hwzET8TM1aVPd+KoatSphfqPiYqWCmPOIR2QF72enpbGBi4WwW9+/G5RdEUxakD9k5j+3eyGTRpJlZCA2qw8+5ywFshvlT1dYC8pMYYw1DSHCWFJOnHwKLgkOLQRAFEuE6L1ya9avRrR+tSAqCfPnIJzFrvOnq07Vyxa9sgzj4ua5fAIixSXmEv5K/ouOSkpNTmF0DqJDAmVSjlFE3QcFk2MEJjZih485lO5MpWHNAt9a+YUE40TRSBcfpuB1YNysnO0+BKMV/glwNXCGDh74jTMgiyJtHt87CgJOIrnS+q3JQbLsczHuNNN3348B7SEh7SegaO8kA8+wSN7D9GP6FoMPPExcawuigqzqPCtOad1p7bMADoUspiBWfbQYCjF5AzvLHgYgRxjoVPSCi95WX758kdiIbBdde3dQ04hc9Hi3xetXbLiifHPDCvY2SMvQJoBybEjhHzERmnXSPzYWMNfUGbelZ3/sYEOtvMeKBV7Lp6+2i8VunrkZmee/mdaVorWq2XTv4efefz7xb9K/0aOexp2xr350svvTbQ0uqIhpjzcT0kJSew5Jy1+GCFYn5VUqsROsUjFjkIAdYPGweyINF6DNkjrwSEcN0rwNQEcFGbFz/zLnjjmLy5ZPhLQjW2sZp2a0MP2byLDCIOQgsN06ge3NQhtiHWHZSWuxgJuVPI4LZ1HzHIpIn40sfleyDLWmZWZifOLbX1aCOXqgleiToO6m1euTynYaHl0/5G0lNTOPbXmWxAS6oqpnNA3ArDQ06ySkRW2HySZnppOAUFP3YYNyCECJjNDa3niqS2rNyElQshLRDBoD68u5iv82njxpGfBfJz6Q2926tUFVy8ITJI/g0kqJiUcVSr2KKjVHOeoP+aXM5MgkhCxrOx85Mp4gGA2OgiWm7RqPnTEcNJE+Ug7Lm/XH+AKMsNvK+UYS4DhTDumwUglAKaZkz+MvHlryufT8YfCvlSYHmGLLsZaiXLuasPziSnMzr507iJDt3XHQgYS6VmbThAEydGaMIvh+cqFSzbECy/OnPdn4/7jQK9u/XrKp2J6E3S15I9FI8Y8MeTh++QdDYO4FAFVYszDO/0LRKPfGaL7tu8l5p1j0mxIDqUmVbFglVp0FfygZ9W6jYdPPr1wSlZSzJl/328+coZNbyr0rezLP0mmlfPO765S1V/EOEv5lkv0GTSAwCYs9jfDrxP0w0kNYSdOD35gCHvNStQocawPj358/rfzeOruB4aYEueE54tYDYLW2Y0/YvRI9qw9NPrxJb/9/cmkD7CssFeO2WrIiOEcFI7DiKOhqJkNbr9/97Mg7J77hwRUC5AT2bVPj92btnPuA/vROEk1NTXtzPFTBNGzM05ezLxpyUVYlmrXL19z4uAxdiqdORHG7Aw8fe7158XcPXLs019/9Nnro1/u0LVTXGzcvq27iPdn0qe5v3+ef2TvQQLG2ZTHpkvifvgAAEAK00jV6oHsK/z64y9AqN369sCB+9asqV9MmzXpuVdbtmt949qNo3sPDrx/MFIqKdkNGjV8bOxThN6/Mfolor4IH2RbXNjRk1//PRc/13MTX8TtOPOtD/sM7s9iPTkpGQDx4luv6AJulYpzGoHjC3+ej+rljMp7Hxoqp6R+SDAB7ITqT37uVU5xu3z+Iq6WWT9/CcucaECEe0BgAPoPMx7nVoCq5c+SljrFJL+tiH8qg4sQ5PftJ1+yJwAJfPPx55LJrYqf3xvT3wFaffzm+7hKP/h6BgXYyMnWDc5Vwo5FvODFMxcee+5JEw1+Omxa+SUDGAR/9/DB2LbfHDMBTMx2DZZz7GCAchkEtTo+WKQRucEaYMnvC5fOXyTow/n+xLhnsGwt/v1vFjNEROzavF0i/aFRjxG2P+f9mXTrt//8UrNOrUbNQnve3WfjirXxcVojJRUS5ii2AUlP2WvCaerUqUZ4OxV1eVnYDgoMbdKtRbVgPn3AD53h7e0tohOMPKvcsrQEPPxqOLt5JVw6lJUcm5kQ4R/Kav72etHSrZtSf0JWSo7mdhiTKY+IMqhYJh50j7/Jn6/xQBYut48ozMlSJ2ry7RZF28XtQqgXJy01b9tKqCXsH+x1AsQQpnP10hW+XhLStFH7rp2YTQh4T01N5QglYo0lwMSaDAtTveD6KFed+ql25aJlfAfjibFPS+XlZQg2x4GCvpSWccGhDYnP4KD5hqGN0EDkY7ChXXYk8c2N+x9/iIOswA3paelsH8PtwjxFJeIfgIytcExeterVbd6mBctl4h4IrifgNCk+EfsKYLFRsyac4wXgYN3JzF6rXi1kKyep7GmVi2P29hh2Ebp2L4T2TKyZUwmQCTCIIy2gs0W7Vr3u6fvwM48xQYsagmpUx+PJMUuYBolX4wALzmuAWe4STs6aODoymoC2GrVrko/yxniFHHBPANRAqAiT/uUkM5AQMz6IhG8C8uCAYfdgDhTnaOCkTkxIpJelsCEMaVDVrHVzqi3KCN+BYWMmQ5TjIol7I7Kta98e9B3YDnoAfOyB4KB2DpKlZnZIgIFol06kFxg24Hjq5Ah47HMMsLio2Jq1a0IbcywWMrQUYw/dTIXsbGd4cB6bT5XKfQb1p1FO9IDmmMioqxcvUwMs41+mXR0icxNzco4nOtXxcqqr3RRp/Kfha92bopwC3VzaaY8LMeWHcHgR2P8ougkTBeeJ4A4DR9KJDEvxj30e7CFg0AJ26RFYwykPlmJDAxZcQqfx8A5++D6+RqD3fTGFknIoo76Wpg5LdmlV2TFIN/CR1jH24NEmsBKUX5QY+OJDQA2bNOYu721cdBwKlGXAgGGDkB4DVXpEfTZZfSXNpbO/Y2Wt77tif6xkGMnMRYV6068Kcw5TKGe+8KbIb9HdrGGImk2MTwSWsaRhlDKGmW04kiNv62sup8qNGDNSr5RKwayfm49jQdRsKR4v9SOX4m8uOL6Rx/s37NChZijhhrzC9LKXl5f8axwqXgkjbSw6uXnU4o8oMPf+Nx9r2T86OjomJoaRERQUREVGHlRulZcENBdWfxV5ZC3N1en5RO1uj5ZXuya1cyU5IkNtHp9Rse3xpgV63FYM6clZV9W39wAW+7gZC5w6euLtsROfnTh+8IP3mbFa668q7Yvz6uvplWa2cLBwzJz1i8JKKAQT0Cmu3QLchusBiDpEatLUKe+cdG7m4zG6vs4t5RIJZO2MyVxyw+PJus6tC22jM69wMv+7mbU12vPlEFMwsXmbtsXaGvrUdHbUXVeUAyMbLx4cOn8SDc0YOG58h2GJiYmRkZEsnwIDA318bu81UWKwyqEvLNqEKnjgeN+6WiPKtW1/xIbttGhjSuVGJMCCDpcccdZ8VQ3XXtEDFIw8ax+3tGFYuZrc+Gz7YMcOuMh3EZoYGEcAFr8yuAjtQGIKC4oEzCgBBWCZUZgVU5XKyTn0gbfcq1Sn+XP/zU65dTvktmIIulNb5XTBF0Y8O23C2yQeeOqRcosesx55F2wkLCebpfUwbrWUqDydVB5OJh7mruE7OQQZOClKQX9/ivALHJ36b5srV89eCHNVrdRT3hJQ3qXylrgl2nP28Gn6yFQnN6/cnKwwNhUm52+ItURbSp2GJEB4O2FDhLJ+/NPnXXp3F6HZhgrbZb6jvzaUxFwfzLFLEZU/U45V3bTfiDQFFggLVpmPaSh/HsunRT4GRUOa5ByLNpebrDUAi7Ys2pBSeTlIQAFY5SDk8mjCw7926PDJBIaDrsL+eZ/jG8qjVaUNmQQIoB49YeyoF57l7Ks7EF0hiYI9a6YdCiATnZK0nARK4LdVXIRGu0Hlp10/ZO+PK/rZR6PPleRmdq76fIrKy9mxSsVHuJeEbqWsfgkoAEu/XGwxt3KDtg36PwflKbfOn1/xGWstW+RCodl2JVAAsBRwb0V9WAK/Ld/J0boIrWsnshWJMkvrvcu9lZFzLMFCVGWujtCk5Li0r6JsE7GQhMu5WgVglbPALdtc9Q5DgtoOoo2YsB3hO/6ybGNK7YoECksAvwafZzEx4qfwo8qVpSQgUK8pfluOcdcSoQAsA12hyQOgQJ+Mf6+rLxg8AsbA08Vlaxyy98ZlbY/Gz+56T1BxpZX7tiGBCtjfaBuCsVUqVQ0Gjk2Pu5F45di17X/iNwxo2sNWWVHotjkJ8AmeALfcyIyi33WxOVbshmARGGcS6lVchMZ7PW8TgHNzn5wTiWnfXnTp7OfcxMexlgfbCIw/Z/yuJilHfT0t52B8zplk1ifuj9VRuSqGD+Mys5m7CsCyma4ykVCVo3Po8LeO//pKetxNHIXulYO8azQy8VmlmCKBMkqAiJ/cG+maxGyVFRyTWEZe7OPxEvhthYVGsWAZ6vg8+TgFe7v2qpqxIByDE/8MlS1FvlOIt/sjtR3zIr1K8bjyiBVKQAFYVtgpZSXJ2aNSk4engrFyMlIJeG/19BeuPqU5XLusdCjP33kScPR3g+ncmEwnBWBZR++b7rcVLkKVcg6WgY4TLkLk41TPy+v1xjnnk3PD09U30x2yy3SygsrDGTOYUx1Pp/peVvYlDgOCULJNloACsEwWlU0V9PCv1Xj4W6cXvJuVEgfGav7kTCcXPZ93sDRP/m6+6lJ9KqcUhLk5Fdp3wz6+IA8936woRc3KI6ZLILFGZpRDlHeSi68ifNOlZuGS16p6ZkWkBbn7Gf/uXaqTJp3vDrl7V7GyvsvN+9yIh4ubi8qgMy43M0uTo3b0cFM5mt+/lqPJzcjJTFRl8oVwX89KPkI+bQMcbPDL1JwEnJyt/Yo8P2dHJ0PfmaFQ6p7IrGsp2eGpMC/Km/2vk6+rS21vtwY+np0Dpd0VmeostIZ0rghfhXBzcs1Oic9OiHT1r+Xs4S0nwxD98jIVmFYAVgUK37JNV67fpsHAcRfXfpMSceH8f5/iNzQ+vVqCmkqutz8OaIn6jdRJOFBlt0KvopHCyi1zScCphl8UcdJxOYrwzSXSstcTE+STeT3FM83Z1c/Y+6hRJdGWp5u7TfadhzHWyihDZwcndyeXTI12Ceft4WmT8pGJwM/99rdcZNm3k3EHbl7943hOiva8FWcvV1cfyyzONQ5Z0WnZN9PS9kVl7oyqP6atZ23DhHkFOlRrfJtEG0kpAMtGOqpUZAa1G5wWc+3WwRWxZ3Zd2/5HnZ5Plqoa5SFFAqZKwK2a9hOlGZGppj6glLO8BNwD8zolKtU4wMoVJ7k7m98CZHkWy6OF/JPunQ1a0cqDCMu3Ebnx0rW/TqrwWz7Y1K9jDTd/T8s5LjkWP/1GcuT6izG7wk9/sL3J5G5e9S34nUfLC0+3BeVd0pWInV3X7/8/zseCqfCdf0ef2mpn3CnsWJsEXCu7O7o4ZkYpAMuKesYt0BNqiu2UghgsRSno77vcHDU3GN76b9tFbsatlPBFp529XZtN61l9UEO3AAuiKwSmclRhtao/uk3w2Hbg18tzj+SWLaDN2jrBnseKtcm6QuhROTo1vn8yIVm0fmHF58k3zlQIGUqjd4oEVCq3QK8MAJZyzK3VdLmwYBUPsPIsWITlWA3h1kWIJk/3q+waYF376wRAp+4TLT2qVypP6ft1rBnYq176reTIDRfLs11Lt6W8S5aWcMXX7+zuxaZCZ3fvXHU2Ae+ZSdEVT5NCgf1KAICVm6nOTlLOc7eWPjbRb1vgAlNOctffccK44mi/LtSc1KzE0zFe9Sr7daihXwSWzK35QBMMWoR/WbKR8q5bAVjlLfEKac/Dr0bog+9gzcpOTQhbNE2dxW4h5adIwCISMNFeYpG2lUr1ScBEv60Sg6VPeLfzCgCo3SrNTEInNRrvEL/bPJdjytnLxaNmJXyU9mT8ttuxUo4Dwzaa8q3bkk2F0Joaeen8f7N5kWyDblumUpP3My8H8jrlafO2UpbasGDxuNZLqPwMSKC8O840vy1b46GX6GYDVN/p2bnZIgbLboPcc9Ky6WMCsCqqp9mxmJt3RENFEWD2dpV3yewitd4K+UxhjY73QV/s2T1Xt/5mbYRmZ2enFv5lZprfzaRWq2kkIyMDJWdpCaxcufK7774z1AqUxMXFRUVF5eSYesxMUlLSb7/99scff4g69+/f/8UXX8THx4vLffv2XblyxVBz5ZZfOgsWQpA6n34vh94xl0BEP968eTMxMTE3t/gzJ8+fP0+v7dixwxABdOjOnTvNO/hN8dsKC02xMVh0TbqBnyGOeN1u3LjBQ4YK2ER+vnyKi8FiJMfGxkZERJg4HqyZd9HXvJhMznI6yTdxFjVUA28KNegOcrvzTivHNMiHjf2n6/Udkx57Pf7ioeu7F3kE1Als0cd6eAaOfPPNN3J6Hnrooeeee06eU/b0xYsXX3rppc6dO7/11luurpZdq23atGn37t3jx48vSjZI6NNPPz116hQTTbVq1bp163b33XeHhIQULSnPSUlJWbhwoYuLy5NPak/cOHbs2Pfffz98+PAqVarExMS88MIL99xzz/vvvy9/pPzT+RE/JbRgIYrXXntNUOvo6Oju7t6rV68RI0bUqFEB4SAmCo2+o39/+OEH0AMwy9nZuVmzZoxY/hqpga6n15555pkePXroLbZ27drZs2f/9NNPbdua7SBLCfW6+GqP2tf7KzipvJhVd0JCwsMPP1y0Bt6mVatWFc1fv379nDlzGLpeXl68C/fee2/RMjaRY4oLdc+ePUxioG3GhpOTU5MmTV5++eVi32urZR9cBf2XLl0aMGDAG2+8IdGZlZV133338YaSaXwWZU345ptvXrhw4f7776f3Of9ZVMJ89dhjj/Xv35+3nhdHqtnOEsW8S3bGrcJO3qbCSR4BtRHFhVVfJF8Psx6ZXLt2jYkJzRpQ8PP01G4vN++PKSM8PJzXm6WVeWs2vTY4HTVqFFaKwMBApmBmq8WLFycnJ5teQ9GS/v7+o0eP7tevX9Fb5ZzDYUsqJ0dtPEdJfqxl6ReeCAoK8vPzQz/9/vvvoJDIyMiSVFOoLJV89tlnetFAoXKlumD8YE0ErF++fLl69eqtWrVi2AITQVolqo/He/bseeTIEekp0P/IkSMbNmwo5ZQ9YYrf1hQAASXoSAab/Oft7X39+nW9L9SaNWsmTJjALUYmmhh9vHTpUr0ly86jpWvQGHUR8hb/+OOPvIOIglVBaGho1apVedOx3lmaMMvVT09hiuPFZKgfPHhQaoh8MjHUFduVvIOiBl5ngJpUA6+JiTVIj9hiwm6Roy12RvnQ7OTm1fThqcfmvZKTnqT9UuEzc9x8A8unaeOt4CyrVKnS1KlTJQMAS0Djj5jrrjDps5CqWbMm2kJUCxTDhYdxCMXAqv3WrVv169cH/3E3LS0NLEh5ZlKdBRwrNmZVjFKoWywxeinElwfCe/DBB9E3VEjl8B4cHExhcAaN+vj4sNwXz1IhtvTKlSt7GD2rmpmONaVUhkrIgXgcFgK4wJogXlRLPtgFMuBXAFmkDeATd/HmoCdQpbVq1ZKeQoXgvQL9YEITzk0E4uamaxFhK5BbVc/SxWA9+uijQE8awr0yb968X3/9dePGjY8//rigCo6QFWQzTpCwfOHLPE4H8RSKHy7EQjk6OhoUSya3qAHKBbXUAyPIHDlTjzTMkAkCQdSwzLMUQEfyk5bdggzxl078+uuvkcB7772HNqVmITTRj6IMHSfGCWJEaPLHRRo1g70KpmgOIqkEImkR050kdkrCHQKHNrhjXAl6hOqCEXIklos2IXIkC5ahAuTnx2AV97FnX19fukZez+bNmydOnPjqq6/KM0ljtcKdDUczZsxo0aIFUBL8QQ6WD0amTmHrvxS7CA3FqCEEMR4+/PBDZjC6m3eZbpXeKetn0BCFzEVMEZMnT54/fz7vi95i4t0ES3GXqYY3S16MMcBkyAihBl5e+S37TutXAPbNs8Kde5XqTbSbCp2z0xJPL5pqDZsKeT9RMKhMXkVUC0CBnw52sUTHobRefPHF7t27o9rxtQ0aNAgjP8TQFvoAHyU+ICYFCmAqF5Z/XB533XXXsGHDKIxL7uTJk4IwnkKdk4PJpE+fPsy2ElbToRxNjGYViId5B5bR0EIBUxvqR+5q+fLLL8mBDJ1KdC5RZhTDYCPyUWljxozZunUrfqihQ4dCKgyC/MRdVtVoREh9+umnhakfW/24cdo9EKjtw4cPcwuTPrf4i1VGCCQsLIyq8EviFEMgr7/+OtLTIUNcArDUadns+tZ710gm0AG4Q9djx6pdW2tnlYAmDM6cORPJA0wxhzz11FM45kRVADJQDj5WcEnv3r1JAMvAYXjrTp8+TTG44yd6CtDz0Ucf4ZOlnr59+z7xxBMCgFIV7PD4okWLPv74Y4RJATwjrN0F+3KykRL9ixhpAtuVwG2QjTNIoGoeYZwwDBDg4MGDBw4cCCVF6yFE79tvv6WeV155BQrfeecdytD7tH727FnRIvBr0qRJEPzAAw8gdhwrrAfAgtOmTaNauhWaeXbdunVyCnXSpvht82OMigtyp4+0L2fBj3ELF0CKLl266DQKRkf4vAV169blFh2K3uU1l1sydB6x5ktxDpbeg0YZgQAsEBUvXZs2bZi4kBLzGCyLsWHNfBVLGzMVLwKvCTOhXgMtC04iLjDEPvLII+K1It5DPtpZtDBEz5w5w8slzy+2aVsvoFiwbL0HS0m/T53mwfc8f2HVnLSoK+eWzQh96D2VqiLRNuYiJilmKDwITNks4pmngB2lZM/kx5jxWZETJYDhgXmfpTmqbtmyZSh4UcfPP/8MYUwcderUwX5w9OjRd999t1OnTkAWVD4RUShFdDCVEGeAw4gF69ixY1EqTLh79+4VxgYdcmCNFTxLeSZfdKShRaHOUyW9JNoMRAIQQZgHDhyAqV9++QUDIfV88sknBFnDNUoRLELED0paxFhgmEFJYG9guQnjCAQQBqmNGzcWBBBiAkBEzTdo0ACu9VLlXs0r8YT26HDn+iWLcsNoBIwDcIAFlyxZAhlACtEEQAQvAx3Rrl07DAN///034AbJ0ykgkn///RfrSIcOHdDoIGM6CyUHQKRCEA+zP5Wg5gFGQE9mf3xwzZs3p/CCBQuQA5IRFiOBnOhfQtmAaP/99x8AF5xEhXJOIYDupkI8vPJ8KQ1IBRVBD+ME5y90vv3224Re6fQ1UVYMchQPvCBPekqqQSToAiwHdB8EUxKC4Qt1BQvoKjoXfyK4n8D5evXq6TwrvzTFb1u6YwjAkbw4rFLkJjfRNFgW+vGfipUGyydGESFo2BTltNlKOt+Fqu8gViYuXjcYAWTYCjslopPhx2y2YsUKVgtFp2XANhMmS9BGjRoxGgHc06dPp5jczU3YKDGp//zzD28Tdt8StW67hRWAZbt9V1bKq7UemB4TfmPfkrjz+69u/rVe32fKWmMZnmdFzsoGVURsLwnmYkwXxD+iUMtQa/GPoq6mTJlCcyAh1OqhQ4eYBdDuEsA6ceIEoRUodeFI+vzzz1nDAVNE8DVEov/QpgCUP//8E42CxQKjCA2zYsOUgoIpSgTL/blz56JxAUAAOExHLPugoWjJsuQw6WPeYF6DtSFDhmzbto0pkgrBsuAGACWrUjQ6djvC7cE0YD7+AhmR//PPPw+yIUElH3zwAWBRAlgIBNQFC8JUo5fC/IifyFSv+iXzBAF3wFWgHNpt2bIlyA/8RBNgWVbP0ACcFaY+sCl2JkAG0hODh1kb9QazdBC0keDyr7/+ouNAOYJOzEiEu2ENYmhRAw3hXwMxgzKl4GtapF/QGbBPGdIY7XQAFn5bWgE3SAY2uRyoFvMed2kFlSPGMwYnWtcBWMAjcoBHWOYYY/JKRJrAly1btmC7AgXCOFVRORzROglAlWAZCYjxWbQGkZPvt9UedORg6NNyJsZgyZugX+gCnD7YAouOB+4yopo2bSrdAo8uX74ct6a8EltJA0C1/kF9O92QP2ZF1htgX1thx3Q6GWnwNWvWLGzzYvuFzrO8a8wYjEASDFFMxUAxkLQEsKiBCZNFC28rs0eFb8TRod9yl2ae0y1HqFKzJSRQt+8zaWwqvLD/xt5/PQNqB7bqb4lWTKkTHz+mESYp1BtWB+wrIC2MFh07drTocgcAxPobzYe5An1AmgkC7S7RjP5r377sW0zUAABAAElEQVS90BAUBoEBSlD2Ag+JUKdz587hicOng05FnYhnSWPA2LVrl1SVlKA2imE1AWah2oFroDqsSgJMSMXKmAAisIhkyqMegAKQCKBAGj0NdgFEEjCBd5J5kEwseeRjmhJeP9AYVhPyKYNA6BE0Opf8qBPDkkgb+mtKxI/eZ3GNde3aFY8DckaqWBPx/SErjFJ0CvY2ga54lkxophjkgWWxsVESawo6AKRiKMSHetCFzPuiHjoCGxIgm3okgIWgEB1NIDrgEQl6WYdaHhG6BM2hc4tLEeBFb2JXE3Yd3HyUlHyRRR8xlINdhIZgVhBMWgApWCZADezL+GERwhA1xLJUM6g3IyIFv62hg47yLVj6LDRSJToJXhzMb3SZpErlBXhHkDCrDimTAQYLUidK+TaR4BwsRxf9UaGwSUdjmWM02gQvJSISpvgBjhlpLIGA1IQKyGvgneLNwvaM/5e1BwsGRnvRtSVvNwYwHidhyPQrr9YO0hXpFbID8dk6C7gFGw97w7OqNkLiwuqvksLzw4kqhC8WSZhV+ItWw/cBOgHxSGFDliCJeQELB94ZwBzYjlADUJFOQzhumD1FpoidQm2g7Fma8wMXQiplqArLEDgGrS/VIPS0dKmTQCPihsOcjrLcvn07lhWdAlwyr0nIpuhd4zm0LidAIELxCOYQSMWEhk8TXIIZBhMaoAEuxLRIo4JBugMG0d9SW8ZdUaKYKXvWpArlCeKZQEjEubOxH78eszbxXggBYihGB0mFUdL0CyqNqRwi8b4RVQYmw3SEu0r4a6TCUkJwR3mpTxELopBDKLlRypBZiL7jFgZXOXqQWhHUgiRoTogR7YsYS7FUgEEakvejaAWjEZKBZTyV+HYxDJCQCNCbcBeffI6+DXd0iokg9xJ9CgZPJUJA4JI85XXyNsE4ncK4EvmYP+HFkGdZ/qwVpgly1xuABamMImIDWBgwjVgh5WYhiS4mxpFlA8ie6DqpTl5A4jqIiyAqEYCF7d8Q1ueNwLqPzRi3O052qQY7TigWLDvuXJNYc3LzbPLwlOPzJmSnJZ3598OWT3/hXjk//Mik5y1TCKWCvueVtuhiF+21evVqbFcYbLBUgSrwyBw/flzOk1xzAJ7QzUwxACO5GqY8IACdByIkSgaUQA7zjnxjs7xOKQ2bgDOcdAAszEs8whzEXUnfA9qoUypfogRVidqKPkUsNmYeSCU+BvMDxhuBC1GHcAHLxDOx8a3og+TIBaK3AJluAZ7Yf0p6UoO8NlrBUgg92EjAtZjNkBU9JZXBJgTMRXrkk4kDgjMdgIk4Mlgi4+gkBIp8JEDX8BOiECcSsciWcrA2AREkByiPmMIgUuIR4tUwfeE91JEzCgaNC/34Tfgr0WwkAT1678IXYwALokSwVIy+IzyOfRh4bbArEKCGKdQI8cX6bXNztDSonPX5wKRWZQmibTDR4X02BBx5WViBADsQOLZSsCY2PACWIQUsq9sak/kuQn2kMVkRz854YE8o4UpGekHf0zaTx9KX5Sh7REBUsCzoZhZlcchfYiR4KRiowC+9lnvKMzcSGYnxHmhuM2yXgVDFglUG4dnLoyCq0AffzdtUmKT9UmFmWvlzhr5kesI/xWIXeIHjA9XFBC32H1mIHtpCSaMd+YGugFbGzQAUw7iCJZz5Ba0PVdQg7OHcIlyd2phZ+Ett7Ci8evVqUcqZgOBUMCtUDv5QTB343ZiXWd6BKghIZy1IJezgE369ovWUJQf3H8gSW9Gzzz6L/QzihYJH+eEyo10wCnqRJkjjQ5QAn4mNEqri5u+RGV3igYRBiDEA7xxSD2jAHsCGAKgC0OAsRuz0ESShsAkjA3ricYAkvFT4dgEiFIMdcpAnaBUdAECnsBAmBYACWEnZXEmvUQ9tMddjaCGEyETWRDEkhuUPVIoBks4CANHpLMqJxmNggCrAPTSBuhU2M4jBGicsW/KGqIdKIIyBRxkKi46QysA+tfE6wCB3wcSgdhIMQqx0JAD6gngqoQbpwaKJYv22JXIRIj3Oo6drRBdIzYFWcaBDJIyADhnVDB56k/K80XQoQARYLJW3oUSei1C/xmSYgRuQhoAOjAeGAczy/uq1cdoQ1zqkMmkQwigiNcUt5kB+pMU0wsvI5KbzlHRJmf/973944XlrpEw7TigWLDvu3BKw5lO7WcPBL55f8Xla9NWzy2Zg0yrnTYXMwkQ+EvHD0p+5GM3B76uvvmKOLgEbJSyKqwIAx4xAbAGwBoVNZIAh75KomzOZOMeBeCkcNBjDWZGjWTlDgbmV8Hb2yDBxEAmEpocLjEPSIQ4SaSgeYsbZBAenICqKUQMhLOK0J8xjIAkMWszX4APu4pIzu58UQw5WBGw80ABhzHocfIBLDmWPDR/8Qeg9cyhNY6VAcxPaTxS2xIIpCewlSaej1ek5Th4lmGTw1eKAoH6mbAYAK2ai2iGPHALGOaqemH2IBPzxI81czy0ianH1ko8xCYsXciMkDtYQJn1Eh2LZQuzi8AVgAe4MehxoguSpBzuQiLWiKtN/oAS2RxC6Tow8Tka6EnwD2fQ+gwG3HZSwYxHfJaYmepDBhvYFXsibgDWi1DEAYBVA5vQLopYXoAs4qJPxBmKDI+rHTwqCgWUAKHVSIQ3ROpuzRG/KH5eni/Xb5gOs4o5pEHWCCLH7Mm6J55O3gnKFF/Z8tG7dGthBFB2gE2kgE/Al4xnrb1FHvLwGq00bsWBBM250ts7hdufHCBTjAb8hgaSGLHxWy6kRwhjqxBXwBkmWdZbBvAtMdJiQ8QOwmGEGYz1gqBIGLSEKwCxDBewpvwRznz2xrfBSVAKBLfunsalwz7/xFw5c2fRz/X7PFi1juRyUEP4UlBOzME4fNCWOM+HQMW+jrLDRtagiZkAUAHsAceIwKQCJWIujz0B1wq1DDrYBHY2IFqcAO90wpbBIxY/G3kPmU4hk6gEfEG2NdQG9jqcAszlGFx360amwBgHYt9CXADuizYBTQuug9TGNADIgiZkIAmiCWHhmLupBS6GPhVOMS4wx0MwjpOGFtBR+jikeeqhBap1WABxcQhUGKkxlhE5TAIQBugUXMksy68EgYAWy2XLI4pt22emGh44HmUmxD0lNSDXrTWAvAWBlRqd61rlNg96SIhMXkmQLoWsYDzQKs5Iypl3ACtY+4ngQOCqcXZCU5HG8VDyOtQBe2DBIBK7YkYe4AEB0Cr5FHhFgnUHFdgrAAfVQOZslqUdgOPoCGlheS3QiJXIMKUhOC2PAsMtPhBkB1nGRCJnTHbTCjjngBTCOpsF81EbNjA3qlIJ86WKQHzYqhiVjSQx+CiBtCkMYA4kxwKtBxzFsMJRi04JHahMGEsjgUh4nJ9EvTxTrt9XGYNGeo0kuQkSK6OggQafUEIOKTG6JUcrrwxvBcgKYS5+yHZLTMaTCtpXIi8HSH+QOIwxFeo3RtWHDBtZsoG2GDWPJpg8apRMZt8BiJhOpsxjkYCnGHhhamkUZ1WBu3jh8iAxFytPdPMJ7x2BgsSTNWmTyLhM1iJREDVLN9pfIdw0YYmzRyc2jFn/E3bn3v/lYy/7YwDGqIzKkKaZ1Qw8q+bYoAY0mlzCsuHPazfwNB7/MOQ7lzAU6BnsJL63xtbgpVGWm5Lh5664fqJzoafAKRgtWUVI95NOi0LJSpvGEMFfwlNDx8sIoVN6RYmsDXTFzoYmL1kBtkMSUpPeWvK1SpAFPLLI5khSrFfTDCLgEyz+mCCwlUoXkC7HIZ0bpbrGJiHUXwxeeCh7X3q+DmW2QhjpL9Ajy1JG8GFRwocMI8idHp3CxfOktQD8K1F70rpFxIi8MU9RQlHipjF4uDLEsPaWTOP7GRnVmTps5d+vki8tT07Zl3Exu98O9eu+anql36Jr4UpjeSnmX1DgcGP2fd4hfk8lao6nxn5HxYPzBir2beDLq3Gd7a94fWmNIo5JSwvgUL1RZpqyzs3YnhcW0//FeQ8fll5Qqy5XfePHg0PnaKM8ZA8eN7zCMxQ9LDt5f8DRrVKldXQ0k3VASd6AEWL02uu/1E79NTI26fHHN1xz47lu3kP3f0jJB2wFNLNEKBm38FBiuCYXB2oE7T94KL4b80pQ084ghUuWrPSNVAW74GSpQCpIMVaWTT2gIipm/yASEgR2OAyaIGmE1KS8JgyYyIn9KShcb8SOVLGnCkGQM9YihQWVE+CUlSQe6yR83RJW8DGlDTEnF9HJhYuVSJcb9tsZdYFIlxSb08lKWsVRsi+VQoERbLI2Mh3IgtUKaYHzq7fcKIcZ6GjU4v1sPiQol5SkBJ1cPArCOsakwNeHM4umt2FRYRWvptfUfLz/h27iE8MjgUrGE89FWRMTxpwS5s1OaA9BRe/giQVpEgCEWM7JQbMSPGdtSqjJRAsb9thq1hq90m1jVnVaMCHdYtn7Lik33i4GttDbMkwKwbLjzLEQ6335u8tC7J/54Myc9+fTCqa2e/ozvQ1uorXKrFiTB0QPYsVlp8Su3dq2wIQJ6CLxlPxrbA/Hm4O4nlgtrHOYQM1LL5wiprSwnNZiRGKUqIYH8LxJG6g+MM5cFyy6lLb70bOigUftgWZzyVYHvbE5ypqObkz2hfHNOqfYxyBQukEClmk1C7p1AIj02/MySTzS5+ad427RwwFVgiDscXYkexIXBNgLCV7HnEYdLcLd50RWtOLo6uVZxJ8jdpseMnRFv3G/Lp3JKdMqonQnHODv5Wyxd7Flj5qRmI4TE09Ha7ymV+y8nOSv9ZopHjUp6P0ZU7uSYp0F7Hi7mkdCdWkvV5n1qdXkY7hMuHbq8ce6dKgaF79JLAC9hVnxGbpY9oPPSS8GanjTut1UsWEb6Kt+CZdoZFkbqseZbLIogLzshI3bP9fKnM3zRKc5r9ut4+2sN5U+D2VtUAJbZRWo/Fdbt9ZR/Y+3pR7cOLI84vNp+GFM4KRcJ5NtLSn7caLlQdyc2YtxvSxy3yumO9p4bGRMFFiyDxzQYeda2buGhu/rnibSrieVHtsYhese1mF3hnrV9qvWtX37tWr4lBWBZXsa224JKFTJ0ole1BnBwae23iVe0nwpWfooETJSAFPFjYnmlmKUlYNxvq1iwjMhfBLnbrQtVFl7u2zJQnZ59+oPtN5acSb+epMm1oL8Q83bKhbgL3x64Mu8og7P+mLZ2to1ACXI38k4ptxzyNxX+8rLYVMiXCj38zHyskSJle5WA8Ygfe+XayvnCS5h8NhbFJvxBcmr5FqHdAgg5n6VKa7K1nyEy9LHnUlVpTQ/J9v141asc2Kve5XlHb648xz/GibOXRY7O4QuuWQmZuAURhHdwlfqj27gHeVuTUMxAi2LBMoMQ7bsKN5+qTR6a4ujkkpORErZwCn/tm1+FO3NJwHjEj7laUeopkQQM+W21hgr22CrHNBiQJjsAuGNn9hUDvDr4tghs8WHvuiNbBnStrX2LgQkW+afyblC5Wr/6wWPbhU7uZn/oCvEqFixDY0zJvy2BSjUbNxzyyrllM9Pjbpxd8nHTEdP4MvTt20pKkYA+CQiAlRmlbCTUJ50KypP8th41K8lJyI8xsusgbjm/JU0XxGDdKSYJJ0+XwD71HBz4p/xKLwFFTZZednfUk1Wb9UqPCQ/fuSDh8pHLG35sMHC8KexnsfdG5t035ZFSl3FWOTk73g5Bxe6coc4qdW3Kg2aQgIuDcyXXjMgUpSPMIEwzVeEYoP2oXGpEoofaT16lOiuHS42T9b41vN2OWkOKnh/zjFqjtTDp+2myYpJy0zJcA3wdPd31FSg+Dwcan/qhXG75yidLnY1dsXj6SlKCCrNz1Y4O7Gdw5Mgp+ZxJc9SUk5uTnqNltqJ+aodctexgIDrdy8XDEDGcu2PoljXkKwDLGnrBNmio02NkWmx4bNjOWwdXevjXqd6++G+WRaTFlptyrYIv0137fVzx47uK4SkRBVfK/xUjAU2AS9aV1GsJtxycrXoerBjpVESrau90mo29GZOWUkhpaVK0ACvDIeuaDb41HCBsDIYAq/iXm+iQUsqdcYzdnJQE5JOgTkkrR/mU2+pUjEROltbymFWuPIqmjf81gqIa+tRyVOmH3cbrLJ+7CsAqHznbRSsqVaMhr51IiEi5deHy+u89/GtWrt9GMJZy63zyzbPV2+lCLuI6ym2OKDrHllvTdtG7FmHC0d9VfTk1JzbTMVBrOFF+FS8Bf23AsjomS+ftEC4wjZNKJ7/iCbYCCkBv4hwsjXP5TWhWwLe1kGC7Y9J6oZ+19K1Ch0wCji5uBLy7evthHzqz+CPOeedm3Pn9J/54I+bkVllBJalIQCsB4ZDKjalIj4PSE3IJqNwcVd7OmiI9wocIKaacgyWXVaF0Tp6NTIlRKyQU5aIYCSgAqxgBKbd1JOBayZ+vQTs6u6ozU08vnHZj7+Kwf6blZmdiwVJnab0Pyk+RgCQBVV7ET26MEgwniaTiE6De3PgsB4EYJHLyAYTiyZUkUiihyZOPSvF0F5KKclGMBBSAVYyAlNtFJeBdPSRk6GvkZ8TfvLLpZ3GQCd8rTAo/VbSwknMnS8AxQOuQ0sQqFiwrGgXaTsF3H1cY9eZZsByUk9wNdVTeOVgOdv0tQkOsK/mlloACsEotujv6Qb+QTp5V6+iIQDnqXUcgyqXiIrTCMaC3UxQXYTE9JSx8CgAtRkzK7UISUILcC4lDuTBFAtlpSbgF06Kv6RROuHJUJ0e5vMMloPJ0Unk4KS5CqxoG+v22eQdpKps9DfWU4iI0JBkl34gEFAuWEeEot/RIALfgid9eTb4eVvReasSlnPSkovlKzp0sAceqbrmxWWy+upOFIOc9OiJqx4atl85dlGfK0znZOZTJzTV0sJO8bGnS+v22iovQuCwFAFVchMalpNwtLAHFglVYHspVcRLIiL/lWikgPe6mvoKaxKsn/EO76rtlal5sdMzhvYfCjp2IvBnZol2rEaNHmvqkaeVio2KWzF+ko7269OnRom1L0yooZan0tPTfv/1Z78Nt7+rQoWsnvbfsIBN1rr6WlhufzZENRti5dvnamsX/iQLuHh7+gf6NmzUJbhyiPV3Sin9pKanb1m8+svdQTFR07fp123fp2KlHF1c3Y5xePHthzvuzhjxyf4NGwXo527Fx60+ffvvhtzMbNGqot0AZM426CEsm7Ytnz29ds6lVx7YwrkNVQlw8L1pIk8bd+/fSuSVdpqakrvp3+dF9h2vVq91nUP/GzZuorPbcSBM2AZw/fXbdstU3roaHtmzWqkOb0BZNGMkSs8w5e7bsOHPyzIXTZ909Pejcbv171m1Qz9GxZDKXKiyfRE5OzrZ1m48fOHIr/CYdfe8j9/lW1h43eHjPgSP7DhWloUuf7k1aNtPJz8nO3rt99/b1W9U5Od369ex1d1/r7Wgd0st2qQCsssnvznu6coN2/ONU91uHV0cd38heQrkM4i4cKDXA4iCrfdt2//bNz7zS/lUDXF1dkhJKeTCgnCSddFpq2trFK1GBgdWDHB3FnilV87atdIqZ/VKtVp8+epJqYTM2MjolOaVmnVoueZoYxWz25qynwgKHVKZxgJUUH7/6n//od1//ytmZ2ajn1OSUTj27vPj2q16VSvsJWI3D9g1brl26MnLs05YQyKHd+7+f+VV8TFzNurU8PD0vnj63a8O2idPf7tyzi5HmGADZWRymnW+gio+NX/jL/HsfHlarbm3xlF+Af0iTRl7epeXaSNt5t/T7bU0AEPKK01PTdmzcxpohOSHJr6q/HGDx/h7Yue/7GV/Sifc99oAhgHUz/MZn730CHKkX0uDMsdO8++MnTejU4y55K9aTNu4ipDdX/rPst6/m+vpVZgzv27Zr5aJlwIjnJ0+ABd79o/sO/fHdvBtXrwdWr+ZVySv6VuTpIycvnb3w+vS3Pb08rYdNHUquXw3/avpn1y5cZoRziMfKhUs3rVz33hfT6wXXZyVcCGBpNIzklKTkRs2b6FQC+8zq65etrtOgHoP/m4++AIk+Me5pXhmdkvZ3qQAs++vT8uDII6B2gwHP1e39VMypbRGHV3H0qGg1/vy+Ujd/+fylLz+Y3bxdq5FjR1Xx93N2cdFYzEsS0rTxc6+/6OaRf/ql6cqMCaJ0ay+m0Xdmv49wtNPN13N3b94xbtLLQTWrk+Pp7VVqoVn/gwJXafASmvDrN3TgwPsH4yMDWy+d/8+uTdvv6t2t58A+JjyqLaLTO2lpqRuWr0ETlA5g6dSmQ0PEjVvoHkh9/u1Xmrdp6ebunpaaev3KtVYd2uqUNH55eO+BzSvX9xjQ26EAYLVs1wpbjpu77tGseunRm2m8Re7it1VfT9f6bfPXGIzLPB+uaUHcmGPnffXj5lUbWrZvg21D3hy2ikW/Lli9aHnX/j1ZychvydOQTedePHN+zGvjegzog2L+YtrM7z6Z07J9aw/P21Yf+SMVnM6PUdNvbUpPT8eSx6eyJ33yHhAK+eDkrV67hqAZXPXtJ3MS4xPHvDqudce2MEiBuJhYNzc3K2W2QNaQ1yAk+NHRI+s2rA/AWr9s1cJf/lw6f9GE997gxaT3Cwo6ZGVm/jD76/OnzjZv3ULKFIkLYedW/L2096B+T70whn4HaG5dvbFDt85tOrXTKWl/lwrAsr8+LT+OnFzcq7UeyL+Um+f4QGHSjbDstMSs5FjOyiopEeoc9dI//3FydsYnyEKnpI+XtDwWLJxQcgP+xlXrtqzaOOyxB3jzRW23rt/87Zu5Li6uL783MSsrixXY3q27QIEBgQE97+5zz/AhlXx9KLl3264VC5c9/eKzJ48cJ7YGe0aL9q3honqt/OlV1IYjoGpQIGk4FbMq636Rg+/gozenuru7Pzl+dEC1qqL8jMkfVPav8tzEF7jcvHrD6aMnHn32SVxRtFXJ1/vDb2b9++uC8Kvhw0c+tHHluoM791NJ9/49h44Y7lPZV9QQExm9evGK/Tv2ZGZktO7Y/oEnH65WIwh0eP1KOFMhJpMq/lX+W7AEsn9Z8Zfl/BT5Dqlok05qAGtiAIB+SG3dqR06OD42TrCD1ef4oSNrl6w8d+psUM2grn174lTy9tF+sRiR7t22E8mAb+qFBLfp2LZTr65IcsHcP86eDFOrc98aN5Fioyc8h88xOzsb78bG/9aeDztXrWb1rn169B3cXxjJWIJ/+t7HOO+cXJxW/r0UbdGoRZOHRj3atFVzQYP0Fz2x4Kc/EuMSwAe97+kn8n0q+wjELC6xnK36Zzld5urm1rlXFwRe2a+KVINIQMnCn/+Ete9nfu3t4924WeiTz4/GmQIvY19/sU4DrWkzMyOTnK1rNl4+d7FucP323Tr2vXcgo4XRuGLR0msXrtRr1KB1x3a4JkV5nSb0Xurx25YEYDGirly4/OI7r/n4+hwrDLCys3OO7T8y+OH7hj/5iBGAxXA9cegYf5F/JZ9KXt5eYMozx08D1zBb6qW5YjONW7CAlcQeNGnVrGGTRrxKdLT89Z///TymhVfen9S9X0/BhW+VyvKhUrGsGWmdl/G517VTkPi1uasDQzr6VhSrRO9KlfhXcMfh6sUrZ0+cefDpEVUC/KRMkdi0ar2Tk1Pzti3F+O/Wr8emFeuOHzyqACwdQSmXigT0S8C7RqMWT83OyUjBaZiRQJBWiQEW3oSrFy4HVAv0qVL54O79GDDwoDVqFlo6c5F+KmW5KF30lkNBwIerq2uL1i2///jLXdWqSgAr7NjJfVt3P/fmi87OzqjSg7v2N2oa2r5rJxZkf/80PyYyhvUoDybGJ5w+cuKbjz+vGlStZbvWVy9eZn2WnJj02vuTTDeMnT0ehn5F90s0EqlTrUY1cSlaz8rIOnn4eGirpoiF/MhbEfsAfOcu1g9pQAjX2VNhi39bmJureXL8M9wlumXm29MT4uI6dO3s5Oy0Z8vOS2fP449gWmetKZyVILDqtap36tnVcugKSvRG/Ai+iv7F1YJNCAqjIqIAEJ5eXh275/uMNq1aN2/OTw1CG4KrUpKT/547H2lM/PAtuuDYwSNffvApgKxN5/bI6sSR4w2bNsYClJmeiR3UxVUlgkK881yNaxavWPDj701aNwcYYUX4/Zu5Vy5ceuGtVxCCWp1z4uDRxLh4laMjlgb0Aa4u3Fiz532lg43o3yN7D1atru3xolyQg33r4zffB8cT3peRnr5y0fLwy9dAJIIG6RGsa87OfHXXsX5IfQY/Y55bSfGJpw4f147PPJscDsSVC5c1a9sSX1tCbPylsxfvHuaMfiKQq2WHNvjgEuITIBvVbjrAKuq3NQ4gJIJFAnzw7qcfgEoRQq5aLb/L4uHtWVOJMVJn58jzddIgVBBJpco+Yj2A8DFaa9H/tXArjUY06kIFQyP8sKMn1y5dhcEVvCjxS5Te/u17Qpo17tKrm5Rpo4moW5EZGZmNmocyJcpZACgv+Ol3Fpx97ukvzyfNrRtXwnkZ/QPzl45BNbUrz9ioaJ2SdnlZSEx2yaHCVLlJwNndu0bHYaVrLi0tLTM9A/WJCeHciTA+PuXk6Dj4kWFPPT/aEuqfkIhnhz0hSGVa//TXbwiz7dyrK0CEQBARpLxnyy4PL8++eVOGf2DA1C8+cnLiu6KOMZFRrLOJnyBIyNU/f7kGFCDeAm2RkZ7x+IAHrl28kpSQZDrAKlZorIDPnAyb/etX6DYJdOJowEr/9EvP8jFUENXIAQ8e3X9IAKzlCxafPXH6pXcnYplXOagat2g6660PD+7ahx1FtHXm2Cksc517dzPyIdViqTKlAB9m4fMsJp7U8OcPv4KcwBXMyxgyZ8z9vEbtmrQC6iIfjT51zkcgKtQz+hhvxba1m/sPvft82NmszCysjwQXc4tnWTEjJWxR2FcYSDidqYScyJsRv375EyD1jenvMOlTElPZonkLkFKLgji8mKiYn5b+4eXtySDETPXPvL/OnAjTCatKSkwiXBfTizCh6cgBGr6bMScuOmbaV59gmOESJPHPL38Nfmio3KvCU30GDwC4g3QHDBsk7GRS54o62Wy49I9/gPV5UNJF+1E2Xg1n53Onz2BVhUE2gmhZVucCo3XIMHKZ77flgzmNC4wQJbFgQaQw39I0P52GBGZKy7q9WtApwCVPgf5DmjWR3m48ay6urjER1qp3jboIgZWPjx01feJ7P336zfK/Fj878fm2ndoJ1iJu3oLZWvXqiO0aDDkWBkIgjNKGTRvhKCwqHyvMwWqFLxs8jZlchzxcvSyHeBP9ipivshmmmVkEm1b2qyyeCgyqxvhhetSpxC4v9XuU7ZJVhSlrlgAxs0CTQ7v2t+3c/qu/f3rjo3cwD2xeuQ4XjyXIxiDRtnOHDt068Q/txYKbVoiDwdm0de0m0lE3Iwhh7nVPXxGHzhSJtePkkRM4rdDZ6tzczMxMPDsSbcQoCOjDVNuld3csHEwr0l2zJB4Z/Tjhz0zKkk7CPNO0VTMtmHB0RNM3a9MS6z1tMYmzX4mc+NhYvJYEeqckJsECYcUSJSxDW3Vqx0rU0akEill6vAQJ8B3fZuEwd11FrKcO4v07dO/MtsqQpqGMh/XL1xLLQrkb4deBmO26dkAbMTsjAfYl4KE4tOcAd7v36+VTxfezKTMAQ7gqnBy16Ip88dcBAvJ+5Fw+fxE9QYguGJo8RNdZa8BTHd5zkLvix/4vrIm0wd2Qpo3IFDQU3M/7Pw9VoDKlvpDfJRjr1OETjAdQ+Pb1W+gCZyenPPnr7r3V0pX3ZB6B0tXtylBdPNi0TXPgoCAJdMXtngN6U/+XH85e9MtfeOtAVwU13X7WSKrArCgboiUBWEZqNvWWBtCsdnO/vd3S2cUZFtDGptZQvuWKtfCFtmj67aJfAB9Aio9ee++TSe9jooNGYYnEkCroxZn44cT3+DflxUmUYVSXLx+lbI0guW8+/uJC2NmXp7zBLCSvBbv7miXabUOs1sTglN/Fps6PVZw0z6gcVe4e7uyEkBez17RiwbLXnrUxvngzURINGjcc9tiDLq4u2C2uX73253e/EvNUdNNv2Xlr0Dj4xXdelWKwxOKS1llo4mjDnrF5zUbM/oAw2mKCWP7Xv+uWrcFxicGDDTVYL3RokAzg5LOCz9O/JgAKnVpkl0WbCKpRXXZfm0TpiuAhke/p7YktgzRzenJCMvat1YtXIldxN7DA4SgugV88LtKW/kvET+6NdE1itqpyvpox1CLulaGPDgcgQvyBHXuxBwBARk8YG5enqxqEBEsPEq2F0sKayExNvMukGVNAVxic2CdPmDmPsFdLKiwliLIijTNOAkYYKbE+ErwllRG2GXFJqBMJBoB0VyQog8IAAgr1qXM3OTGZR4geWzL/n/ydqhoH5J+TcxuR6zxi6DIqIhIQDJbSKVCtRvXJsPzrgr/n/kF0YPP2rf736nj5YNApr3NZALBuo5liAYRODWW8RMv6VfW7GKaFjwIagmKBJlIMYhnrN//jfCoHLCztCdDXAKOCzXFYJXFD848F2JQvphM5QFlCIMQTeKw/+v5T0n/9+BtBfvqqsbo8xjmR6VtWbRj75otdenXVoe9W+A3C6WrWrc1WD51bXAK8WAdmZWUzeYq7CbFxvN3yt6zoU3aTowAsu+lK22aEaFkcaqlJKQIiwAw+IP4WxRlm4ZM5HTzHP3lthGcGhzbE64TZjNkkqFZ1cBgFLp65gBcpMChwxtwv2EuPu4rIZfmDpLF26OSYfgkx6BssK9LWfaZmlrY16tSUV1L0RCjtc/oO0QE5sUbk3zuffSBt/pdXRVrbaEEIms4ts186+muRXG5MplNxAAs5IEl+Lr4u4F2vSpWAWSPHPY27EFY520KiDZMnS+cqfn4iHKRJi6ZEBeEh/evH3zevXl+tZtDDTz+WX1iGjoQ0cEZLej0d53RKqlzUtC61YiiB8cy3ii+YAGSGb0unmBboqFQERYGBhL9Mp4CeSxmR8rt+/n4gSI5CkGeKNM7Ht2dNO37wCCxvW7OparXAx597ysQ+1eO3FcdGmLaLsCgxJc2BTr+AgJOHj9GPYGW6Iy46FmBdtZquMEtas4XKawGos6MWYxn9ASbqBtdjP0rYsVPsYABJsJUEezmXAG5sP4zwhqEh1OHjm78ZxWh9FX+TJcS/v/29Y/1WQk4H3Deo6AAjTpFTJ/732vN6F2y8TWxJuRh2jv4VzNy6EUHCt2AvTsVzaEkKFBehJaWr1G2yBFjQsHiNi41jbxcPsZYlHAoLk3wzjsmVlbIgc0H3Ab0AOhysx8zIjnH0N3UlxMeD86oE+IuNP4SxY+cvZRv6HmPOYjtbbFRs5M1b3EfZ4NSDDH1lTcoDdfW8uy8B1CcPHaM28Qx6uix1mtSwgUIF9hKZQ8pASSkbl8Sx/YeTEhL8q1XFUsWOSwLAd27cRr4oc+LQUY4069C9E5c4ZPHtIsY2ndqDxjS52gBqEZZEnxJjjhYXT9VtWI/zFE4fO0n/koNG37lxO3/b3aV7TqYob+gv0HzMq+MBamxUxMgqFQOrMVSIZG/ZvtW1S1dxEUq3gIM0JF2KBDS75oWCMcZ0bonL4CYh9CA7PXFJk0M6MSGRfsQeIFjGXPf4c6PIJ2q4BP1b1G+b7yK0oEaAPA4mBZJCLUMU7zbssyMBvnjf2WoAOuGl0yuHis/M0aicDcIrIiBvXLsOX4LO1JQU3MTMafg9GYGjXnqWS3ZLXLt8teIZKQkF8PXbVz+tXbICFgY/dB/9pfM0ax62KhNv0KZzO/ktAiounDkvBjy7SbKys3kXkA9j4MjeA5i1GjfX7tSx+59iwbL7LrYNBjG3PPva+BceGcM0xGFIhJUc2XOQwCYLHQHKhvBpE96RbEJDHhlGLA6SatGuNdE8m1ZoYzn7DRnIcpNM/6r+TP3EHyz5YxEb1NcvW+PmofUcmfHHHETUOfvO2N+ekpS0eeUGERZW6iYeevpRQn++m/ElZ/oR4Z6UlLhrw/ZRL4zhLOZS11nqB8W3WbBgFVvDuqWrju4/nJKYTOwRszNWq7GvvyCsdI8++8RXH3762qjn+9w7EGWGzaZ+o+B+Q+6mzoXz/tq3dWevQf3xLG/4by3lSYCB2MxFNFXEjZvfzfqKHLaFY/V59YNJMyd9MOnZV7r268GGUHZ4dexxF6HixdKmU4BthoMeGsr+vteeer5xS+2h8yAqDBXf/zuPLRGvTJv0v/ufnPryW/ePfAjzWGx0LBvuJkx5Q2fBgMYKDg3BaMrGRsL+iPIeOGyQvCGOs+8xsPf2dVveHD2hVae2R/cexNsy6+c5i+b9tXvLzj6D+2OT27hiHfXgo9HZ2yWvp2hax29bDi5C9lFOf22Ku6f7+1/NYDXFnhL8uV++P7v7wN5shmX8syOyqDmwKOUVk0OQu2GAxfa6CSPH1msUzAmxYAtiSSFy4odvi9Ar5haGGUffMVSatGper2H9m9dvslHG+sPbeR/BT+AhPJ6ckCIkX8m30tMvP1cvuD6XnDMXExH1yDOP64y9L6bNYoH0zcK5BF2w15UzGpb9tZi3ABPg3i07Of3BepG0WYeX09SpU41UeCrq8rKwHRQY2qRbi2rBWNP5Acm9vb3Zy2PkQeWWIgEkkJCVkqMx1RLDgo/3MDUlDbXHHm+OS/jfxOdN9bA4OHg4u3m53D6iMCdLnai57VGSugOExERfJaAKChhNnPdzCm3ZVOyQ5xIzflpKCkgL5S1WbFj4OaAZNw17AwlHeHDUCPaUYTlv3Ul7ZiC+PPaUoaGlTfIcoMVajXOJdPbk59OgcaAAEw2x8NIRoxxmTVvsf+MWU9X4yRMABBjwxFEx7DJjBdypR1d5LA4R61DLngDhS6Vy+AKn8iUK0txqx9dLaOvGrTMnTkfeiAiqVYNjshEyBp2b165jGmnWugXFJMlYLgFOzdoWrark7NJaN5ZIajQ1OZX9Vlrnmkaj3fQeXJ818XMTn69fEHdVo04tOMV5eunchezMLM45ZHiI/fD0Kdas65evhR0/xfHQfYcMHPTAEHQbxipi4zjgEesOMgQSBQRWxQzJ8WMszVHqtN6xe2f2GIp6qJwoeKKVwWGCMEwRbDxkMNTRd9o+n1cKrBHEfMhg4FM53t5e7MbnXAnmRtwlYFmsWRgt8DhjUePTKG3uak8+xic0TdPWzfEh0grbV+Gd/gWfVfL1pS0O/khKTOQ4KDH4OQkC4IWpgEPPGW8tO7Tm1CtOlMhIS79+OZwTNxgnvQf3Z0ehUOeSSI0ncq+nqy+nOjfzcfTTzuTqs8lcunT2d6xSgokdqjhQg9cWv5hOc3i8WZMQQMmhvuIWRrjL5zl8pDqvNl3Di8Z7R3AS32Bh3NJrHDmmo6d16qzAy6wt0Zwj6toz/6wBHUp43zGjYthmGGBZBDQ/NGoE5nAxgdAv7KTRrtOcnTGm8o6zfqtdrw6bORgkwBed2irqkq2+OYfinUO8nYK9BQ1MMrxcvC+MW+kf/nE2gjA4MQNzsDtns7F/UGeuu3rpCtYujpBlikMIHPQPy0RrYeLl5Xr+rVcIZjULm/7uvkLIZqnN9Eouxd9ccHwj5fs37NChZihjOzU1lanAy8tLjptVklVTb9WLTm4etfgjbs29/83HWvaPjo6OiYlh+ggKCqIivY8omYoEJAlcSY7IUBdvt5DKkyDCCWWD4keXFN2TIi+pk/Zz8wn0uH2QY3py1lW11uOm88MuItxD8nzmOEk54UpDXxIbjg6Ql+FQBm5RksBnKmGTIHYs6MT1o92H7IoSzJ8oeZyS0G8IvjBn4a/TKYDxnMmXv+hL5jLOgkJFUQYaqJ9WUEK8wBJJVMJUDg1SJr4w/GISaKOklpf0DJ6lDCUFhTQBTCSHCqXaLJvQOCS/edwx0N1rYiNDDcFLRkaGdBfyEKnEmpTPpm+AhWBHrozBRkKqfGGJuHX5nAv2Qpg8gmTyK9Q4aOtJ19aDtKVQPABuWlo61SJ/0aKQlbxzJUpEgvkT9xY9TgJcyPCQdzq3ODcImEVDUCUIZoQzHTPeJM1KN6F4qIEeYdTBC+TJu1uQQa6WCy8vQXAByzl0qw7LOkTqvczeG5exKNz94dounbV+8MzlNwHBni+HONX11Fteb6boNTkvUjHYQfJyYZKTnJTMskYLZwucTYiCIcqbLudXqsR6EinvnuITQ16TQw2RBLritaIrGQD0LP0oH4TiKXjN0k4OanoQoTGTCBu5oTrLOT/nTHL6j5fc7gly7Z8fCSdmHh0y6Dq4YygyDfISEQhK3+kwy8vIS8FyTspHMry52kHu6SFNtjo1l+KykW9tzs4pxYNlfGTjxYND50+ikhkDx43vMCwxMTEyMhK+AgMDfXy0B1CLn+IiLJCE8r91SICoBdOtVqUgmelPmCsMPYtKcPbW817It2ihJDwKjtrjpeInr0271HPI19DyfCnN9FT0NhOW/FAltLVUnvlaUsZSJpVIaZEAK+jkaHnBJlT4R0PGJVC4uDmuVNrjRjW4CIlR0Y3iyK8flWMKVYAJfkVpAgPxr2g+OXykSPdzbyrt5qaiIsUjqUNDsbJCf+ThqtudJacB0M0/eQ5pRjj/5Jn0knzMF+WlgIxCa9qixeR1FpvW9duKGCzDXjC9FRrpNSSjI0xy2MuiUw/LffmKX+euFV3iIizcazq0EUXgXXge0CnApc0wW0C63tek4KbWTA7cly7lCe0UV3iC0k6red9dkBez+3QFQD+7l6nCoCIBRQI6EtACrKxcTYru8RY6xZTLcpNAwc6DfAOzJg9gqcprF2G5sWmuhohRU7GLUPkpEiiJBJQRUxJpKWUVCSgSKJUExNHhpsS5l6p65aESS0Dl60LU9u0T9sWnYBSApVeQWF4BoIpw9ApHyTQsAQVgGZaNckeRgCIBM0nAsarWiaYALDOJ0xzVyP221FcqF6E56LCFOsR3clwUdWkLnWVNNCojxpp6Q6FFkYCdSkAVoA1Fum0vsVM2bYstzIqS31aTd9Co4iLU24PlcIaF3naVTFuXgAKwbL0HFfoVCdiABHQifmyA4juAxEKdorgIjfS4EE4JdwAYqU+5dYdIQAFYd0hHK2wqEqhICTjykRwnlSamBIe5VyS5d0bbhfy2+S5CRSPo6XtNnotQCXLXIxoly6gElNfJqHiUm4oEFAmYRQIcVuPnqsRgmUWW5qpE7rdVdhEak6piwTImHeWeQQkoAMugaJQbigQUCZhRAhy8pElXa9JMPdnfjE0rVemVgOIi1CsWPZnZeR8ZVFyEekSjZBmTgAKwjElHuadIQJGAuSRQSJ2bq1KlnjJIoJDfFhchX940cAxsGRqxh0cVF6E99GJF8FDoQOGKIEBp054l4O3i5ir7uotFWXV3LnyQN8dGu5bgox8WpU2pHAmkVPPOcohxS3DwbKj0i7WMiHQ/t9zYLN6UjFxVrrPNvDKOKpW70+3T89NyMrNzS3OGbU5kojou2aVeoKOH7oH78h7SqNRpDg5eHh4BntrPCpXbLyUbk29uGZvLuhqtycx2a1hdC6AL/9ycXNydbjOe5u5ww8HB28XDz6xsZuXm5JSqdwoTa+hKlylD5SokXwFYFSL2O6XRAPfbHwcsZ575mk0NT/1fZi1nSpTmhAQSa+UmOlzxTFD6xYpGREqQT+KJqECN7//buxP4pqp8D+DZmqRt2iRd0h1oKYvsUhYBBaqCKILiMj4cn8+Pg+MyDx0cUWc+is4857157zOOOjgPfa4DM4PLZ2QYFQRFFBGQRWzLVpbuKUmbNm3StGnW909PuA0habP10ja/fPqJ55577jn3fG+1f88999xWl8glEQ/Rf2VU0pQITRXZgtH9H2oSNzfT6+TliZE31H8jAUrEprmJob5WWSjpopOgyDU27QboUNxl4RZh3F1yPjtst162CTdiTJjg80qH0JZM43ltmbXJEkJZFOFJQJ7luSjdTRaXwyXCq2CCqBMO7YFPEB5kBxVAgBWUBjuiF3CxZ7+jryj8GkQIsMJHG9AjZBlJAqGwW48Aa0CZw6vcG/XqLbTQqFCMPweB9dx2T4CFZRoC6yA3uAD+jQpugz1RC8iSL9s9aOElEw6i7g0qiEqA/j7J0hO7m2k2Cz6DRUDeM6xII1g0j1uI/ycJcllcds9IvChBHGQ/siEQWAABVmAX5EIAAjEXoPESu6nb2RXJfOSYnwwqJAHuvi29DQYjNMF+JbxPEeJdhMGAkB9EAAFWEBhkQwACsRbwjpc04y5hrGUjrc9737apE3Ow+iB09dwiFCHA6sMIuwIJIMAKpII8CEBgAARkPVOqrZiGNQC2kVXpvW9LtwgxByu4IBvBwiT34ELYE1gAAVZgF+RCAAIxF+Bm/MS8ZlQYsQC7b9szBwt/DgIrshEs3EINrIPc4AKXbQ5y8FPCHghAYHgKcDN+hmf3hmavKOo1naBlnqJ9Ss5c3Xr2lYO+BhKlVJ6XIs9WJI9QqqfkDN3nTtyY5O57XZEOWQABVshUKDjIBFwuzwvCRHhacJBdlz5OR5bpWcOdnlnrowx28SzA7ttSoyJxdItiu9wOk8335GnTWt/BcpLHqEbeMyW5QOVbIKy01WBp/KRSOVmTXpIf1oHRF2brYAkxByt6yjirAQFWnF3wYdRdhFZD7mKKpGKpWo4Aa1BdOFmmZ61R+sTqFph6To5qWo5A4HaYbV26jo5TLdaGDsuZthPP7Sl86MqMWQWsuXC/Ww9rW/Y0JKhk/AdYmIMV7sVCeSaAAAu/CRCAAH8CdJfQXNnisjkp2OKvVbQUXIAt5k77YxVgJY1UZczsHWRyO926r85p3z9FYUrdporU8ZnSVHnA03G73EJhkBdOuwUt+xoCHuWX2VMJdSa60biLK2XrYAmxDtbFLNjqVwABVr9EKAABCMRMgGb8UIBFy40m5kX6/riYnQsq8giw+7aUiFWA5ccqFAtzrium6IpiLKfFUfd+RfEDM7kyzi67sVzXekjb1WC2Gay0FIIsK0k9KzertEiS6H19e2ejSbv1FA2D0VGGr+tNxw3s8KJVJYlZCko7ux1tFbqWQ1prvdnW1CUQC2XZSaqSnJzrRkuSe19mzDUaboKt5I6nCMN1Q3kEWPgdgAAE+BPgVmpAgMUfep8t0VBiglJmb+8WDeSrcrJLRzd9Xm1v7TYeOO/6t97xy8adZ3Rbz3In6KJlaOvMXXWVxkONE341ny2efvrF/XZjNyvjaLfRD0uzgSVK67+u1r53kqtE4HLT3C9d/RnjAe3E5xaKZdH+mcMcrF5bpMIRiPY3L5y2UBYCEIh3AazUMAh/A6RpiRRgCQZylQYK4xTj0437GgVuAU1XT8pNZQ5Z8wvby5oyrilIGZ0uS0+yNLTrPjtrKmvuqjU376vNWlBExcY8NpsOqXr1CKXTrs7LKi1kx8ovzB7LnDuy9YA2fW5+yhiqJLlLZ9J9fq79kL5b16nfXZW7ZCwrH/E3FhqNmC7OD0SAFee/AOg+BHgVwEoNvHKH1hg9eWCpFrhsnlcaD9yHXXqq36rv4AIsqTpx0rMLBRdmTCnHZUqSEk6UeZaNsNS2s5NJHqESy71/qqRpckVhmt9JJiikvpUkFGdIlfKKQ/qeStr8CkewySa5D9At1AjOB4cMFYGB/H+WoWKA84QABPgSYH9l8SAhX94htZOg8sw6pycPQiodaaGEVBk71G6yXlTHheiKZSbnK8XJntlX4f2SXFyJPFMh1SR6KtHH4OXieNnzRdcLGyELYAQrZCoUhAAEohagoQiRTELz3I89uzvqylBBbARoPQWqyHSyOZSLQuuF5t4yXj09O9y2bcYudgi3MATbpNt/xrLz9NyDzdDp6LBTnOd9HbhnnbtQP93GLuMPjRSTdRu6HB02qsTe0hPG9ayWx9VC+WfWH7S3XRzhcbuDJOjcaM+J3+zhRtqCFBza2U6r5y3snfWmod2NwXT2CLAG09XAuUAgDgQScxT0H3GbMbw/cnEAc/m62HNv0O0ShHJRKMBydl60oGiI592t8y4wK9d4Hv2jD70AsWrj0dZvtGyTvsXJEs/wlTuM2IrWZah9r7x5Vy3N7mIfUaJEoqBKuFp7E7RmhN1otYUZYNH50LOQYR/V2+wQSVE3RUJuoHGInPSgPk0EWIP68uDkIDD8BCasmz/8OoUe9S3gsNjMJ1uoDEUqMrVnQX/61G89yaKr1GmZGfMKFKPSZGlJNEr0/aPbnR12Vqbf78Ydp5u/qKViionpmfNHUCXyDKpEWP6rL2iSu9/h4kTJpBdK/TKxCYEBEkCANUCwqBYCEIAABLwC2k8rWcyUce0IirE8uW5B637P2JUkVTrm4VlsRQbapAlPTkuo0RWVNx5spG+RVDT232f3rsjgppEq78oOtBcfCFwWAQRYl4UdjUIAAhCICwGn1a7ddrppRzX1NiFNnn/rBNZtuj/IpklJUqQiSe+y/qbK5kvv7tG8PXaU9cJ9Rq+dW8CGqcQKeg1TbyXmqlZaUstbBv+AwGUSQIB1meDRLAQgAIHhKNBV3956tJHip+6WTquuw1TRTOuLUkdpfs+o+6Zw67PTqge03jqFR1ZtR8tRbdqUHJvJSgfqPuldd5TjSUiR0buWaUX19iP6tuN6WjTL1tZFq7RTvjxf0Xmu3d5qbT5Qnz4jz9Fp91SyLUAlXG1IQIAfAQRY/DijFQhAAAJxIdD6bSP9+HVVWaIZceckbno725u1ZHTduxWUpkVEa2RiNuaUMjkjIVXqVwMFZ5mLRjVtq6JZ6mde/I4dXvzzmeopOVmLiqrPHaWcmjd+qNtYwSpJHqdWTtEYvqxjJfENgcsigADrsrCjUQhAAALDS0AoEMl6b9IJJfRCwGR5joJeJq0oTleOzbx0jQPN1aNo3YTGjypdVhrvckqU0rQ5eSNum2g6Y2g7rKchK1+g/JvHu+3O5l119CYcyhcnScRJnvcMZswsoPUFtB/Siw7tnkpSpaqZ2SPvnNypbW/9VutXiW+FSENgoAUQYA20MOqHAAQgMPwFUorSSzYsDaufNC6Vc31x9rWjbe1WepVygkLGgjDlFZpLq6IV1EatnEqREy15Re+ETkiReyfLCwX0vp2sa0ZRJZ5VBlLkrBJa8P3SSsI6PRSGQJQCCLCiBMThEIAABCAQuQBFRTK1Z9X1UD40c4t7BeFF5YVCqSrUSi46EBsQGDCBi8ZgB6wVVAwBCEAAAhCAAATiSAABVhxdbHQVAhCAAAQgAAF+BBBg8eOMViAAAQhAAAIQiCMBBFhxdLHRVQhAAAIQgAAE+BFAgMWPM1qBAAQgAAEIQCCOBBBgxdHFRlchAAEIQAACEOBHAAEWP85oBQIQgAAEIACBOBJAgBVHFxtdhQAEIAABCECAHwEEWPw4oxUIQAACEIAABOJIAAFWHF1sdBUCEIAABCAAAX4EEGDx44xWIAABCEAAAhCIIwEEWHF0sdFVCEAAAhCAAAT4EUCAxY8zWoEABCAAAQhAII4EEGDF0cVGVyEAAQhAAAIQ4EcAARY/zmgFAhCAAAQgAIE4EkCAFUcXG12FAAQgAAEIQIAfAQRY/DijFQhAAAIQgAAE4kgAAVYcXWx0FQIQgAAEIAABfgQQYPHjjFYgAAEIQAACEIgjAQRYcXSx0VUIQAACEIAABPgRQIDFjzNagQAEIAABCEAgjgQQYMXRxUZXIQABCEAAAhDgR0DCTzNoBQIQgAAEIAABCIQr4HS5DOZWfbshPUWdq9IIhcJwa/At7xa4W8xtDUZderIqS5khlST47o1tGgFWbD1RGwQgAAEIQAACEQpsK/tqS/muF+94yu12/+Po5++Xf37YUN3hcrDq8mUpC/ImTc0dN2vU5Fmjp4bexhldzTdnDpc1Vu5tOHayo5k7sESVv3zcNStn3ZSrzlq39Y8aRdqjN3QNzAAADftJREFU19/L7Y0ygQArSkAcDgEIQAACEIBAbAS0bU1/rdrftPGXRwzVrQ6rJiHpZ9NuvjL/igm5xWZrR0XD6YN1x17Y/zfTXtuaKUufXvJASqKi74btTse7ez96/Os3nG73bSNKVk1fNiV/XK4q62xTbVnDqQ+Of/ncd5vpZ2ne5E+1FfcWX913bWHtRYAVFhcKQwACEIAABCAwUAKOnsGqz3UnqYFpytyNK/+jOGsk19iVIyfeO2/FA3Un/2XzMy+Vf/pFzZH1y9f2MZRV3dyw9h+/39Z4TCwUbl721C3TF3FVFWbmL5o47/55t6/+4D+31H9P0RXtYq1zZaJMYJJ7lIA4HAIQgAAEIACB2Ag4XE5WEUVXH6/6o290xTUwdcQV2+9/hQpUmHQL//KLvx/ewe3yTZTXnZrz+k8pukqTyD9b+Tvf6IorlqZQvX3vCz8umsNybE7vvUiuQDQJBFjR6OFYCEAAAhCAAARiJuC4EOL8etGD6QpVsHpHZeb/3x3PsL1rdr5KU+D9Stoc9ic+fsnktFH+HxY9Mm9MiV8BblMmkT5z40M0xEU5CLA4FiQgAAEIQAACEBg+AmwEa1n+1OsnzO27V5Pyx9KcKipjsHe9sP01v8J/2b91r+EcZdK8+KVTS/32+m2OzMhbN+suysQtQj8ZbEIAAhCAAAQgMBwEWIB138zloSzH8NO5d7A+v1X51e6TB7j+1xkan/7qTba5ZvadybJEblewxO3TF9MujGAF80E+BCAAAQhAAAJDWIAe+pMKRXOLp4fSh6vHlkxNzWEl1+3sHcTasGczt7LDbT2RU7+1FWoK5qYX2lz2fkuGXgBPEYZuhZIQgAAEIAABCAygwIwRE19Jy1EmpYTShkgomqYpLjOdp8JHaPVQS7s6WUnpbxuOscOzpckaZXooVQkFwqdL76syNIRSOMQyCLBChEIxCEAAAhCAAAQGVuCmqQvDaqBAlcWVrzE0UIDVYe08bKxnmZPUBRQ5cQX6Tlw/cV7fBcLdi6cIwxVDeQhAAAIQgAAEBoVAnkrDnUdVsyeuqvUZhSpUe28gcmX4TCDA4lMbbUEAAhCAAAQgEDOB7NRMrq5T+mpKszCLZRaosrm9/CcQYPFvjhYhAAEIQAACEIiBgO8TgtWtWqqx3qjj6lVIk7g0/wnMweLfHC1CAAIQgAAEINAr8NHhHdo2fe+2T+pYS11Tt7kws8Anrzd5Tl/LbVS0aR/f/mrl+SouZ9OJXaetLdymb0Lf3qw3tZRoRucrAs2CFwpXX/evvuUjSCPAigANh0AAAhCAAAQgEDMBvbnlo5Nff9faGy2xqlUS2WhltlsiSbEEfq5QbzFyJ+GiRUctbbaetxmyzObOdsrhCvgmDJ3t9aamcy31epvFN5/SxUlpCwqm+GVGsIkAKwI0HAIBCEAAAhCAQMwEHi69m35+qD2x/K9P0crsrN53b3z81umLpJKEPpp5/IPflRtqWIGn59x1+4wlxxtOz3zrEZaTJBRtvPBGnYCVOF2uQ1XlP/rgWa7RTUufWFGymBaACFg+rMwYVBFWeygMAQhAAAIQgAAELhWYNnLCLUWzWf6CzOIfzbqp7+iKSh5r9kxsZ5/ZRVMpMT53dGGi9yWGpy0tpq6OC/sD/FMsEl1VPG3V5CVs3wh56m0lN8QkuqIKEWAFEEcWBCAAAQhAAAL8C2Qmq1mjhar+V1j4oe4ke+EgHXJ91vj8NM8hYpH47onXcWf+SdluLh0skav0Poo4KiUzlFf0BKvHLx8Blh8INiEAAQhAAAIQuMwCoQQ6b+/7iJ2lWCj87dLV3Bk/vGDlSLlnSXf6vLzvPbuznxfghL4YKaszxG8EWCFCoRgEIAABCEAAAgMr4HLTVPWQPtXNDW9Wekennp+9cnLBOO6wNIXq5Zt+zjaPmfW7ju/jdgVMuAVulu90eRMBi4WbiQArXDGUhwAEIAABCEBgQAS4AKvT3t1HA/TawSe3vsgKzFAXPFJ6t1/hxZOvvn/sApb5y50bzuhq/Ar4blrtNrbpDDm88z08WBoBVjAZ5EMAAhCAAAQgwKsAPdbH2tOaDcEabjQ23fnOE59qK6gALanwpxVPJ0rlfoXprt+6pY8s1Iyh/EqL4YZ3Hvu+5rhfGW7TcGGtB7vPEg/c3ogTCLAipsOBEIAABCAAAQjEUkCVmMqqo9nrqzY9c0J7lgu5aHCLlhWlJUmXvf3YvpZqKvbY5Bv3/OxN35uDvqeiSU3f8sArLy34iVQo0tksSzb94q09H1bUV3Y7vONVbre7oVX3/D/X/8/RrezArCTv44e+9UScxjpYEdPhQAhAAAIQgAAEYimwdslPfjx72Zcn979fvvNvVQfoh9YanaMZk5Ws/rK+rM5qYo1NSNH8Yema+eNm9t22TCJ9cOHK0nFXPfnPl3bqTqze/bpgtyBVLF1SMM3hcu7TnaLAi2qYnJp9z5QbFk+YNzansO8Kw9qLACssLhSGAAQgAAEIQGAABXLVmnvm3kI/Nc0N55rrzrc1a9v1tcbzpflTp+SOGZ9dNCZrZJ46O5THDNlZUti05cFXDKbWs021p3TVFY1njFbzmIyCa4tn0gINBWk543OLaUGsmHcJAVbMSVEhBCAAAQhAAALRCozKzKefaGvpOZ6mZGWmptPPnOLpMakwlEpCDdlc7lg+uxjKmaEMBCAAAQhAAAIQGGwCNHkrlFPqJ8BSy72vV2zt9N74DKVSlIEABCAAAQhAAALDUoBeFM36pU4M/ApqtrefACsnJZ2VO29uGZZM6BQEIAABCEAAAhAIXYCLiLgYKeCxoQZYte36gMcjEwIQgAAEIAABCMSPQH17E+tsjsI7CBWw7/0EWGmJqdkpaXTk7qqj9ExjwCqQCQEIQAACEIAABOJBgCZgfXHuMPU0KUFalJbbR5f7CbDoMcibx82j49ut5m/rKrinIkOc4dVHw9gFAQhAAAIQgAAEhpbAKUPduVYtnfN1o2fJJVJKsIiIAiQuRmI96ifAokLLxs1lRTce/UzUs1AE1eV0YjSLqeAbAhCAAAQgAIF4EaBYiHV1+XjP8JNvRMRiJA6i/wBrQeGVuamZdMB75btOtdb7VcdVhAQEIAABCEAAAhAYxgI0++q1g1uog6mypJvHzaEEF2DR8JVYLPbte/8BllQsea70Pk8tAvdvvvkzLf5A1dntdt9akIYABCAAAQhAAALDWICCn2e/eLPb6aA+rr3mbqVcQQkuIqLhK4nkosXb+w+w6Pi7py6aqBlFiT115a8f30b3B7u7u10XXnlN+fhAAAIQgAAEIACBYSzw2qGtHxz7kjpIt/Uemb2C9dThcFitVhq+ougq7BEsqkIsFG1Y/oRM7AnN3ji+/ZOagzSC1dXVxWrHNwQgAAEIQAACEBjGAjvOfPfkZ3+iDoqEgg3LHk+UyChN400UXdE3hVaJiYlhT3JnXjPyxm+4ZS1LP3dw0/+WfWzuMNPIGMvBNwQgAAEIQAACEBh+AhTqvH5o6x2bn3H2xDz/tfjhRcUzWTdp+Kqjo4PSFGAlJSX59V38/PPP+2UF25yUVUTR2Z6aMipwuOl0ue7s9OyxmSnqYOWRDwEIQAACEIAABIauAC3avmbb+t/v3czGkx6YsWxd6X1spIomSlF01dbWRrOvkpOT1Wq13wiWMNxRqD9/v331py+zRUclIvGqkqUPzV4xNr1g6PLhzCEAAQhAAAIQgICvQG2b7p3vt63f//cuRzfl053B3y568NGr7mBRFMVONFFKr9fTLUKZTJaVlUUxlu/hlA47wKJj9pw7ev+W/260GLi6KMBaMnZWkTqP3suTmayiwIvbhQQEIAABCEAAAhAY5AJOt8tgadN1tNYYdTvOHjymr+JOODNZ/cataxcXz2I5FF3Ro34tLS0mk4luDiqVSo1G4zd8RSUjCbBoWMxoalu/98PXyreZ7BbuDJCAAAQgAAEIQAACw0ZAIU1cM++u1VfdTgnWKRZd0Z1Bo9FIQRUNXFF0RYNYl3Y5kgCLaqE58xS41Zyv31FzZE9jxX7dCbYyxKUNIAcCEIAABCAAAQgMIYEEkWRB4TRaq33FhPnpSUruzGmAie4JUmhFIRBFV/TkYEZGxqU3B1n5CAMsOpgmz1MERx9asqHb5Wi0GTsEtpZuc4vVxJ0KEhCAAAQgAAEIQGBICFAsRTOdshVpEzSFtFa77zlTaEXRTmdnZ3t7O82+ouhKLpenpaWlpqb6FvNNRx5gUS1sHItCOZvNRoNmtMqWoueTkJBAdyWpefbxbQ9pCEAAAhCAAAQgMPgFKLChD4VWbL0rembQYrFQDj02SIsyUHQVbOyKdS2qAIuqoIYpoKMYiyZ80ZgWNUxBlVQqpciOrWrq9+7DwQ+KM4QABCAAAQhAIM4FuNCKhpDotiBFOARCIQ0NIVF0RYsyBJx35YsWbYDF6qKGzWYz3ZKkATQK9Cjq8m0DaQhAAAIQgAAEIDBEBWjkiO7L0YeCKnpmkAauKKffvsQmwGLNUJhFo1n0YW8qpOiPffo9CRSAAAQgAAEIQAACg0qATXOib7ojR/PZaeCK7s6Ffl8ulgEW50KDWBRs0QejWZwJEhCAAAQgAAEIDBUBiqsolmKTnei2YChDVn5dG5AAy68NbEIAAhCAAAQgAIG4EhDFVW/RWQhAAAIQgAAEIMCDAAIsHpDRBAQgAAEIQAAC8SWAACu+rjd6CwEIQAACEIAADwIIsHhARhMQgAAEIAABCMSXAAKs+Lre6C0EIAABCEAAAjwI/D81DmOapIuFNgAAAABJRU5ErkJggg=="
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
+    "tags": []
+   },
+   "source": [
+    "### Pandas\n",
+    "![image.png](attachment:4f3ffb45-6681-426e-a674-87ff7d3a7472.png)\n",
+    "(Source: https://www.geeksforgeeks.org/python-pandas-dataframe/)\n",
+    "\n",
+    "### Xarray\n",
+    "![image.png](attachment:1f171b31-582b-4003-be00-7d731d031ab9.png)\n",
+    "(Source: https://docs.xarray.dev/)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 1. Read in CMIP6 data: We will skip this next part, but you can check it later to read data: \n",
+    "#### Import python packages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "xr.set_options(display_style='html')\n",
+    "import intake\n",
+    "import cftime\n",
+    "import matplotlib.pyplot as plt\n",
+    "import cartopy.crs as ccrs\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import datetime\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Open CMIP6 online catalog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<p><strong>pangeo-cmip6 catalog with 7674 dataset(s) from 514818 asset(s)</strong>:</p> <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>unique</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>activity_id</th>\n",
+       "      <td>18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>institution_id</th>\n",
+       "      <td>36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_id</th>\n",
+       "      <td>88</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>experiment_id</th>\n",
+       "      <td>170</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>member_id</th>\n",
+       "      <td>657</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>table_id</th>\n",
+       "      <td>37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>variable_id</th>\n",
+       "      <td>700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>grid_label</th>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>zstore</th>\n",
+       "      <td>514818</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <td>60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>version</th>\n",
+       "      <td>736</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>derived_variable_id</th>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cat_url = \"https://storage.googleapis.com/cmip6/pangeo-cmip6.json\"\n",
+    "col = intake.open_esm_datastore(cat_url)\n",
+    "col"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "### Search corresponding data "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Please check [here](https://pangeo-data.github.io/escience-2022/pangeo101/data_discovery.html?highlight=cmip6) for info about CMIP and variables :) \n",
+    "\n",
+    "Particularly useful is maybe the variable search which you find here: https://clipc-services.ceda.ac.uk/dreq/mipVars.html "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>activity_id</th>\n",
+       "      <th>institution_id</th>\n",
+       "      <th>source_id</th>\n",
+       "      <th>experiment_id</th>\n",
+       "      <th>member_id</th>\n",
+       "      <th>table_id</th>\n",
+       "      <th>variable_id</th>\n",
+       "      <th>grid_label</th>\n",
+       "      <th>zstore</th>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <th>version</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>CMIP</td>\n",
+       "      <td>NCAR</td>\n",
+       "      <td>CESM2</td>\n",
+       "      <td>historical</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>fx</td>\n",
+       "      <td>areacella</td>\n",
+       "      <td>gn</td>\n",
+       "      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>20190308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>CMIP</td>\n",
+       "      <td>NCAR</td>\n",
+       "      <td>CESM2</td>\n",
+       "      <td>historical</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>AERmon</td>\n",
+       "      <td>mmrso4</td>\n",
+       "      <td>gn</td>\n",
+       "      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>20190308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>CMIP</td>\n",
+       "      <td>NCAR</td>\n",
+       "      <td>CESM2</td>\n",
+       "      <td>historical</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>Amon</td>\n",
+       "      <td>hurs</td>\n",
+       "      <td>gn</td>\n",
+       "      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>20190308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>CMIP</td>\n",
+       "      <td>NCAR</td>\n",
+       "      <td>CESM2</td>\n",
+       "      <td>historical</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>Amon</td>\n",
+       "      <td>tas</td>\n",
+       "      <td>gn</td>\n",
+       "      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>20190308</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  activity_id institution_id source_id experiment_id member_id table_id  \\\n",
+       "0        CMIP           NCAR     CESM2    historical  r1i1p1f1       fx   \n",
+       "1        CMIP           NCAR     CESM2    historical  r1i1p1f1   AERmon   \n",
+       "2        CMIP           NCAR     CESM2    historical  r1i1p1f1     Amon   \n",
+       "3        CMIP           NCAR     CESM2    historical  r1i1p1f1     Amon   \n",
+       "\n",
+       "  variable_id grid_label                                             zstore  \\\n",
+       "0   areacella         gn  gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...   \n",
+       "1      mmrso4         gn  gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...   \n",
+       "2        hurs         gn  gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...   \n",
+       "3         tas         gn  gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...   \n",
+       "\n",
+       "   dcpp_init_year   version  \n",
+       "0             NaN  20190308  \n",
+       "1             NaN  20190308  \n",
+       "2             NaN  20190308  \n",
+       "3             NaN  20190308  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat = col.search(source_id=['CESM2'], experiment_id=['historical'], table_id=['Amon','fx','AERmon'], \n",
+    "                 variable_id=['tas','hurs', 'areacella','mmrso4' ], member_id=['r1i1p1f1'])\n",
+    "cat.df\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Create dictionary from the list of datasets we found\n",
+    "- This step may take several minutes so be patient!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
+      "\t'activity_id.institution_id.source_id.experiment_id.table_id.grid_label'\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
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+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
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+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='3' class='' max='3' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [3/3 00:11&lt;00:00]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dset_dict = cat.to_dataset_dict(zarr_kwargs={'use_cftime':True})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['CMIP.NCAR.CESM2.historical.fx.gn',\n",
+       " 'CMIP.NCAR.CESM2.historical.AERmon.gn',\n",
+       " 'CMIP.NCAR.CESM2.historical.Amon.gn']"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "list(dset_dict.keys())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'CMIP.NCAR.CESM2.historical.fx.gn': <xarray.Dataset> Size: 229kB\n",
+       " Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                      nbnd: 2)\n",
+       " Coordinates:\n",
+       "   * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "     lat_bnds        (lat, nbnd) float32 2kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "   * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "     lon_bnds        (lon, nbnd) float32 2kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "   * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "   * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       " Dimensions without coordinates: nbnd\n",
+       " Data variables:\n",
+       "     areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       " Attributes: (12/60)\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     activity_id:                      CMIP\n",
+       "     branch_method:                    standard\n",
+       "     branch_time_in_child:             674885.0\n",
+       "     branch_time_in_parent:            219000.0\n",
+       "     case_id:                          15\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:variable_id:     areacella\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "     intake_esm_attrs:version:         20190308\n",
+       "     intake_esm_attrs:_data_format_:   zarr\n",
+       "     intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn,\n",
+       " 'CMIP.NCAR.CESM2.historical.AERmon.gn': <xarray.Dataset> Size: 14GB\n",
+       " Dimensions:         (lev: 32, nbnd: 2, lat: 192, lon: 288, member_id: 1,\n",
+       "                      dcpp_init_year: 1, time: 1980)\n",
+       " Coordinates:\n",
+       "     a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "     b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "   * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "     lat_bnds        (lat, nbnd) float64 3kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "   * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "     lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "   * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "     lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "   * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "     time_bnds       (time, nbnd) object 32kB dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
+       "   * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "   * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       " Dimensions without coordinates: nbnd\n",
+       " Data variables:\n",
+       "     a               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "     b               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "     mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array<chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray>\n",
+       "     p0              float32 4B ...\n",
+       "     ps              (time, lat, lon) float32 438MB dask.array<chunksize=(10, 192, 288), meta=np.ndarray>\n",
+       " Attributes: (12/61)\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     activity_id:                      CMIP\n",
+       "     branch_method:                    standard\n",
+       "     branch_time_in_child:             674885.0\n",
+       "     branch_time_in_parent:            219000.0\n",
+       "     case_id:                          15\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:variable_id:     mmrso4\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "     intake_esm_attrs:version:         20190308\n",
+       "     intake_esm_attrs:_data_format_:   zarr\n",
+       "     intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.AERmon.gn,\n",
+       " 'CMIP.NCAR.CESM2.historical.Amon.gn': <xarray.Dataset> Size: 876MB\n",
+       " Dimensions:         (member_id: 1, dcpp_init_year: 1, time: 1980, lat: 192,\n",
+       "                      lon: 288, nbnd: 2)\n",
+       " Coordinates:\n",
+       "   * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "     lat_bnds        (lat, nbnd) float32 2kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "   * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "     lon_bnds        (lon, nbnd) float32 2kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "   * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "     time_bnds       (time, nbnd) object 32kB dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
+       "   * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "   * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       " Dimensions without coordinates: nbnd\n",
+       " Data variables:\n",
+       "     hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       "     tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       " Attributes: (12/54)\n",
+       "     Conventions:                      CF-1.7 CMIP-6.2\n",
+       "     activity_id:                      CMIP\n",
+       "     branch_method:                    standard\n",
+       "     branch_time_in_child:             674885.0\n",
+       "     branch_time_in_parent:            219000.0\n",
+       "     case_id:                          15\n",
+       "     ...                               ...\n",
+       "     intake_esm_attrs:member_id:       r1i1p1f1\n",
+       "     intake_esm_attrs:table_id:        Amon\n",
+       "     intake_esm_attrs:grid_label:      gn\n",
+       "     intake_esm_attrs:version:         20190308\n",
+       "     intake_esm_attrs:_data_format_:   zarr\n",
+       "     intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.Amon.gn}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dset_dict"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Open dataset\n",
+    "\n",
+    "- Use `xarray` python package to analyze netCDF dataset\n",
+    "- `open_dataset` allows to get all the metadata without loading data into memory. \n",
+    "- with `xarray`, we only load into memory what is needed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "ds1 = dset_dict['CMIP.NCAR.CESM2.historical.Amon.gn']\n",
+    "ds2 = dset_dict['CMIP.NCAR.CESM2.historical.fx.gn']\n",
+    "ds3 = dset_dict['CMIP.NCAR.CESM2.historical.AERmon.gn']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "  --xr-background-color-row-odd: #313131;\n",
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+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 876MB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, time: 1980, lat: 192,\n",
+       "                     lon: 288, nbnd: 2)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "    lat_bnds        (lat, nbnd) float32 2kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float32 2kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;\n",
+       "Attributes: (12/54)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:member_id:       r1i1p1f1\n",
+       "    intake_esm_attrs:table_id:        Amon\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.Amon.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-19cad1a0-3409-49eb-9c05-2e91922b629d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-19cad1a0-3409-49eb-9c05-2e91922b629d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8f2a1b68-aa56-4f1a-9d28-85a7396c8882' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8f2a1b68-aa56-4f1a-9d28-85a7396c8882' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-6daf1120-1ad0-4209-bcb0-6de1c203c7b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6daf1120-1ad0-4209-bcb0-6de1c203c7b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b206aed-5c0b-42fd-88d9-276f8e774795' class='xr-var-data-in' type='checkbox'><label for='data-1b206aed-5c0b-42fd-88d9-276f8e774795' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, nbnd)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;</div><input id='attrs-5bd66430-8c69-45c3-8f7d-f36815f6f316' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5bd66430-8c69-45c3-8f7d-f36815f6f316' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-addb38f3-374b-4c65-a4d7-4df850924178' class='xr-var-data-in' type='checkbox'><label for='data-addb38f3-374b-4c65-a4d7-4df850924178' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 kiB </td>\n",
+       "                        <td> 1.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (192, 2) </td>\n",
+       "                        <td> (192, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.60913412115106,0.0 25.60913412115106,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.804567\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.609134\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.609134,60.000000)\">192</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-9c64ff37-717d-4468-b27b-87fc3a42a398' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c64ff37-717d-4468-b27b-87fc3a42a398' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2bef3518-effb-471f-86ad-c511f8c11bfd' class='xr-var-data-in' type='checkbox'><label for='data-2bef3518-effb-471f-86ad-c511f8c11bfd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-a0387bbd-b232-4efa-a445-032530a5146c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0387bbd-b232-4efa-a445-032530a5146c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fb657a4-ec9d-48ff-b938-abb8d6144076' class='xr-var-data-in' type='checkbox'><label for='data-3fb657a4-ec9d-48ff-b938-abb8d6144076' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.25 kiB </td>\n",
+       "                        <td> 2.25 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
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+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-1b2e2506-f9d5-46b2-adf5-824ba7091ad6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b2e2506-f9d5-46b2-adf5-824ba7091ad6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a54bd7c1-8a33-441a-996a-fead39d549fe' class='xr-var-data-in' type='checkbox'><label for='data-a54bd7c1-8a33-441a-996a-fead39d549fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-7aa31124-3287-4413-9f9d-8d1cc21899a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7aa31124-3287-4413-9f9d-8d1cc21899a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18d4fe6d-226c-47cd-b569-8cd133697bf4' class='xr-var-data-in' type='checkbox'><label for='data-18d4fe6d-226c-47cd-b569-8cd133697bf4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-fd99a088-7101-45d3-8096-130a86412e9d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd99a088-7101-45d3-8096-130a86412e9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecc88eb2-c6e1-4523-9f04-080aa6a17bdf' class='xr-var-data-in' type='checkbox'><label for='data-ecc88eb2-c6e1-4523-9f04-080aa6a17bdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-1a0e6776-97f1-4dbc-a895-ca9518c010a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a0e6776-97f1-4dbc-a895-ca9518c010a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1dd16820-715a-47f5-af1b-8c17b67fbdd0' class='xr-var-data-in' type='checkbox'><label for='data-1dd16820-715a-47f5-af1b-8c17b67fbdd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b128bf1f-fa65-4177-967f-5835953e3cc0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b128bf1f-fa65-4177-967f-5835953e3cc0' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-faeb3046-321c-489a-a084-699ec6e4cf5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-faeb3046-321c-489a-a084-699ec6e4cf5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30a1fcf3-21f9-4f2f-a1b1-cb2cb9f22f59' class='xr-var-data-in' type='checkbox'><label for='data-30a1fcf3-21f9-4f2f-a1b1-cb2cb9f22f59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 417.66 MiB </td>\n",
+       "                        <td> 126.56 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 1980, 192, 288) </td>\n",
+       "                        <td> (1, 1, 600, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 4 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
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+       "        </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-3a3eaabb-27dc-4c00-b719-a39e5d8fff1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a3eaabb-27dc-4c00-b719-a39e5d8fff1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a55f7f7c-f661-48bb-862b-8e1bb435f091' class='xr-var-data-in' type='checkbox'><label for='data-a55f7f7c-f661-48bb-862b-8e1bb435f091' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 417.66 MiB </td>\n",
+       "                        <td> 126.56 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 1980, 192, 288) </td>\n",
+       "                        <td> (1, 1, 600, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 4 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"351\" height=\"159\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "\n",
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+       "  <text x=\"120.294118\" y=\"93.719750\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,120.294118,93.719750)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-229fc39d-795e-499b-bca6-a0bff06439b4' class='xr-section-summary-in' type='checkbox'  ><label for='section-229fc39d-795e-499b-bca6-a0bff06439b4' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4a1f9dbf-e8f3-4714-a489-e2763aa20ede' class='xr-index-data-in' type='checkbox'/><label for='index-4a1f9dbf-e8f3-4714-a489-e2763aa20ede' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-95145dd8-4bed-44b3-8cf2-955cdd71858a' class='xr-index-data-in' type='checkbox'/><label for='index-95145dd8-4bed-44b3-8cf2-955cdd71858a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-28b50fab-c4d8-40eb-bc31-12cfe1ec7c3d' class='xr-index-data-in' type='checkbox'/><label for='index-28b50fab-c4d8-40eb-bc31-12cfe1ec7c3d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,\n",
+       "             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,\n",
+       "             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,\n",
+       "             1850-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,\n",
+       "             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,\n",
+       "             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,\n",
+       "             2014-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a3d1f863-73fb-4531-b3e1-417ad9100297' class='xr-index-data-in' type='checkbox'/><label for='index-a3d1f863-73fb-4531-b3e1-417ad9100297' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-edff9bda-e3e8-4844-ab38-23c849967fde' class='xr-index-data-in' type='checkbox'/><label for='index-edff9bda-e3e8-4844-ab38-23c849967fde' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f8f37539-6046-479b-8ae8-0f01515f42b9' class='xr-section-summary-in' type='checkbox'  ><label for='section-f8f37539-6046-479b-8ae8-0f01515f42b9' class='xr-section-summary' >Attributes: <span>(54)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>Amon</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.Amon.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 876MB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, time: 1980, lat: 192,\n",
+       "                     lon: 288, nbnd: 2)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "    lat_bnds        (lat, nbnd) float32 2kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float32 2kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       "Attributes: (12/54)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:member_id:       r1i1p1f1\n",
+       "    intake_esm_attrs:table_id:        Amon\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.Amon.gn"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "  margin-top: 0;\n",
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+       "  font-weight: 500;\n",
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+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
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+       "\n",
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+       "  color: var(--xr-font-color2);\n",
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+       "  color: var(--xr-disabled-color);\n",
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+       ".xr-section-summary-in:checked + label:before {\n",
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+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
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+       ".xr-section-inline-details {\n",
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+       "  grid-column: 1;\n",
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+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
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+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
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+       "  display: none;\n",
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+       "}\n",
+       "\n",
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+       ".xr-var-dims:hover,\n",
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+       ".xr-index-data {\n",
+       "  display: none;\n",
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+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
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+       ".xr-index-data {\n",
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+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
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+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
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+       "\n",
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+       ".xr-icon-database,\n",
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+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
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+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 14GB\n",
+       "Dimensions:         (lev: 32, nbnd: 2, lat: 192, lon: 288, member_id: 1,\n",
+       "                     dcpp_init_year: 1, time: 1980)\n",
+       "Coordinates:\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "    lat_bnds        (lat, nbnd) float64 3kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 438MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;\n",
+       "Attributes: (12/61)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     mmrso4\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.AERmon.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c166d8ac-7778-48a6-9330-9bc7cb6ea739' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c166d8ac-7778-48a6-9330-9bc7cb6ea739' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lev</span>: 32</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-92ac6c37-f641-4bd3-9225-44ce54fbcf2f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-92ac6c37-f641-4bd3-9225-44ce54fbcf2f' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-deed4b9b-e2a3-4373-a710-ce2c21846f30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-deed4b9b-e2a3-4373-a710-ce2c21846f30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d08035a-7364-42fe-ac9e-c0cb866fe462' class='xr-var-data-in' type='checkbox'><label for='data-5d08035a-7364-42fe-ac9e-c0cb866fe462' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-6f2ffd96-ef07-4b14-b3fc-7d28fa3b6fe4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f2ffd96-ef07-4b14-b3fc-7d28fa3b6fe4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f255b7f0-c048-4225-8913-d7fce636e50b' class='xr-var-data-in' type='checkbox'><label for='data-f255b7f0-c048-4225-8913-d7fce636e50b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-01d9b51c-7a26-4aec-b47a-470f2f658084' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01d9b51c-7a26-4aec-b47a-470f2f658084' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a31eaf-fe25-48f4-bdce-e9f8e924d822' class='xr-var-data-in' type='checkbox'><label for='data-84a31eaf-fe25-48f4-bdce-e9f8e924d822' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;</div><input id='attrs-8130a583-5f51-4f2e-af44-9e8987a3e1cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8130a583-5f51-4f2e-af44-9e8987a3e1cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25cdac0f-a60e-46b7-85f5-7791b4d4546c' class='xr-var-data-in' type='checkbox'><label for='data-25cdac0f-a60e-46b7-85f5-7791b4d4546c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 3.00 kiB </td>\n",
+       "                        <td> 3.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (192, 2) </td>\n",
+       "                        <td> (192, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.60913412115106,0.0 25.60913412115106,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.804567\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.609134\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.609134,60.000000)\">192</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-1ac05413-c935-4ec8-a48f-04649cc082cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ac05413-c935-4ec8-a48f-04649cc082cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90b761f3-6a54-4ac5-b30d-5d6e8ed51a84' class='xr-var-data-in' type='checkbox'><label for='data-90b761f3-6a54-4ac5-b30d-5d6e8ed51a84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,\n",
+       "        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,\n",
+       "       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,\n",
+       "       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,\n",
+       "       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,\n",
+       "       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,\n",
+       "       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-5ec9b59f-e16f-4716-8c82-904ab9943b16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ec9b59f-e16f-4716-8c82-904ab9943b16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28094f69-d286-4fe0-b73f-40135852211f' class='xr-var-data-in' type='checkbox'><label for='data-28094f69-d286-4fe0-b73f-40135852211f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-ca3cad7c-74e6-4832-8e61-179e7cdfceff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca3cad7c-74e6-4832-8e61-179e7cdfceff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0e37d9e-639b-41fd-839d-7f1094955a75' class='xr-var-data-in' type='checkbox'><label for='data-a0e37d9e-639b-41fd-839d-7f1094955a75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-eb62ad28-4de9-43ee-96c6-00ebcfac0d6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb62ad28-4de9-43ee-96c6-00ebcfac0d6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dee7a12-aff0-4302-973d-53fc3752dc62' class='xr-var-data-in' type='checkbox'><label for='data-3dee7a12-aff0-4302-973d-53fc3752dc62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-f54b4670-2a98-4936-bebf-1fbc7b1e02e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f54b4670-2a98-4936-bebf-1fbc7b1e02e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65b46556-0db4-49a6-9164-f8378d3a4d27' class='xr-var-data-in' type='checkbox'><label for='data-65b46556-0db4-49a6-9164-f8378d3a4d27' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-88520582-3ea9-456d-9146-28bdbab904ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88520582-3ea9-456d-9146-28bdbab904ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91147058-abbb-4de6-9de3-f101a9bf0210' class='xr-var-data-in' type='checkbox'><label for='data-91147058-abbb-4de6-9de3-f101a9bf0210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-c2d44599-5940-4fe8-ba5c-2a4ded67b17e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2d44599-5940-4fe8-ba5c-2a4ded67b17e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e300d6c-edee-4e32-b486-66aa184f65bc' class='xr-var-data-in' type='checkbox'><label for='data-5e300d6c-edee-4e32-b486-66aa184f65bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e215e719-0647-4431-b8fe-795bd943a72b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e215e719-0647-4431-b8fe-795bd943a72b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6ab0c9b-4a8a-4250-bbc1-3485321521eb' class='xr-var-data-in' type='checkbox'><label for='data-a6ab0c9b-4a8a-4250-bbc1-3485321521eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d88aa10-6a43-4a7e-9159-906418246052' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7d88aa10-6a43-4a7e-9159-906418246052' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-7ce7ec97-9e6f-4cf4-8d99-03c0e6ce189a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ce7ec97-9e6f-4cf4-8d99-03c0e6ce189a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4d6f304-074d-441f-a0a4-5802c906dd08' class='xr-var-data-in' type='checkbox'><label for='data-e4d6f304-074d-441f-a0a4-5802c906dd08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32,) </td>\n",
+       "                        <td> (32,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"81\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"31\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"31\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,31.635229193102678 0.0,31.635229193102678\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"51.635229\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >32</text>\n",
+       "  <text x=\"140.000000\" y=\"15.817615\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,15.817615)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-f7f45bb7-ba2a-4fe1-996b-ecf93c498a0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7f45bb7-ba2a-4fe1-996b-ecf93c498a0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06ab2e35-a678-43ab-98bf-506908c03170' class='xr-var-data-in' type='checkbox'><label for='data-06ab2e35-a678-43ab-98bf-506908c03170' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32,) </td>\n",
+       "                        <td> (32,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-3028cae2-9a1f-4490-bb79-eacda5102097' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3028cae2-9a1f-4490-bb79-eacda5102097' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3c1312b-9993-4b7b-a972-3dd2840fa9f3' class='xr-var-data-in' type='checkbox'><label for='data-d3c1312b-9993-4b7b-a972-3dd2840fa9f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dffb4786-c992-49cc-9333-bf0cde9a52ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dffb4786-c992-49cc-9333-bf0cde9a52ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a717249-2b8d-4662-b340-6dac06b15ec0' class='xr-var-data-in' type='checkbox'><label for='data-5a717249-2b8d-4662-b340-6dac06b15ec0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-7dd891a8-6485-4e35-9033-4cd8c9a8cf87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7dd891a8-6485-4e35-9033-4cd8c9a8cf87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2efda39-757a-4b25-9a7a-a9f4f2a58be8' class='xr-var-data-in' type='checkbox'><label for='data-b2efda39-757a-4b25-9a7a-a9f4f2a58be8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                        <th> Bytes </th>\n",
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+       "                        <th> Shape </th>\n",
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+       "\n",
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+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"50\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"28\" y1=\"18\" x2=\"69\" y2=\"18\" />\n",
+       "  <line x1=\"32\" y1=\"22\" x2=\"72\" y2=\"22\" />\n",
+       "  <line x1=\"35\" y1=\"25\" x2=\"76\" y2=\"25\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"109\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
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+       "  <text x=\"100.866665\" y=\"129.013868\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >288</text>\n",
+       "  <text x=\"141.145096\" y=\"89.801051\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,141.145096,89.801051)\">192</text>\n",
+       "  <text x=\"35.294118\" y=\"93.719750\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,93.719750)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2d23e700-eaa5-45d3-b163-36f9d4092a9a' class='xr-section-summary-in' type='checkbox'  ><label for='section-2d23e700-eaa5-45d3-b163-36f9d4092a9a' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cfb85fc2-491c-4afc-9b4e-ad120a4d9141' class='xr-index-data-in' type='checkbox'/><label for='index-cfb85fc2-491c-4afc-9b4e-ad120a4d9141' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e1cc7aad-18cf-4047-9c70-d281d3944bfb' class='xr-index-data-in' type='checkbox'/><label for='index-e1cc7aad-18cf-4047-9c70-d281d3944bfb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,\n",
+       "       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,\n",
+       "        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,\n",
+       "        -87.82123029232025, -103.31712663173676, -121.54724076390266,\n",
+       "       -142.99403876066208, -168.22507977485657,  -197.9080867022276,\n",
+       "       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,\n",
+       "       -379.10090386867523,   -445.992574095726,  -524.6871747076511,\n",
+       "        -609.7786948084831,  -691.3894303143024,   -763.404481112957,\n",
+       "        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,\n",
+       "         -912.644546944648,  -936.1983984708786,   -957.485479535535,\n",
+       "         -976.325407391414,   -992.556095123291],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3dfdac6e-2864-4ad9-b94d-849b46f2cdaa' class='xr-index-data-in' type='checkbox'/><label for='index-3dfdac6e-2864-4ad9-b94d-849b46f2cdaa' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c490b542-0f84-4568-b8e7-5602ffe8a757' class='xr-index-data-in' type='checkbox'/><label for='index-c490b542-0f84-4568-b8e7-5602ffe8a757' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,\n",
+       "             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,\n",
+       "             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,\n",
+       "             1850-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,\n",
+       "             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,\n",
+       "             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,\n",
+       "             2014-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b465b924-e9e5-4694-a7c2-ba786e8639eb' class='xr-index-data-in' type='checkbox'/><label for='index-b465b924-e9e5-4694-a7c2-ba786e8639eb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b82590fe-0f90-4289-b3ec-cdac68eb2eaa' class='xr-index-data-in' type='checkbox'/><label for='index-b82590fe-0f90-4289-b3ec-cdac68eb2eaa' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-442f75a5-5816-49cc-8566-8669f3a9b75b' class='xr-section-summary-in' type='checkbox'  ><label for='section-442f75a5-5816-49cc-8566-8669f3a9b75b' class='xr-section-summary' >Attributes: <span>(61)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-03-07T14:55:48Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>AERmon</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/068116b9-bea7-4f4d-a942-e0bbee279412</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-11-04;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/068116b9-bea7-4f4d-a942-e0bbee279412</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;mmrso4&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>AERmon</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>mmrso4</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/AERmon/mmrso4/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.AERmon.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 14GB\n",
+       "Dimensions:         (lev: 32, nbnd: 2, lat: 192, lon: 288, member_id: 1,\n",
+       "                     dcpp_init_year: 1, time: 1980)\n",
+       "Coordinates:\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "    lat_bnds        (lat, nbnd) float64 3kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    a               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    b               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array<chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray>\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 438MB dask.array<chunksize=(10, 192, 288), meta=np.ndarray>\n",
+       "Attributes: (12/61)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     mmrso4\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.AERmon.gn"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds3"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<span style=\"color:black;font-weight:700;font-size:20px\">\n",
+    "Since I have already checked that these datasets are on the same grid, we can merge them:\n",
+    "</span>\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_11040/2274112695.py:1: DeprecationWarning: dropping variables using `drop` is deprecated; use drop_vars.\n",
+      "  ds_list = [dset_dict[l].drop('lat_bnds') for l in dset_dict.keys()]\n"
+     ]
+    }
+   ],
+   "source": [
+    "ds_list = [dset_dict[l].drop('lat_bnds') for l in dset_dict.keys()]\n",
+    "ds = xr.merge(ds_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "}\n",
+       "\n",
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 15GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 1980)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 438MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e90c3490-46b3-4c21-aa9e-85d46e93dd8a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e90c3490-46b3-4c21-aa9e-85d46e93dd8a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c3e23b15-8ae9-4068-a4a3-ce2aa07869cd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c3e23b15-8ae9-4068-a4a3-ce2aa07869cd' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-3d47c756-08b8-4d36-a6b2-5ae1d5a7644b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d47c756-08b8-4d36-a6b2-5ae1d5a7644b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f2609c4-f4a8-4ecf-9d7a-9ce602ea5b96' class='xr-var-data-in' type='checkbox'><label for='data-4f2609c4-f4a8-4ecf-9d7a-9ce602ea5b96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-ce11782f-f5df-4003-a643-02ac30db87ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce11782f-f5df-4003-a643-02ac30db87ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27616872-4b8f-4715-83db-7cf1dc326409' class='xr-var-data-in' type='checkbox'><label for='data-27616872-4b8f-4715-83db-7cf1dc326409' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-39fafa3d-d120-45dd-95e3-5e0577ba59df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39fafa3d-d120-45dd-95e3-5e0577ba59df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bdd3382-1f07-4d38-a870-eb42acb012af' class='xr-var-data-in' type='checkbox'><label for='data-0bdd3382-1f07-4d38-a870-eb42acb012af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-885b4ffa-67eb-41c4-830b-2fc1c056abd4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-885b4ffa-67eb-41c4-830b-2fc1c056abd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b9541f2-134c-4dfd-900b-6c60933d5a7c' class='xr-var-data-in' type='checkbox'><label for='data-9b9541f2-134c-4dfd-900b-6c60933d5a7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2acc8cee-b77d-48e9-8b96-fb31813edeb8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2acc8cee-b77d-48e9-8b96-fb31813edeb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c0e4014-2d9d-4e13-acce-7e3af089071a' class='xr-var-data-in' type='checkbox'><label for='data-6c0e4014-2d9d-4e13-acce-7e3af089071a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-e310c819-d9c5-442e-b562-3184b2c2ff7f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e310c819-d9c5-442e-b562-3184b2c2ff7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6a516a4-0aac-4cb3-b89c-331c4f2ecacb' class='xr-var-data-in' type='checkbox'><label for='data-e6a516a4-0aac-4cb3-b89c-331c4f2ecacb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-669733f3-acf9-4ef6-b80c-c41501a0f55a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-669733f3-acf9-4ef6-b80c-c41501a0f55a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6bb0354-e0c2-43aa-a31d-c957485a9582' class='xr-var-data-in' type='checkbox'><label for='data-f6bb0354-e0c2-43aa-a31d-c957485a9582' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-39b3db86-5479-4b62-bac9-16a3bfeee0a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39b3db86-5479-4b62-bac9-16a3bfeee0a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b990322-3c4d-4c97-b4ce-38b84d01c0df' class='xr-var-data-in' type='checkbox'><label for='data-7b990322-3c4d-4c97-b4ce-38b84d01c0df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,\n",
+       "        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,\n",
+       "       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,\n",
+       "       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,\n",
+       "       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,\n",
+       "       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,\n",
+       "       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-1ea8d0b7-ae57-4fd4-812a-ed7a2436af69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ea8d0b7-ae57-4fd4-812a-ed7a2436af69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd889eec-7991-4ca6-86fe-000be471af2e' class='xr-var-data-in' type='checkbox'><label for='data-fd889eec-7991-4ca6-86fe-000be471af2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-0fc45a33-1edf-4733-a73f-e7bddc836891' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0fc45a33-1edf-4733-a73f-e7bddc836891' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3a3f239-e5e7-42c8-9811-51f48b272885' class='xr-var-data-in' type='checkbox'><label for='data-d3a3f239-e5e7-42c8-9811-51f48b272885' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-b55fec80-d040-4ea4-bfa4-99db455b7964' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b55fec80-d040-4ea4-bfa4-99db455b7964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd2c249f-f6b5-48de-97e7-81d37fb62b82' class='xr-var-data-in' type='checkbox'><label for='data-fd2c249f-f6b5-48de-97e7-81d37fb62b82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 6 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7db91c7d-e443-48c8-9436-6473f83ba1cf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7db91c7d-e443-48c8-9436-6473f83ba1cf' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-f980b003-a669-4d0e-9714-a68165a2c38b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f980b003-a669-4d0e-9714-a68165a2c38b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bceeb408-e0ee-48ea-be77-007d28206bbc' class='xr-var-data-in' type='checkbox'><label for='data-bceeb408-e0ee-48ea-be77-007d28206bbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-896ba7e5-aae5-484d-bca2-7801a5e9e3bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-896ba7e5-aae5-484d-bca2-7801a5e9e3bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e354c88e-20b1-439a-9d75-70047c822e25' class='xr-var-data-in' type='checkbox'><label for='data-e354c88e-20b1-439a-9d75-70047c822e25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
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+       "                        <td> (32,) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-cc3885de-bbd7-40f6-89a4-6ad7f8b608aa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc3885de-bbd7-40f6-89a4-6ad7f8b608aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da6f3e52-fc48-4fd7-90bc-a41997a11cb7' class='xr-var-data-in' type='checkbox'><label for='data-da6f3e52-fc48-4fd7-90bc-a41997a11cb7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
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+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
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+       "                    <tr>\n",
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+       "                        <td> (32,) </td>\n",
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+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-2949d059-3ee9-4cb9-a579-ca12152f9a39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2949d059-3ee9-4cb9-a579-ca12152f9a39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e65bd460-6878-42be-a7aa-633e9c5e9bd5' class='xr-var-data-in' type='checkbox'><label for='data-e65bd460-6878-42be-a7aa-633e9c5e9bd5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                <thead>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
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+       "                        <td> 67.50 MiB </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9003f384-e444-40df-838a-c03b77e16b12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9003f384-e444-40df-838a-c03b77e16b12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45c139cd-9705-4e1a-bc02-abc4ae8c7008' class='xr-var-data-in' type='checkbox'><label for='data-45c139cd-9705-4e1a-bc02-abc4ae8c7008' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-56c7e90f-60cc-4d90-a374-12f5e0de018d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56c7e90f-60cc-4d90-a374-12f5e0de018d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78867c72-2fa4-4fa5-980a-a2132c3a33e9' class='xr-var-data-in' type='checkbox'><label for='data-78867c72-2fa4-4fa5-980a-a2132c3a33e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 417.66 MiB </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-b78c1860-011f-4bea-a8bc-a592c14d89f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b78c1860-011f-4bea-a8bc-a592c14d89f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a9b9fe0-c297-412a-9e80-09937303fc63' class='xr-var-data-in' type='checkbox'><label for='data-6a9b9fe0-c297-412a-9e80-09937303fc63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-c945c430-29d5-473a-92a7-300c2cc1e00c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c945c430-29d5-473a-92a7-300c2cc1e00c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-650cc16c-586b-4d79-962c-6f187791e328' class='xr-var-data-in' type='checkbox'><label for='data-650cc16c-586b-4d79-962c-6f187791e328' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                        <td> 417.66 MiB </td>\n",
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+       "                    <tr>\n",
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+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-a65c45fe-912c-47b9-a48f-9793bc8e11fc' class='xr-section-summary-in' type='checkbox'  ><label for='section-a65c45fe-912c-47b9-a48f-9793bc8e11fc' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4820bcb8-7e3a-489e-ba03-fb4411cb4434' class='xr-index-data-in' type='checkbox'/><label for='index-4820bcb8-7e3a-489e-ba03-fb4411cb4434' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0540677b-1831-4c16-9eed-879221abbd66' class='xr-index-data-in' type='checkbox'/><label for='index-0540677b-1831-4c16-9eed-879221abbd66' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1518f381-b4f9-4ab4-9e8a-8457b988c5e0' class='xr-index-data-in' type='checkbox'/><label for='index-1518f381-b4f9-4ab4-9e8a-8457b988c5e0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-07bd4a92-bfc2-4b14-bb92-9a79c5b898a0' class='xr-index-data-in' type='checkbox'/><label for='index-07bd4a92-bfc2-4b14-bb92-9a79c5b898a0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-898d3593-fc78-47ac-b265-91f40157b8fd' class='xr-index-data-in' type='checkbox'/><label for='index-898d3593-fc78-47ac-b265-91f40157b8fd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,\n",
+       "       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,\n",
+       "        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,\n",
+       "        -87.82123029232025, -103.31712663173676, -121.54724076390266,\n",
+       "       -142.99403876066208, -168.22507977485657,  -197.9080867022276,\n",
+       "       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,\n",
+       "       -379.10090386867523,   -445.992574095726,  -524.6871747076511,\n",
+       "        -609.7786948084831,  -691.3894303143024,   -763.404481112957,\n",
+       "        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,\n",
+       "         -912.644546944648,  -936.1983984708786,   -957.485479535535,\n",
+       "         -976.325407391414,   -992.556095123291],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2a86eceb-c979-4c56-9bdf-cb57ee1ef651' class='xr-index-data-in' type='checkbox'/><label for='index-2a86eceb-c979-4c56-9bdf-cb57ee1ef651' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,\n",
+       "             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,\n",
+       "             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,\n",
+       "             1850-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,\n",
+       "             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,\n",
+       "             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,\n",
+       "             2014-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3b69f123-2e06-43c3-bc8c-1db8564b4a0e' class='xr-section-summary-in' type='checkbox'  ><label for='section-3b69f123-2e06-43c3-bc8c-1db8564b4a0e' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 15GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 1980)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    a               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    b               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array<chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray>\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 438MB dask.array<chunksize=(10, 192, 288), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## 1.1 Reading in the data from file:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "```python\n",
+    "path='filename.nc'\n",
+    "ds = xr.open_dataset(path)\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "##### Opening multiple files:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "```python\n",
+    "\n",
+    "list_of_files = [\n",
+    "    'file1.nc',\n",
+    "    'file2.nc'\n",
+    "]\n",
+    "xr.open_mfdataset(list_of_files, concat_dim='time',combine='by_coords')\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# 2. Check how your dataset looks"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "#### Different types of information/data:\n",
+    "- Coordinates\n",
+    "- Data variables\n",
+    "- Global attributes\n",
+    "- Variable attributes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<defs>\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
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+       " */\n",
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+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
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+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
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+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
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+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
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+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 15GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 1980)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 438MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-048f0340-7b0f-4dd2-9ce8-dfca6e13d284' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-048f0340-7b0f-4dd2-9ce8-dfca6e13d284' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-bfd4b7b3-7882-49da-95cc-c847a58d2c48' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bfd4b7b3-7882-49da-95cc-c847a58d2c48' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-ad6ea541-3301-488d-b0a0-8a25b4521657' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad6ea541-3301-488d-b0a0-8a25b4521657' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69e81aea-bd14-4d0f-a94b-d225aeee528a' class='xr-var-data-in' type='checkbox'><label for='data-69e81aea-bd14-4d0f-a94b-d225aeee528a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-3f0afd85-77a3-40e6-9b5e-02d8d0b17e03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f0afd85-77a3-40e6-9b5e-02d8d0b17e03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fced7d30-1ca0-46a1-8d61-cd4ebc048b5f' class='xr-var-data-in' type='checkbox'><label for='data-fced7d30-1ca0-46a1-8d61-cd4ebc048b5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-defca196-9000-41a8-97cc-34c6c18ae078' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-defca196-9000-41a8-97cc-34c6c18ae078' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19c0b1e1-6b50-4816-b8e5-34f8d22f0785' class='xr-var-data-in' type='checkbox'><label for='data-19c0b1e1-6b50-4816-b8e5-34f8d22f0785' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-98a6a390-1ab0-4394-957a-8303d9e4116e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98a6a390-1ab0-4394-957a-8303d9e4116e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c5b634b-44c8-47b3-ae0d-c032627ca0cf' class='xr-var-data-in' type='checkbox'><label for='data-5c5b634b-44c8-47b3-ae0d-c032627ca0cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e8517f54-c0ff-49a6-a4bb-b8414bf4634c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8517f54-c0ff-49a6-a4bb-b8414bf4634c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-323b0bfd-ff29-4350-af4a-6aa6d3c99aa5' class='xr-var-data-in' type='checkbox'><label for='data-323b0bfd-ff29-4350-af4a-6aa6d3c99aa5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-58a74926-b720-4689-bfbb-4d532e3b1ae8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58a74926-b720-4689-bfbb-4d532e3b1ae8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed2273d8-9ddb-487c-8743-576814085cfa' class='xr-var-data-in' type='checkbox'><label for='data-ed2273d8-9ddb-487c-8743-576814085cfa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-9209ae5b-c488-4af8-9b58-bb9852d08fb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9209ae5b-c488-4af8-9b58-bb9852d08fb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b405acc-005d-4930-ab70-bfda83a805b5' class='xr-var-data-in' type='checkbox'><label for='data-4b405acc-005d-4930-ab70-bfda83a805b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-a04deb06-2249-447c-b045-14de2c44c964' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a04deb06-2249-447c-b045-14de2c44c964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc82fbef-e2fb-41de-a0b0-8fb38cea525f' class='xr-var-data-in' type='checkbox'><label for='data-bc82fbef-e2fb-41de-a0b0-8fb38cea525f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,\n",
+       "        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,\n",
+       "       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,\n",
+       "       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,\n",
+       "       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,\n",
+       "       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,\n",
+       "       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-13f091da-c8a5-47e1-a704-63a7d4cc7629' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-13f091da-c8a5-47e1-a704-63a7d4cc7629' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec58db63-e3dc-4ff5-b3d2-487737922a67' class='xr-var-data-in' type='checkbox'><label for='data-ec58db63-e3dc-4ff5-b3d2-487737922a67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-a53dee04-f5e7-4816-a860-dcc66e1c249b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a53dee04-f5e7-4816-a860-dcc66e1c249b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6df1e86-0fde-40ce-9ff4-76f31f50de28' class='xr-var-data-in' type='checkbox'><label for='data-f6df1e86-0fde-40ce-9ff4-76f31f50de28' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-cada893c-525d-4458-b03b-fd38d1613380' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cada893c-525d-4458-b03b-fd38d1613380' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92cda687-0618-47bf-9557-67aa3cb27c0b' class='xr-var-data-in' type='checkbox'><label for='data-92cda687-0618-47bf-9557-67aa3cb27c0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 6 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-38e982e6-59be-4833-8991-2625cc71d292' class='xr-section-summary-in' type='checkbox'  checked><label for='section-38e982e6-59be-4833-8991-2625cc71d292' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-d6c069d2-2064-4e23-8460-e27a0c8f31bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6c069d2-2064-4e23-8460-e27a0c8f31bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81d9d8ac-96cf-4ce5-afba-f4bf54df694a' class='xr-var-data-in' type='checkbox'><label for='data-81d9d8ac-96cf-4ce5-afba-f4bf54df694a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"374\" height=\"144\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-385a7520-dae5-4ace-bc27-9ada8698ae85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-385a7520-dae5-4ace-bc27-9ada8698ae85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c139d309-60a7-438b-9d24-98cc8d737d98' class='xr-var-data-in' type='checkbox'><label for='data-c139d309-60a7-438b-9d24-98cc8d737d98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
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+       "                        <td> (32,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-caf04ec5-5460-4069-addb-1658ea9e0031' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-caf04ec5-5460-4069-addb-1658ea9e0031' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66a732d0-ad63-4a84-944c-b61b6fcf6572' class='xr-var-data-in' type='checkbox'><label for='data-66a732d0-ad63-4a84-944c-b61b6fcf6572' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
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+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (32,) </td>\n",
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+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
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+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-da5aac5d-dd29-40e8-8b8b-edd55c74dbb5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da5aac5d-dd29-40e8-8b8b-edd55c74dbb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8cb3e66-3443-4b9a-929c-a29966c5256a' class='xr-var-data-in' type='checkbox'><label for='data-d8cb3e66-3443-4b9a-929c-a29966c5256a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 13.05 GiB </td>\n",
+       "                        <td> 67.50 MiB </td>\n",
+       "                    </tr>\n",
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+       "                    <tr>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a1e5ab66-a426-40d6-9b38-b0f9f8da62ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1e5ab66-a426-40d6-9b38-b0f9f8da62ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0589db32-d728-46d0-91c4-77e12280beb2' class='xr-var-data-in' type='checkbox'><label for='data-0589db32-d728-46d0-91c4-77e12280beb2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-f86c6704-463b-4f15-8a1f-83409b1e0a42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f86c6704-463b-4f15-8a1f-83409b1e0a42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2238a743-d6ca-4e79-9289-075dddf3bfe2' class='xr-var-data-in' type='checkbox'><label for='data-2238a743-d6ca-4e79-9289-075dddf3bfe2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                    <tr>\n",
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+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-14d7761a-6669-4484-9ad4-d0748eca7d38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14d7761a-6669-4484-9ad4-d0748eca7d38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fc57e0f-3a9e-4b28-9bde-2defb048a2da' class='xr-var-data-in' type='checkbox'><label for='data-7fc57e0f-3a9e-4b28-9bde-2defb048a2da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-0be929b5-3581-48e1-b77c-d31763db2608' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0be929b5-3581-48e1-b77c-d31763db2608' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-243f49fc-2a11-4fc4-8b86-55a03b68be24' class='xr-var-data-in' type='checkbox'><label for='data-243f49fc-2a11-4fc4-8b86-55a03b68be24' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                    <tr>\n",
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+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-d0a073e0-d860-4e3e-ae59-4e3280f00031' class='xr-section-summary-in' type='checkbox'  ><label for='section-d0a073e0-d860-4e3e-ae59-4e3280f00031' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-efd0719c-0828-4ecd-9594-e1f9a47870bc' class='xr-index-data-in' type='checkbox'/><label for='index-efd0719c-0828-4ecd-9594-e1f9a47870bc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-81acf561-dc10-4004-8f4b-6919609378be' class='xr-index-data-in' type='checkbox'/><label for='index-81acf561-dc10-4004-8f4b-6919609378be' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9d496204-3030-41de-a627-34fa83574d92' class='xr-index-data-in' type='checkbox'/><label for='index-9d496204-3030-41de-a627-34fa83574d92' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-92cb847a-4d3f-4d47-8c26-b397187d151a' class='xr-index-data-in' type='checkbox'/><label for='index-92cb847a-4d3f-4d47-8c26-b397187d151a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3eaa50cd-6bc3-436a-a7df-a938e7813094' class='xr-index-data-in' type='checkbox'/><label for='index-3eaa50cd-6bc3-436a-a7df-a938e7813094' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,\n",
+       "       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,\n",
+       "        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,\n",
+       "        -87.82123029232025, -103.31712663173676, -121.54724076390266,\n",
+       "       -142.99403876066208, -168.22507977485657,  -197.9080867022276,\n",
+       "       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,\n",
+       "       -379.10090386867523,   -445.992574095726,  -524.6871747076511,\n",
+       "        -609.7786948084831,  -691.3894303143024,   -763.404481112957,\n",
+       "        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,\n",
+       "         -912.644546944648,  -936.1983984708786,   -957.485479535535,\n",
+       "         -976.325407391414,   -992.556095123291],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8cdffeb8-dbf1-46c5-90dc-b0814af92357' class='xr-index-data-in' type='checkbox'/><label for='index-8cdffeb8-dbf1-46c5-90dc-b0814af92357' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,\n",
+       "             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,\n",
+       "             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,\n",
+       "             1850-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,\n",
+       "             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,\n",
+       "             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,\n",
+       "             2014-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8dff8441-bc8b-400e-aff5-87a03bfc94c9' class='xr-section-summary-in' type='checkbox'  ><label for='section-8dff8441-bc8b-400e-aff5-87a03bfc94c9' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 15GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 1980)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    a               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    b               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array<chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray>\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 438MB dask.array<chunksize=(10, 192, 288), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# 3. Sometimes we want to do some nice tweaks before we start: "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Selecting data and super quick plotting:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "xarray loads data only when it needs to (it's lazy, Anne can explain), and you might want to early on define the subset of data you want to look at so that you don't end up loading a lot of extra data. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "##### See [here](http://xarray.pydata.org/en/stable/user-guide/indexing.html) for nice overview"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to reduce unecessary calculations and loading of data, think about which part of the data you want, and slice early on. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Slice in time: the sel method"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 15GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 1980)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 438MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5d456d01-e285-4c04-979c-86679c5b19bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5d456d01-e285-4c04-979c-86679c5b19bc' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f0c87daa-804c-4a47-9a1b-eb20b9613a50' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f0c87daa-804c-4a47-9a1b-eb20b9613a50' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-5a9ed2f4-1772-47d7-86cd-bb392085876f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a9ed2f4-1772-47d7-86cd-bb392085876f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dcb6fd3-0ca2-47ba-85e6-9b34f1a80e72' class='xr-var-data-in' type='checkbox'><label for='data-0dcb6fd3-0ca2-47ba-85e6-9b34f1a80e72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-6505f85e-b703-4b32-a019-3ca324034e48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6505f85e-b703-4b32-a019-3ca324034e48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-787b338e-497d-489c-a116-53a60c5b952f' class='xr-var-data-in' type='checkbox'><label for='data-787b338e-497d-489c-a116-53a60c5b952f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-74396d85-2069-417f-86e3-2c0b18b49dd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74396d85-2069-417f-86e3-2c0b18b49dd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01a1b832-61ef-4351-bed2-fa0853824b39' class='xr-var-data-in' type='checkbox'><label for='data-01a1b832-61ef-4351-bed2-fa0853824b39' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-ff6c56f2-76fe-4786-8a78-4c75dbe816f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff6c56f2-76fe-4786-8a78-4c75dbe816f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8487dd41-2956-4037-8abc-7a9d74f42b60' class='xr-var-data-in' type='checkbox'><label for='data-8487dd41-2956-4037-8abc-7a9d74f42b60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-28c7ff17-54ec-46b9-8f9d-a7baf5efbd24' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28c7ff17-54ec-46b9-8f9d-a7baf5efbd24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1b12f45-b183-400d-9a94-d66a72ecb2aa' class='xr-var-data-in' type='checkbox'><label for='data-a1b12f45-b183-400d-9a94-d66a72ecb2aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-70f62d83-1535-4b08-834b-ebf5ccca1d47' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70f62d83-1535-4b08-834b-ebf5ccca1d47' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e34abcc-9067-42e3-b72b-a09dd0c81328' class='xr-var-data-in' type='checkbox'><label for='data-7e34abcc-9067-42e3-b72b-a09dd0c81328' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-eb0ddb85-4485-4c21-a6ca-04718a911c40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb0ddb85-4485-4c21-a6ca-04718a911c40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d156658d-706e-4482-939e-b68596c8eaf5' class='xr-var-data-in' type='checkbox'><label for='data-d156658d-706e-4482-939e-b68596c8eaf5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-5318b861-8d7a-4a9d-a8be-faf17e7c119f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5318b861-8d7a-4a9d-a8be-faf17e7c119f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8db3584-0241-44b0-8b72-d448643dc545' class='xr-var-data-in' type='checkbox'><label for='data-c8db3584-0241-44b0-8b72-d448643dc545' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,\n",
+       "        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,\n",
+       "       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,\n",
+       "       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,\n",
+       "       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,\n",
+       "       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,\n",
+       "       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-abc64fb2-5d1e-4623-8bb2-06b527614f42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abc64fb2-5d1e-4623-8bb2-06b527614f42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24ffa659-db65-4af5-b2f8-ece4d59ec735' class='xr-var-data-in' type='checkbox'><label for='data-24ffa659-db65-4af5-b2f8-ece4d59ec735' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-f59664a6-7313-41a7-8a90-ac6367f2da7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f59664a6-7313-41a7-8a90-ac6367f2da7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e311fc82-3688-42fc-8ad4-395689b94309' class='xr-var-data-in' type='checkbox'><label for='data-e311fc82-3688-42fc-8ad4-395689b94309' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-9b3ccf50-dbd9-4f4f-9d81-b1718e173489' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b3ccf50-dbd9-4f4f-9d81-b1718e173489' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d719a95-80f5-4af5-8d9e-1cdf971aca86' class='xr-var-data-in' type='checkbox'><label for='data-4d719a95-80f5-4af5-8d9e-1cdf971aca86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                        <td> 30.94 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                        <td> (1980, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 6 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1980</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-647b18f9-0938-4974-b6ca-ce11eb5e3471' class='xr-section-summary-in' type='checkbox'  checked><label for='section-647b18f9-0938-4974-b6ca-ce11eb5e3471' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-811b88e5-497f-4951-814f-38bbb2735397' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-811b88e5-497f-4951-814f-38bbb2735397' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-667455df-e72e-42a1-94f7-fe492b171406' class='xr-var-data-in' type='checkbox'><label for='data-667455df-e72e-42a1-94f7-fe492b171406' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"374\" height=\"144\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-114ea8b5-438e-4317-96de-1239ce9aca62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-114ea8b5-438e-4317-96de-1239ce9aca62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e820f9c3-59ba-482f-b23d-50e0e00988a4' class='xr-var-data-in' type='checkbox'><label for='data-e820f9c3-59ba-482f-b23d-50e0e00988a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
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+       "                        <td> (32,) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
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+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-ae58bb41-373a-4f91-8843-e58c5cc12966' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae58bb41-373a-4f91-8843-e58c5cc12966' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9073436-960c-4498-8398-10e9d8e921d2' class='xr-var-data-in' type='checkbox'><label for='data-a9073436-960c-4498-8398-10e9d8e921d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
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+       "                    <tr>\n",
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+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (32,) </td>\n",
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+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-61ff90f1-bade-4bfe-8300-6afba859749e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61ff90f1-bade-4bfe-8300-6afba859749e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4e0bbf1-8094-479b-a579-881dbe1efa52' class='xr-var-data-in' type='checkbox'><label for='data-d4e0bbf1-8094-479b-a579-881dbe1efa52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
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+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 13.05 GiB </td>\n",
+       "                        <td> 67.50 MiB </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ac05ec69-1119-40de-b4b5-522c940dca50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac05ec69-1119-40de-b4b5-522c940dca50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86744a89-2acb-43e9-9f5d-e902e9f4037e' class='xr-var-data-in' type='checkbox'><label for='data-86744a89-2acb-43e9-9f5d-e902e9f4037e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-068da162-fd82-4a36-af80-6da2b22fc0e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-068da162-fd82-4a36-af80-6da2b22fc0e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f7278d0-e981-4bcd-9ea3-e2fe56195fc7' class='xr-var-data-in' type='checkbox'><label for='data-7f7278d0-e981-4bcd-9ea3-e2fe56195fc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                    <tr>\n",
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+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 417.66 MiB </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-9c19fbfe-76a2-41c1-a29e-10598558f3e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c19fbfe-76a2-41c1-a29e-10598558f3e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c3de56c-267c-491f-b488-6f85a0897e1f' class='xr-var-data-in' type='checkbox'><label for='data-9c3de56c-267c-491f-b488-6f85a0897e1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-e1ffaa80-6bf3-4b34-8d96-55d071f00b2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1ffaa80-6bf3-4b34-8d96-55d071f00b2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-deb48396-ed80-49df-89b2-892dd3f4ae75' class='xr-var-data-in' type='checkbox'><label for='data-deb48396-ed80-49df-89b2-892dd3f4ae75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                    <tr>\n",
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+       "                        <td> 417.66 MiB </td>\n",
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+       "                    <tr>\n",
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+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-46507964-5274-456b-beb7-9303c93650f6' class='xr-section-summary-in' type='checkbox'  ><label for='section-46507964-5274-456b-beb7-9303c93650f6' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b28acdb6-1033-4340-bfc8-da4c4569f24f' class='xr-index-data-in' type='checkbox'/><label for='index-b28acdb6-1033-4340-bfc8-da4c4569f24f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-10d5af22-d58c-49e5-8a66-9ba84d8d8fb8' class='xr-index-data-in' type='checkbox'/><label for='index-10d5af22-d58c-49e5-8a66-9ba84d8d8fb8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-53898e4e-1f5a-4fae-aa68-6d5f5e5afdd4' class='xr-index-data-in' type='checkbox'/><label for='index-53898e4e-1f5a-4fae-aa68-6d5f5e5afdd4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4d887f90-48b4-420c-91d7-6b1af23bfd90' class='xr-index-data-in' type='checkbox'/><label for='index-4d887f90-48b4-420c-91d7-6b1af23bfd90' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4f2340fd-5d58-40dc-b3b6-5b3471779b2e' class='xr-index-data-in' type='checkbox'/><label for='index-4f2340fd-5d58-40dc-b3b6-5b3471779b2e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,\n",
+       "       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,\n",
+       "        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,\n",
+       "        -87.82123029232025, -103.31712663173676, -121.54724076390266,\n",
+       "       -142.99403876066208, -168.22507977485657,  -197.9080867022276,\n",
+       "       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,\n",
+       "       -379.10090386867523,   -445.992574095726,  -524.6871747076511,\n",
+       "        -609.7786948084831,  -691.3894303143024,   -763.404481112957,\n",
+       "        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,\n",
+       "         -912.644546944648,  -936.1983984708786,   -957.485479535535,\n",
+       "         -976.325407391414,   -992.556095123291],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-822197fe-3cff-42e7-af63-c6bd4c1cb890' class='xr-index-data-in' type='checkbox'/><label for='index-822197fe-3cff-42e7-af63-c6bd4c1cb890' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,\n",
+       "             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,\n",
+       "             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,\n",
+       "             1850-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,\n",
+       "             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,\n",
+       "             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,\n",
+       "             2014-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-88c803d6-1cea-49ea-aae9-18a68cd5dc2a' class='xr-section-summary-in' type='checkbox'  ><label for='section-88c803d6-1cea-49ea-aae9-18a68cd5dc2a' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 15GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 1980)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...\n",
+       "    time_bnds       (time, nbnd) object 32kB dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    a               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    b               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array<chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray>\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 438MB dask.array<chunksize=(10, 192, 288), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array<chunksize=(1, 1, 600, 192, 288), meta=np.ndarray>\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dss = ds.sel(time = slice('1990-01-01','2010-01-01'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  display: block;\n",
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+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
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+       "\n",
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+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
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+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 240)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 2GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 53MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8220c364-3477-4f77-b9ce-02dc7e75afb5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8220c364-3477-4f77-b9ce-02dc7e75afb5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-670427de-485b-43b7-9cf6-52683f428f54' class='xr-section-summary-in' type='checkbox'  checked><label for='section-670427de-485b-43b7-9cf6-52683f428f54' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-597bd880-ad1d-4bb1-b5c2-38fd64a1440e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-597bd880-ad1d-4bb1-b5c2-38fd64a1440e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adfb6acf-5dca-4e2a-8268-de740094a419' class='xr-var-data-in' type='checkbox'><label for='data-adfb6acf-5dca-4e2a-8268-de740094a419' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-69d3d1a9-6a5e-4edd-89f9-3ee7d50c3480' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69d3d1a9-6a5e-4edd-89f9-3ee7d50c3480' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a104b75-2af2-4e64-9427-8148bf8ef4aa' class='xr-var-data-in' type='checkbox'><label for='data-6a104b75-2af2-4e64-9427-8148bf8ef4aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-7a7a2a3e-2106-4000-8cb8-9bc1f8762e8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a7a2a3e-2106-4000-8cb8-9bc1f8762e8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73a8ad79-6000-4393-809e-f93b0fe0851e' class='xr-var-data-in' type='checkbox'><label for='data-73a8ad79-6000-4393-809e-f93b0fe0851e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-2c0f45c8-5e56-48c0-b6a8-c4054335a301' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c0f45c8-5e56-48c0-b6a8-c4054335a301' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04e19313-7fca-4d7c-a1d3-4d18ce66fadb' class='xr-var-data-in' type='checkbox'><label for='data-04e19313-7fca-4d7c-a1d3-4d18ce66fadb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4793e73f-6e9d-4f07-9037-ba7b62e34e0c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4793e73f-6e9d-4f07-9037-ba7b62e34e0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78d28831-8308-4f81-bdbc-3f239acf9a6a' class='xr-var-data-in' type='checkbox'><label for='data-78d28831-8308-4f81-bdbc-3f239acf9a6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-390630aa-f569-4731-80b8-00c88ef02913' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-390630aa-f569-4731-80b8-00c88ef02913' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8a4e911-7e95-46d2-9b5d-bc5bf630d38d' class='xr-var-data-in' type='checkbox'><label for='data-a8a4e911-7e95-46d2-9b5d-bc5bf630d38d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-1a33044e-b0af-4005-9982-b8100e0144a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a33044e-b0af-4005-9982-b8100e0144a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8ac9951-8cd9-4e8f-8ce8-b21369158a65' class='xr-var-data-in' type='checkbox'><label for='data-c8ac9951-8cd9-4e8f-8ce8-b21369158a65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-5e2878a0-908f-4b1f-8d7d-5d2797c9fb62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e2878a0-908f-4b1f-8d7d-5d2797c9fb62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04a6f1f6-f9eb-4b6c-a5ea-4a88444e5b6a' class='xr-var-data-in' type='checkbox'><label for='data-04a6f1f6-f9eb-4b6c-a5ea-4a88444e5b6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,\n",
+       "        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,\n",
+       "       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,\n",
+       "       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,\n",
+       "       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,\n",
+       "       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,\n",
+       "       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-11450798-096b-478a-87b0-6bf54ab1f2b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11450798-096b-478a-87b0-6bf54ab1f2b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6effd2a4-2bb3-40fa-8797-1f12b2798c5d' class='xr-var-data-in' type='checkbox'><label for='data-6effd2a4-2bb3-40fa-8797-1f12b2798c5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-32eaa2ad-11f2-4741-8a43-5ffa3f38db0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32eaa2ad-11f2-4741-8a43-5ffa3f38db0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73599167-b6db-4efb-8379-6df3c5526ca4' class='xr-var-data-in' type='checkbox'><label for='data-73599167-b6db-4efb-8379-6df3c5526ca4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-f018d94b-683d-4ebd-bb1b-31ddb86a315b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f018d94b-683d-4ebd-bb1b-31ddb86a315b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-915d3a2b-1d25-4a79-98c9-4df41a2df884' class='xr-var-data-in' type='checkbox'><label for='data-915d3a2b-1d25-4a79-98c9-4df41a2df884' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 7 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c3a4ccaf-94e2-47ce-b8c9-2f68bb107454' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c3a4ccaf-94e2-47ce-b8c9-2f68bb107454' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-1b2e86b2-3a2e-489a-8f01-5f6662c650c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b2e86b2-3a2e-489a-8f01-5f6662c650c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5ef78c4-c214-48d7-a946-b3b480fe9c85' class='xr-var-data-in' type='checkbox'><label for='data-c5ef78c4-c214-48d7-a946-b3b480fe9c85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-0c3de282-d07e-42f4-af20-7479a7b122a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c3de282-d07e-42f4-af20-7479a7b122a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbddf06c-5d64-4a14-94f1-e2e2dc9c2eb4' class='xr-var-data-in' type='checkbox'><label for='data-bbddf06c-5d64-4a14-94f1-e2e2dc9c2eb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
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+       "                        <td> (32,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-c670e6fb-0333-422d-aafa-0b907a2ed811' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c670e6fb-0333-422d-aafa-0b907a2ed811' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae6096c2-056e-4cd7-a391-cead37335a79' class='xr-var-data-in' type='checkbox'><label for='data-ae6096c2-056e-4cd7-a391-cead37335a79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
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+       "                    <tr>\n",
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+       "                        <td> (32,) </td>\n",
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+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
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+       "                        <th> Data type </th>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-8fa13572-b9cb-4ee2-938c-f7bf4ecddb6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fa13572-b9cb-4ee2-938c-f7bf4ecddb6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e41e4f5b-eaaa-46d1-a529-e6ccca463d4e' class='xr-var-data-in' type='checkbox'><label for='data-e41e4f5b-eaaa-46d1-a529-e6ccca463d4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5f1b67a0-513d-462a-a1ac-48027c21f417' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f1b67a0-513d-462a-a1ac-48027c21f417' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46be4717-dc2e-4c29-9769-559fbf920002' class='xr-var-data-in' type='checkbox'><label for='data-46be4717-dc2e-4c29-9769-559fbf920002' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-52fb00db-ebb2-492c-84f7-ab30da011580' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52fb00db-ebb2-492c-84f7-ab30da011580' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a77f1b96-3d52-46ad-98ea-c7f6c6da403d' class='xr-var-data-in' type='checkbox'><label for='data-a77f1b96-3d52-46ad-98ea-c7f6c6da403d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
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+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-509881b9-7952-4cbf-b8f0-964264ecd024' class='xr-section-summary-in' type='checkbox'  ><label for='section-509881b9-7952-4cbf-b8f0-964264ecd024' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c7e24b01-036f-46f7-8ef8-293d473ab021' class='xr-index-data-in' type='checkbox'/><label for='index-c7e24b01-036f-46f7-8ef8-293d473ab021' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ce436c77-b9e2-4f38-b0a8-ca5b695346ff' class='xr-index-data-in' type='checkbox'/><label for='index-ce436c77-b9e2-4f38-b0a8-ca5b695346ff' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2cb18fcf-8c5d-48f9-983f-81d06eac3001' class='xr-index-data-in' type='checkbox'/><label for='index-2cb18fcf-8c5d-48f9-983f-81d06eac3001' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-13c08cf1-5f10-4d91-80aa-62a8aa6cfbb1' class='xr-index-data-in' type='checkbox'/><label for='index-13c08cf1-5f10-4d91-80aa-62a8aa6cfbb1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2e8814cc-ccac-4360-82cd-3e38c5930607' class='xr-index-data-in' type='checkbox'/><label for='index-2e8814cc-ccac-4360-82cd-3e38c5930607' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,\n",
+       "       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,\n",
+       "        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,\n",
+       "        -87.82123029232025, -103.31712663173676, -121.54724076390266,\n",
+       "       -142.99403876066208, -168.22507977485657,  -197.9080867022276,\n",
+       "       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,\n",
+       "       -379.10090386867523,   -445.992574095726,  -524.6871747076511,\n",
+       "        -609.7786948084831,  -691.3894303143024,   -763.404481112957,\n",
+       "        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,\n",
+       "         -912.644546944648,  -936.1983984708786,   -957.485479535535,\n",
+       "         -976.325407391414,   -992.556095123291],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ff6b705f-1344-4b9f-85a2-5b9a68b8764f' class='xr-index-data-in' type='checkbox'/><label for='index-ff6b705f-1344-4b9f-85a2-5b9a68b8764f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,\n",
+       "             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,\n",
+       "             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,\n",
+       "             1990-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,\n",
+       "             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,\n",
+       "             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,\n",
+       "             2009-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-084b135d-a421-46b2-b771-c118461b124c' class='xr-section-summary-in' type='checkbox'  ><label for='section-084b135d-a421-46b2-b771-c118461b124c' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 240)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array<chunksize=(240, 2), meta=np.ndarray>\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    a               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    b               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 2GB dask.array<chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray>\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 53MB dask.array<chunksize=(10, 192, 288), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 120, 192, 288), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 120, 192, 288), meta=np.ndarray>\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "<span style=\"color:red;font-weight:700;font-size:20px\">\n",
+    "NB: Always check that the function you are using is doing what you expect!\n",
+    "</span>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You might even select only the arctic e.g.: "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "#### isel, sel: index selecting "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Select the surface (which in this case is the last index :) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "\n",
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+       "  display: none;\n",
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+       "\n",
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+       "\n",
+       ".xr-dim-list {\n",
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+       "  display: none;\n",
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+       "  display: block;\n",
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+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
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+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
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+       "\n",
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+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 240)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 2GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 53MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7077d0cd-a175-4adf-9ca6-914b74155a73' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7077d0cd-a175-4adf-9ca6-914b74155a73' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-47111de8-7674-47f9-bd63-b7aacaa9249e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-47111de8-7674-47f9-bd63-b7aacaa9249e' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-43d59d81-2f5d-43de-bdd8-9850c6508539' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43d59d81-2f5d-43de-bdd8-9850c6508539' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eafb3b7d-1d2b-42b8-8b40-6a9dea4499ff' class='xr-var-data-in' type='checkbox'><label for='data-eafb3b7d-1d2b-42b8-8b40-6a9dea4499ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-96e8173b-c8dc-46fd-82d6-6b4a87cfba20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96e8173b-c8dc-46fd-82d6-6b4a87cfba20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fd11f61-da06-4a0d-a189-dcde9e40fa1c' class='xr-var-data-in' type='checkbox'><label for='data-3fd11f61-da06-4a0d-a189-dcde9e40fa1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-1f152a9c-b7e9-494d-b2bd-6eb6e0ec12de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f152a9c-b7e9-494d-b2bd-6eb6e0ec12de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a799f3ce-ac82-48fc-8ded-5aefbb1a4a99' class='xr-var-data-in' type='checkbox'><label for='data-a799f3ce-ac82-48fc-8ded-5aefbb1a4a99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-86439893-b693-4c60-abc8-3bcc3574ead8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86439893-b693-4c60-abc8-3bcc3574ead8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45eae2f8-2c89-4a4a-99b1-bd1926fd349e' class='xr-var-data-in' type='checkbox'><label for='data-45eae2f8-2c89-4a4a-99b1-bd1926fd349e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-3f1801b8-052f-4c96-b74e-54d33e1429e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3f1801b8-052f-4c96-b74e-54d33e1429e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-828d65b9-fdb3-4f93-a5c4-f3a09b6b9125' class='xr-var-data-in' type='checkbox'><label for='data-828d65b9-fdb3-4f93-a5c4-f3a09b6b9125' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-1b62cfcb-8ecf-4bf9-94a8-93850254ab95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b62cfcb-8ecf-4bf9-94a8-93850254ab95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41e95c9a-109b-4f81-9049-38155b9bf9fc' class='xr-var-data-in' type='checkbox'><label for='data-41e95c9a-109b-4f81-9049-38155b9bf9fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-69abe9b6-04a9-43f3-a0df-ccae7d350b32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69abe9b6-04a9-43f3-a0df-ccae7d350b32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cab393cc-32a3-4cc7-a703-e7b373072142' class='xr-var-data-in' type='checkbox'><label for='data-cab393cc-32a3-4cc7-a703-e7b373072142' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-7f4e121a-0f89-48c6-aa3a-56fae93f9a0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f4e121a-0f89-48c6-aa3a-56fae93f9a0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f4650a0-f748-45f3-a43a-4ae04a2c601e' class='xr-var-data-in' type='checkbox'><label for='data-9f4650a0-f748-45f3-a43a-4ae04a2c601e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,\n",
+       "        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,\n",
+       "       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,\n",
+       "       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,\n",
+       "       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,\n",
+       "       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,\n",
+       "       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-7265b689-d4cd-44cb-9026-6b14b87b4130' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7265b689-d4cd-44cb-9026-6b14b87b4130' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f78d8c5-b63c-4298-8850-af7030d463de' class='xr-var-data-in' type='checkbox'><label for='data-4f78d8c5-b63c-4298-8850-af7030d463de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
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+       "\n",
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+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-8aff2af4-4c4f-412b-b059-aefe65d72e5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8aff2af4-4c4f-412b-b059-aefe65d72e5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa908b24-7424-4be9-9966-e677b7e84063' class='xr-var-data-in' type='checkbox'><label for='data-aa908b24-7424-4be9-9966-e677b7e84063' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-24470e9c-c0f0-42a1-a612-c3d670ba68ec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24470e9c-c0f0-42a1-a612-c3d670ba68ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dda272e7-5473-489a-9d56-935c7660a33b' class='xr-var-data-in' type='checkbox'><label for='data-dda272e7-5473-489a-9d56-935c7660a33b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 7 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
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+       "\n",
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+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-796bf9c0-4bbb-484b-bee8-dc098ec6a2f5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-796bf9c0-4bbb-484b-bee8-dc098ec6a2f5' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-5ee3d78c-f83e-407f-b25e-94935856da97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ee3d78c-f83e-407f-b25e-94935856da97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ec30d3b-588a-4f3a-bc88-ce11eb92fac7' class='xr-var-data-in' type='checkbox'><label for='data-8ec30d3b-588a-4f3a-bc88-ce11eb92fac7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-7ed3b1f5-54a7-4c1d-8af1-0d7db6010130' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ed3b1f5-54a7-4c1d-8af1-0d7db6010130' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e37e032-9460-4b16-a696-a99f541b6ab2' class='xr-var-data-in' type='checkbox'><label for='data-3e37e032-9460-4b16-a696-a99f541b6ab2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32,) </td>\n",
+       "                        <td> (32,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-edb5b770-ffd3-4a51-8ff0-fc20a6a20c33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edb5b770-ffd3-4a51-8ff0-fc20a6a20c33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e6d45bb-203b-4ab4-b00c-7996fdc8f9bd' class='xr-var-data-in' type='checkbox'><label for='data-9e6d45bb-203b-4ab4-b00c-7996fdc8f9bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
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+       "                    <tr>\n",
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+       "                        <td> (32,) </td>\n",
+       "                        <td> (32,) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-579ea7cf-8f3f-4389-b3f3-7928efa735c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-579ea7cf-8f3f-4389-b3f3-7928efa735c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98b0c2a4-d6b7-4a57-b1b5-74b549c8ba97' class='xr-var-data-in' type='checkbox'><label for='data-98b0c2a4-d6b7-4a57-b1b5-74b549c8ba97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-30fee6cc-e8a2-4414-a668-27fcfb42c60f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30fee6cc-e8a2-4414-a668-27fcfb42c60f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6982805-5939-4662-ac0b-daab747a8024' class='xr-var-data-in' type='checkbox'><label for='data-d6982805-5939-4662-ac0b-daab747a8024' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-dfe670cc-f461-4970-851f-766046dadaaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dfe670cc-f461-4970-851f-766046dadaaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41692584-0b26-46fe-8763-ecb2ecf558c2' class='xr-var-data-in' type='checkbox'><label for='data-41692584-0b26-46fe-8763-ecb2ecf558c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "  <text x=\"213.823529\" y=\"158.823529\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >288</text>\n",
+       "  <text x=\"293.823529\" y=\"98.823529\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,293.823529,98.823529)\">192</text>\n",
+       "  <text x=\"114.411765\" y=\"129.411765\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,114.411765,129.411765)\">240</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f3b16c8-905c-4efa-9a21-8543d221ce4c' class='xr-section-summary-in' type='checkbox'  ><label for='section-6f3b16c8-905c-4efa-9a21-8543d221ce4c' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-77edadd2-c823-4eaf-9f69-c2619c85221c' class='xr-index-data-in' type='checkbox'/><label for='index-77edadd2-c823-4eaf-9f69-c2619c85221c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-eb7e5956-d275-4cc7-a934-9fbbb52f6b95' class='xr-index-data-in' type='checkbox'/><label for='index-eb7e5956-d275-4cc7-a934-9fbbb52f6b95' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-48e90d37-22d7-44ef-983d-4064ded225e1' class='xr-index-data-in' type='checkbox'/><label for='index-48e90d37-22d7-44ef-983d-4064ded225e1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0ac44de4-539e-4966-bce0-dcd56fbb7e0e' class='xr-index-data-in' type='checkbox'/><label for='index-0ac44de4-539e-4966-bce0-dcd56fbb7e0e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f346f419-ab55-473b-aa10-5aca1cec459d' class='xr-index-data-in' type='checkbox'/><label for='index-f346f419-ab55-473b-aa10-5aca1cec459d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,\n",
+       "       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,\n",
+       "        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,\n",
+       "        -87.82123029232025, -103.31712663173676, -121.54724076390266,\n",
+       "       -142.99403876066208, -168.22507977485657,  -197.9080867022276,\n",
+       "       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,\n",
+       "       -379.10090386867523,   -445.992574095726,  -524.6871747076511,\n",
+       "        -609.7786948084831,  -691.3894303143024,   -763.404481112957,\n",
+       "        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,\n",
+       "         -912.644546944648,  -936.1983984708786,   -957.485479535535,\n",
+       "         -976.325407391414,   -992.556095123291],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a3073d83-6acb-4705-a395-00fe9660ff70' class='xr-index-data-in' type='checkbox'/><label for='index-a3073d83-6acb-4705-a395-00fe9660ff70' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,\n",
+       "             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,\n",
+       "             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,\n",
+       "             1990-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,\n",
+       "             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,\n",
+       "             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,\n",
+       "             2009-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f6768113-dbeb-43d4-9882-0054c7b2c5eb' class='xr-section-summary-in' type='checkbox'  ><label for='section-f6768113-dbeb-43d4-9882-0054c7b2c5eb' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 240)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array<chunksize=(240, 2), meta=np.ndarray>\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    a               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    b               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 2GB dask.array<chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray>\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 53MB dask.array<chunksize=(10, 192, 288), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 120, 192, 288), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 120, 192, 288), meta=np.ndarray>\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dss_s = dss.isel(lev=-1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 213MB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, time: 240)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;\n",
+       "    b_bnds          (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;\n",
+       "    lev             float64 8B -992.6\n",
+       "    lev_bnds        (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;\n",
+       "  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    a               float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
+       "    b               float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 10, 192, 288), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 53MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-57631753-fc24-46fa-8adb-ed85a66cd516' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-57631753-fc24-46fa-8adb-ed85a66cd516' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1b2fea94-91b4-4851-8874-2d017d7b6312' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b2fea94-91b4-4851-8874-2d017d7b6312' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-a93ab33d-f04c-403c-b1fb-b07c25d3150e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a93ab33d-f04c-403c-b1fb-b07c25d3150e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65e329dc-2590-43c7-aacb-22fc4efd430d' class='xr-var-data-in' type='checkbox'><label for='data-65e329dc-2590-43c7-aacb-22fc4efd430d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-4d867e34-a50a-46b9-b55c-6b7ed9c60b1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d867e34-a50a-46b9-b55c-6b7ed9c60b1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7e7d572-5941-45c7-941b-d3dd73f99e32' class='xr-var-data-in' type='checkbox'><label for='data-b7e7d572-5941-45c7-941b-d3dd73f99e32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-9a0a1759-2810-4c92-ad30-ed9145141ea5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a0a1759-2810-4c92-ad30-ed9145141ea5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6fe0061-69ec-462b-b7a3-b2702ed54d4c' class='xr-var-data-in' type='checkbox'><label for='data-c6fe0061-69ec-462b-b7a3-b2702ed54d4c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-940e27a9-7bcb-4fd8-8c7c-8a8751268427' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-940e27a9-7bcb-4fd8-8c7c-8a8751268427' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12ba3fcb-7151-40f3-83db-4bf1e20552b3' class='xr-var-data-in' type='checkbox'><label for='data-12ba3fcb-7151-40f3-83db-4bf1e20552b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4928f9dd-ff9f-4401-8dbb-c2c5f90ac7e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4928f9dd-ff9f-4401-8dbb-c2c5f90ac7e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe5ded26-d288-4638-a24a-6729376434cf' class='xr-var-data-in' type='checkbox'><label for='data-fe5ded26-d288-4638-a24a-6729376434cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-529cc299-29e1-446e-b879-b9cce7dacbbb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-529cc299-29e1-446e-b879-b9cce7dacbbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a39c99e7-9b51-4c1b-8de2-af5fb2462b0d' class='xr-var-data-in' type='checkbox'><label for='data-a39c99e7-9b51-4c1b-8de2-af5fb2462b0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 16 B </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2,) </td>\n",
+       "                        <td> (2,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,30.000000)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-9a2ceb22-b0c5-4abb-8b20-cf6187929c2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a2ceb22-b0c5-4abb-8b20-cf6187929c2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a0e79d3-ee63-4a4b-bbef-70b763bad94c' class='xr-var-data-in' type='checkbox'><label for='data-4a0e79d3-ee63-4a4b-bbef-70b763bad94c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 16 B </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2,) </td>\n",
+       "                        <td> (2,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,30.000000)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-992.6</div><input id='attrs-f466ad22-d19e-4f26-b457-7f98ede59adf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f466ad22-d19e-4f26-b457-7f98ede59adf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5299ccd4-de61-4e59-a6a6-9fe3cefe29e7' class='xr-var-data-in' type='checkbox'><label for='data-5299ccd4-de61-4e59-a6a6-9fe3cefe29e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array(-992.55609512)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-95547b69-4a81-4ada-a968-fbcf2fb2e771' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95547b69-4a81-4ada-a968-fbcf2fb2e771' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-845c970d-303f-4304-bbef-d90e29eafec7' class='xr-var-data-in' type='checkbox'><label for='data-845c970d-303f-4304-bbef-d90e29eafec7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 16 B </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2,) </td>\n",
+       "                        <td> (2,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,30.000000)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-e0b26014-f400-46ac-8dff-27df86cc2af6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0b26014-f400-46ac-8dff-27df86cc2af6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-010a58bf-3dc0-4f5c-bd2a-8b7429b526d8' class='xr-var-data-in' type='checkbox'><label for='data-010a58bf-3dc0-4f5c-bd2a-8b7429b526d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-8e9505b6-7416-4ecb-b721-e6980e4a10f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8e9505b6-7416-4ecb-b721-e6980e4a10f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d81abd4-f099-49b1-8ec6-e14355199085' class='xr-var-data-in' type='checkbox'><label for='data-9d81abd4-f099-49b1-8ec6-e14355199085' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 7 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-443b222b-8db3-4fe6-9ba8-b9cee925deeb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-443b222b-8db3-4fe6-9ba8-b9cee925deeb' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-ba6f9b1a-b167-4987-9777-3c3e132db94d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba6f9b1a-b167-4987-9777-3c3e132db94d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a304aff-e616-4677-abae-b8bfa6f4c7e9' class='xr-var-data-in' type='checkbox'><label for='data-9a304aff-e616-4677-abae-b8bfa6f4c7e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-4f29448a-29aa-43b1-b72d-5ae9b70c45a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f29448a-29aa-43b1-b72d-5ae9b70c45a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0fef89f-1b64-44e8-adbb-f266b754b24f' class='xr-var-data-in' type='checkbox'><label for='data-a0fef89f-1b64-44e8-adbb-f266b754b24f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8 B </td>\n",
+       "                        <td> 8 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> () </td>\n",
+       "                        <td> () </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        \n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-39ac93a5-4026-48fd-87af-1c5004ae5412' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39ac93a5-4026-48fd-87af-1c5004ae5412' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-265bd1ed-82b4-49f7-a768-bd87dd752308' class='xr-var-data-in' type='checkbox'><label for='data-265bd1ed-82b4-49f7-a768-bd87dd752308' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8 B </td>\n",
+       "                        <td> 8 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> () </td>\n",
+       "                        <td> () </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        \n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-fe48dfe7-023b-430a-b0c6-b496f3c04ab1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe48dfe7-023b-430a-b0c6-b496f3c04ab1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a05154d9-5474-4367-a50c-e144932c6f06' class='xr-var-data-in' type='checkbox'><label for='data-a05154d9-5474-4367-a50c-e144932c6f06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 50.62 MiB </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3846fee4-2bf6-42a2-86cf-91a16f280370' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3846fee4-2bf6-42a2-86cf-91a16f280370' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3195e27-f468-4a1a-896b-f844e177b62d' class='xr-var-data-in' type='checkbox'><label for='data-d3195e27-f468-4a1a-896b-f844e177b62d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-0b476db0-4f81-48d4-8ad0-41ea2cca418b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b476db0-4f81-48d4-8ad0-41ea2cca418b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71441b2e-e84c-49e1-a579-15eb8f3a512f' class='xr-var-data-in' type='checkbox'><label for='data-71441b2e-e84c-49e1-a579-15eb8f3a512f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 50.62 MiB </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-01510107-7208-4d30-8a98-5f365cfa3460' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01510107-7208-4d30-8a98-5f365cfa3460' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68997643-058a-47db-a583-1f0597503b95' class='xr-var-data-in' type='checkbox'><label for='data-68997643-058a-47db-a583-1f0597503b95' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                        <td> 50.62 MiB </td>\n",
+       "                        <td> 25.31 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (1, 1, 120, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 2 chunks in 4 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-26de26ad-d18a-4771-a903-2ecdca6739e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26de26ad-d18a-4771-a903-2ecdca6739e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f4275b9-19b0-408e-a5f1-dcc64953670c' class='xr-var-data-in' type='checkbox'><label for='data-6f4275b9-19b0-408e-a5f1-dcc64953670c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 50.62 MiB </td>\n",
+       "                        <td> 25.31 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 240, 192, 288) </td>\n",
+       "                        <td> (1, 1, 120, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 2 chunks in 4 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5da3881a-ef28-470b-b7c6-8984cf32b5c5' class='xr-section-summary-in' type='checkbox'  ><label for='section-5da3881a-ef28-470b-b7c6-8984cf32b5c5' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-21cdf139-e5fe-4852-9136-966c5a04b155' class='xr-index-data-in' type='checkbox'/><label for='index-21cdf139-e5fe-4852-9136-966c5a04b155' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-81ba0b0d-a689-436a-a23a-9a89adf9ce51' class='xr-index-data-in' type='checkbox'/><label for='index-81ba0b0d-a689-436a-a23a-9a89adf9ce51' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a25c9db7-9ebe-415d-ad0c-bd27c56c5946' class='xr-index-data-in' type='checkbox'/><label for='index-a25c9db7-9ebe-415d-ad0c-bd27c56c5946' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9f5b5461-705e-4951-b9cc-cf75e625aa71' class='xr-index-data-in' type='checkbox'/><label for='index-9f5b5461-705e-4951-b9cc-cf75e625aa71' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d095bdb9-3069-4c3f-9465-7f89984f096e' class='xr-index-data-in' type='checkbox'/><label for='index-d095bdb9-3069-4c3f-9465-7f89984f096e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,\n",
+       "             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,\n",
+       "             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,\n",
+       "             1990-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,\n",
+       "             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,\n",
+       "             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,\n",
+       "             2009-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4cf22325-da59-498a-a6eb-f10e7eb3f999' class='xr-section-summary-in' type='checkbox'  ><label for='section-4cf22325-da59-498a-a6eb-f10e7eb3f999' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 213MB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, time: 240)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (nbnd) float64 16B dask.array<chunksize=(2,), meta=np.ndarray>\n",
+       "    b_bnds          (nbnd) float64 16B dask.array<chunksize=(2,), meta=np.ndarray>\n",
+       "    lev             float64 8B -992.6\n",
+       "    lev_bnds        (nbnd) float64 16B dask.array<chunksize=(2,), meta=np.ndarray>\n",
+       "  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array<chunksize=(240, 2), meta=np.ndarray>\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    a               float64 8B dask.array<chunksize=(), meta=np.ndarray>\n",
+       "    b               float64 8B dask.array<chunksize=(), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 10, 192, 288), meta=np.ndarray>\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 53MB dask.array<chunksize=(10, 192, 288), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 120, 192, 288), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 120, 192, 288), meta=np.ndarray>\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss_s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f3a1471b810>"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dss_s['mmrso4'].isel(time=0).plot(robust=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## 3.2 Calculates variables and assign attributes! \n",
+    "Nice for plotting and to keep track of what is in your dataset (especially 'units' and 'standard_name'/'long_name' will be looked for by xarray."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dss['T_C'] = dss['tas']-273.15"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dss['T_C'] = dss['T_C'].assign_attrs({'units': '$^\\circ$C'})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;T_C&#x27; (member_id: 1, dcpp_init_year: 1, time: 240, lat: 192,\n",
+       "                         lon: 288)&gt; Size: 53MB\n",
+       "dask.array&lt;sub, shape=(1, 1, 240, 192, 288), dtype=float32, chunksize=(1, 1, 120, 192, 288), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...\n",
+       "Attributes:\n",
+       "    units:    $^\\circ$C</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'T_C'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 240</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-16f38a7b-0ebf-4356-85f4-7bd6d371b794' class='xr-array-in' type='checkbox' checked><label for='section-16f38a7b-0ebf-4356-85f4-7bd6d371b794' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 50.62 MiB </td>\n",
+       "                        <td> 25.31 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 240, 192, 288) </td>\n",
+       "                        <td> (1, 1, 120, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 2 chunks in 5 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"418\" height=\"188\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1</text>\n",
+       "  <text x=\"45.412617\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,45.412617,12.706308)\">1</text>\n",
+       "\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"95\" y1=\"0\" x2=\"153\" y2=\"58\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"95\" y1=\"80\" x2=\"153\" y2=\"138\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"95\" y1=\"0\" x2=\"95\" y2=\"80\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"153\" y1=\"58\" x2=\"153\" y2=\"138\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"95\" y1=\"0\" x2=\"215\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"153\" y1=\"58\" x2=\"273\" y2=\"58\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"95\" y1=\"0\" x2=\"153\" y2=\"58\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"215\" y1=\"0\" x2=\"273\" y2=\"58\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"95.0,0.0 215.0,0.0 273.8235294117647,58.82352941176471 153.8235294117647,58.82352941176471\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"153\" y1=\"58\" x2=\"273\" y2=\"58\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"153\" y1=\"138\" x2=\"273\" y2=\"138\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"153\" y1=\"58\" x2=\"153\" y2=\"138\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"273\" y1=\"58\" x2=\"273\" y2=\"138\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"213.823529\" y=\"158.823529\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >288</text>\n",
+       "  <text x=\"293.823529\" y=\"98.823529\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,293.823529,98.823529)\">192</text>\n",
+       "  <text x=\"114.411765\" y=\"129.411765\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,114.411765,129.411765)\">240</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-e7d8cacd-409d-4916-8d39-1f8ef9582fb9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e7d8cacd-409d-4916-8d39-1f8ef9582fb9' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-65b66b99-7dc1-46a8-bdc4-e7aa5b297397' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65b66b99-7dc1-46a8-bdc4-e7aa5b297397' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7d11e60-1fdb-4076-9e77-5efa6cafb5d7' class='xr-var-data-in' type='checkbox'><label for='data-b7d11e60-1fdb-4076-9e77-5efa6cafb5d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-1448faec-52ab-45ae-8a4b-cc65239e586b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1448faec-52ab-45ae-8a4b-cc65239e586b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d109ba0d-d109-4b74-ae85-f7574d58e60d' class='xr-var-data-in' type='checkbox'><label for='data-d109ba0d-d109-4b74-ae85-f7574d58e60d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-e8ae2ceb-cb32-41b5-b20d-c6babf9e98d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8ae2ceb-cb32-41b5-b20d-c6babf9e98d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d5b77a1-2a8f-462a-b092-f6471121d55b' class='xr-var-data-in' type='checkbox'><label for='data-9d5b77a1-2a8f-462a-b092-f6471121d55b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-adefa5e1-6e99-446a-ab2f-167ded05259e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-adefa5e1-6e99-446a-ab2f-167ded05259e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a62c5cac-a580-4ef3-9bf2-e2411754019f' class='xr-var-data-in' type='checkbox'><label for='data-a62c5cac-a580-4ef3-9bf2-e2411754019f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-3e6ea819-771c-4565-8b87-47699b71fb77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e6ea819-771c-4565-8b87-47699b71fb77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-690d11e8-6d16-4732-b5b5-0f5aba9daed7' class='xr-var-data-in' type='checkbox'><label for='data-690d11e8-6d16-4732-b5b5-0f5aba9daed7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1237dea0-a0a6-4478-a151-a902e0c42d4a' class='xr-section-summary-in' type='checkbox'  ><label for='section-1237dea0-a0a6-4478-a151-a902e0c42d4a' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-61a0a3c7-0356-4971-ac16-3bd27b5be525' class='xr-index-data-in' type='checkbox'/><label for='index-61a0a3c7-0356-4971-ac16-3bd27b5be525' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-68d52203-871e-49ca-b966-e1d5b9921179' class='xr-index-data-in' type='checkbox'/><label for='index-68d52203-871e-49ca-b966-e1d5b9921179' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-143021a4-2b62-4d2d-a365-88ba3c2ffa32' class='xr-index-data-in' type='checkbox'/><label for='index-143021a4-2b62-4d2d-a365-88ba3c2ffa32' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0c24e6c5-0f9c-4045-a50a-455b1e6a9a3f' class='xr-index-data-in' type='checkbox'/><label for='index-0c24e6c5-0f9c-4045-a50a-455b1e6a9a3f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7b65f158-4fca-48dc-b246-1d9e0d532a39' class='xr-index-data-in' type='checkbox'/><label for='index-7b65f158-4fca-48dc-b246-1d9e0d532a39' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,\n",
+       "             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,\n",
+       "             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,\n",
+       "             1990-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,\n",
+       "             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,\n",
+       "             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,\n",
+       "             2009-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-307a7d40-517b-4cf1-a617-dc2b56173972' class='xr-section-summary-in' type='checkbox'  checked><label for='section-307a7d40-517b-4cf1-a617-dc2b56173972' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\\circ$C</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'T_C' (member_id: 1, dcpp_init_year: 1, time: 240, lat: 192,\n",
+       "                         lon: 288)> Size: 53MB\n",
+       "dask.array<sub, shape=(1, 1, 240, 192, 288), dtype=float32, chunksize=(1, 1, 120, 192, 288), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...\n",
+       "Attributes:\n",
+       "    units:    $^\\circ$C"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss['T_C']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "<span style=\"color:green;font-weight:700;font-size:20px\">\n",
+    "May always be small things you need to adjust: \n",
+    "</span>\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "  --xr-background-color-row-odd: #313131;\n",
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+       ".xr-wrap {\n",
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+       "  min-width: 300px;\n",
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+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
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+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
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+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
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+       "  display: inline;\n",
+       "  margin-top: 0;\n",
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+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 240)&gt; Size: 2kB\n",
+       "array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)\n",
+       "Coordinates:\n",
+       "  * time     (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:00:00\n",
+       "Attributes:\n",
+       "    axis:           T\n",
+       "    bounds:         time_bnds\n",
+       "    standard_name:  time\n",
+       "    title:          time\n",
+       "    type:           double</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-62c80d0d-a472-4874-8239-941dd2d10deb' class='xr-array-in' type='checkbox' checked><label for='section-62c80d0d-a472-4874-8239-941dd2d10deb' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1990-01-15 12:00:00 1990-02-14 00:00:00 ... 2009-12-15 12:00:00</span></div><div class='xr-array-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></div></li><li class='xr-section-item'><input id='section-ab579307-1b0e-4fb0-8ef8-bf35a3a184f2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ab579307-1b0e-4fb0-8ef8-bf35a3a184f2' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-99fa0e1f-9fa4-4b2f-bc48-70e46fb197cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99fa0e1f-9fa4-4b2f-bc48-70e46fb197cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f867744f-7019-4dc3-a1b1-6bcb1024c141' class='xr-var-data-in' type='checkbox'><label for='data-f867744f-7019-4dc3-a1b1-6bcb1024c141' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9bc5c033-1bfa-4c3d-825d-fc87102f8df9' class='xr-section-summary-in' type='checkbox'  ><label for='section-9bc5c033-1bfa-4c3d-825d-fc87102f8df9' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-892fa850-3733-4c7f-ada4-f01f2f50a83b' class='xr-index-data-in' type='checkbox'/><label for='index-892fa850-3733-4c7f-ada4-f01f2f50a83b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,\n",
+       "             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,\n",
+       "             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,\n",
+       "             1990-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,\n",
+       "             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,\n",
+       "             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,\n",
+       "             2009-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-325bb4b6-dae6-4f96-9993-52675f554e60' class='xr-section-summary-in' type='checkbox'  checked><label for='section-325bb4b6-dae6-4f96-9993-52675f554e60' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'time' (time: 240)> Size: 2kB\n",
+       "array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)\n",
+       "Coordinates:\n",
+       "  * time     (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:00:00\n",
+       "Attributes:\n",
+       "    axis:           T\n",
+       "    bounds:         time_bnds\n",
+       "    standard_name:  time\n",
+       "    title:          time\n",
+       "    type:           double"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss['time']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "This calendar is in cftime and noLeap. Sometimes this causes issues when plotting timeseries, so just for fun we will convert to normal calendar because it's anyway monthly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_11040/4195133999.py:1: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
+      "  dss['time'] = dss['time'].to_dataframe().index.to_datetimeindex()\n"
+     ]
+    }
+   ],
+   "source": [
+    "dss['time'] = dss['time'].to_dataframe().index.to_datetimeindex()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 240)&gt; Size: 2kB\n",
+       "array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,\n",
+       "       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)\n",
+       "Coordinates:\n",
+       "  * time     (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12-15T12:...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-490a5e84-8a88-4335-8cf2-1c309452f016' class='xr-array-in' type='checkbox' checked><label for='section-490a5e84-8a88-4335-8cf2-1c309452f016' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1990-01-15T12:00:00 1990-02-14 ... 2009-11-15 2009-12-15T12:00:00</span></div><div class='xr-array-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,\n",
+       "       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-7a1cc611-d902-4d11-a3b8-bcffc6b3df78' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7a1cc611-d902-4d11-a3b8-bcffc6b3df78' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-15T12:00:00 ... 2009-12-...</div><input id='attrs-4366eef1-1e9a-40f4-8b1d-5eee2af69940' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4366eef1-1e9a-40f4-8b1d-5eee2af69940' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d806627-0850-4100-8aaf-7c60b9d474b2' class='xr-var-data-in' type='checkbox'><label for='data-1d806627-0850-4100-8aaf-7c60b9d474b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,\n",
+       "       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-369c5f38-0118-4899-9e9f-0076e859bafd' class='xr-section-summary-in' type='checkbox'  ><label for='section-369c5f38-0118-4899-9e9f-0076e859bafd' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ca77bca3-bbc6-41c6-ab6f-1e74c79d55d3' class='xr-index-data-in' type='checkbox'/><label for='index-ca77bca3-bbc6-41c6-ab6f-1e74c79d55d3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-15 12:00:00&#x27;, &#x27;1990-02-14 00:00:00&#x27;,\n",
+       "               &#x27;1990-03-15 12:00:00&#x27;, &#x27;1990-04-15 00:00:00&#x27;,\n",
+       "               &#x27;1990-05-15 12:00:00&#x27;, &#x27;1990-06-15 00:00:00&#x27;,\n",
+       "               &#x27;1990-07-15 12:00:00&#x27;, &#x27;1990-08-15 12:00:00&#x27;,\n",
+       "               &#x27;1990-09-15 00:00:00&#x27;, &#x27;1990-10-15 12:00:00&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2009-03-15 12:00:00&#x27;, &#x27;2009-04-15 00:00:00&#x27;,\n",
+       "               &#x27;2009-05-15 12:00:00&#x27;, &#x27;2009-06-15 00:00:00&#x27;,\n",
+       "               &#x27;2009-07-15 12:00:00&#x27;, &#x27;2009-08-15 12:00:00&#x27;,\n",
+       "               &#x27;2009-09-15 00:00:00&#x27;, &#x27;2009-10-15 12:00:00&#x27;,\n",
+       "               &#x27;2009-11-15 00:00:00&#x27;, &#x27;2009-12-15 12:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-25b8e1f0-67b3-4c93-860b-005702d58c4d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-25b8e1f0-67b3-4c93-860b-005702d58c4d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'time' (time: 240)> Size: 2kB\n",
+       "array(['1990-01-15T12:00:00.000000000', '1990-02-14T00:00:00.000000000',\n",
+       "       '1990-03-15T12:00:00.000000000', ..., '2009-10-15T12:00:00.000000000',\n",
+       "       '2009-11-15T00:00:00.000000000', '2009-12-15T12:00:00.000000000'],\n",
+       "      dtype='datetime64[ns]')\n",
+       "Coordinates:\n",
+       "  * time     (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12-15T12:..."
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss['time']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
+    "tags": []
+   },
+   "source": [
+    "\n",
+    "<span style=\"color:green;font-weight:700;font-size:20px\">\n",
+    "We get a warning, but it's ok as long as we know what we are doing. \n",
+    "</span>\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### 3.3 Convert longitude: \n",
+    "this data comes in 0--360 degrees, but often -180 to 180 is more convenient. So we can convert:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**NOTE:** Maybe you want to put this in a module? Or a package.. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
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+       "  padding-right: 10px;\n",
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+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
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+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
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+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 240)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * time            (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 2GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 53MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;\n",
+       "    T_C             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8179e209-a9b0-4b1d-8612-b0f578a502a6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8179e209-a9b0-4b1d-8612-b0f578a502a6' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6569d756-d1d8-446d-bd3a-5d2f913ba495' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6569d756-d1d8-446d-bd3a-5d2f913ba495' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-0ce22ada-6a97-4acd-bf37-b00822a7f00c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ce22ada-6a97-4acd-bf37-b00822a7f00c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09a3df3c-6f3a-42bd-805a-3abdb75de44a' class='xr-var-data-in' type='checkbox'><label for='data-09a3df3c-6f3a-42bd-805a-3abdb75de44a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-24ea265d-caab-40d9-ab3e-679f55865b94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24ea265d-caab-40d9-ab3e-679f55865b94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcbb4e9b-6afe-4a84-a2d1-b3033667546d' class='xr-var-data-in' type='checkbox'><label for='data-dcbb4e9b-6afe-4a84-a2d1-b3033667546d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-c9e7c052-7a12-4b55-b511-c59d0b68b97b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9e7c052-7a12-4b55-b511-c59d0b68b97b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce39dbba-1d92-4c1f-a911-d71690fb02c3' class='xr-var-data-in' type='checkbox'><label for='data-ce39dbba-1d92-4c1f-a911-d71690fb02c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-e22c37fd-1eb9-4fa5-a4f7-e1cb28378b07' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e22c37fd-1eb9-4fa5-a4f7-e1cb28378b07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64867cfe-ae54-43de-ad5b-d6ad62608ec4' class='xr-var-data-in' type='checkbox'><label for='data-64867cfe-ae54-43de-ad5b-d6ad62608ec4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-d0c9f6d9-50ea-49e6-a898-7c0b08879bd9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0c9f6d9-50ea-49e6-a898-7c0b08879bd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c9771e4-b806-45da-b8df-775ea3e26454' class='xr-var-data-in' type='checkbox'><label for='data-6c9771e4-b806-45da-b8df-775ea3e26454' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-67c57826-b33f-4182-839c-65151ed97fa6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67c57826-b33f-4182-839c-65151ed97fa6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f88e1d8-2bba-465e-a6c9-bfae41e0d34b' class='xr-var-data-in' type='checkbox'><label for='data-7f88e1d8-2bba-465e-a6c9-bfae41e0d34b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-2a467e0e-a2b2-49fe-a714-81bc0b54f7d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a467e0e-a2b2-49fe-a714-81bc0b54f7d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ab080bf-ebc9-43e2-b499-53fa3a018e5e' class='xr-var-data-in' type='checkbox'><label for='data-5ab080bf-ebc9-43e2-b499-53fa3a018e5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-19dd20e1-9626-4e81-8256-4164238bd171' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19dd20e1-9626-4e81-8256-4164238bd171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdd5f79a-8753-413f-b96b-c038c8da88ac' class='xr-var-data-in' type='checkbox'><label for='data-fdd5f79a-8753-413f-b96b-c038c8da88ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,\n",
+       "        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,\n",
+       "       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,\n",
+       "       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,\n",
+       "       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,\n",
+       "       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,\n",
+       "       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-f8fcc718-209c-4dc0-ab07-fe08d9e28c60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8fcc718-209c-4dc0-ab07-fe08d9e28c60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7442f197-9dd6-4609-9fc5-9f7af23a75d4' class='xr-var-data-in' type='checkbox'><label for='data-7442f197-9dd6-4609-9fc5-9f7af23a75d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-15T12:00:00 ... 2009-12-...</div><input id='attrs-cfd057c8-0c85-40da-8f1d-5f4d5d4485cf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cfd057c8-0c85-40da-8f1d-5f4d5d4485cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-429e084b-74c1-472e-bc1f-bfc6b42e5594' class='xr-var-data-in' type='checkbox'><label for='data-429e084b-74c1-472e-bc1f-bfc6b42e5594' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,\n",
+       "       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-f85e04c7-a70a-4652-90c0-2be4f9b7ce17' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f85e04c7-a70a-4652-90c0-2be4f9b7ce17' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcfb9e9f-8ad6-42f2-bfce-499d057fb309' class='xr-var-data-in' type='checkbox'><label for='data-dcfb9e9f-8ad6-42f2-bfce-499d057fb309' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 7 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">240</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-b23b2dbf-5d5d-43cb-a92f-30786be24e28' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b23b2dbf-5d5d-43cb-a92f-30786be24e28' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-48d14d0e-3a70-4a00-8572-d6b3826906ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48d14d0e-3a70-4a00-8572-d6b3826906ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-905ed74b-6bdc-461d-bb4d-6e1460d8d763' class='xr-var-data-in' type='checkbox'><label for='data-905ed74b-6bdc-461d-bb4d-6e1460d8d763' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-0d674740-8e70-43fd-baf2-75baf06d9a7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d674740-8e70-43fd-baf2-75baf06d9a7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fa67ef9-269c-4238-8319-f9716b64e098' class='xr-var-data-in' type='checkbox'><label for='data-7fa67ef9-269c-4238-8319-f9716b64e098' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32,) </td>\n",
+       "                        <td> (32,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-e609c5e1-f1d9-4aba-9a32-04d89d60c204' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e609c5e1-f1d9-4aba-9a32-04d89d60c204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5deeafdb-494c-4536-8942-658ed6c04583' class='xr-var-data-in' type='checkbox'><label for='data-5deeafdb-494c-4536-8942-658ed6c04583' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
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+       "                        <td> </td>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32,) </td>\n",
+       "                        <td> (32,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-17ecd75c-a24b-403c-9d79-0f40e092ecc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17ecd75c-a24b-403c-9d79-0f40e092ecc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e04b193-4a31-4a3a-acd5-8d7bfd90371c' class='xr-var-data-in' type='checkbox'><label for='data-1e04b193-4a31-4a3a-acd5-8d7bfd90371c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.58 GiB </td>\n",
+       "                        <td> 67.50 MiB </td>\n",
+       "                    </tr>\n",
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+       "                        <th> Shape </th>\n",
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+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 24 chunks in 4 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ac2cde97-181f-4634-a761-0ee26d6b1ee1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac2cde97-181f-4634-a761-0ee26d6b1ee1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a42554ce-7ec7-4ca7-b3a5-86ab1d7fe384' class='xr-var-data-in' type='checkbox'><label for='data-a42554ce-7ec7-4ca7-b3a5-86ab1d7fe384' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-f8cd291f-d6ab-4070-9ac5-5d5b0195e1ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8cd291f-d6ab-4070-9ac5-5d5b0195e1ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7aa083ae-6856-49c9-9f14-0c4a60936725' class='xr-var-data-in' type='checkbox'><label for='data-7aa083ae-6856-49c9-9f14-0c4a60936725' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
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+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T_C</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-4d1ef398-8b63-4c47-b95a-6d101831399b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d1ef398-8b63-4c47-b95a-6d101831399b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2c028b3-6033-4cdd-866b-6d4a710fccee' class='xr-var-data-in' type='checkbox'><label for='data-d2c028b3-6033-4cdd-866b-6d4a710fccee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\\circ$C</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 50.62 MiB </td>\n",
+       "                        <td> 25.31 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 240, 192, 288) </td>\n",
+       "                        <td> (1, 1, 120, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 2 chunks in 5 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"418\" height=\"188\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
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+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
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+       "\n",
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+       "\n",
+       "\n",
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+       "\n",
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+       "  <text x=\"114.411765\" y=\"129.411765\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,114.411765,129.411765)\">240</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b3194e2-0335-4ffc-aedb-549008e33ac6' class='xr-section-summary-in' type='checkbox'  ><label for='section-6b3194e2-0335-4ffc-aedb-549008e33ac6' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a2411746-f485-4773-a663-04513e4e8361' class='xr-index-data-in' type='checkbox'/><label for='index-a2411746-f485-4773-a663-04513e4e8361' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7956913a-78ad-4c48-a0d4-f7d1fdffe4c6' class='xr-index-data-in' type='checkbox'/><label for='index-7956913a-78ad-4c48-a0d4-f7d1fdffe4c6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,\n",
+       "        11.25,\n",
+       "       ...\n",
+       "        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,\n",
+       "       358.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2b1504f1-debf-4e96-af49-948fba1ad173' class='xr-index-data-in' type='checkbox'/><label for='index-2b1504f1-debf-4e96-af49-948fba1ad173' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b330423a-a2e0-48e1-ae01-8ace5526ad7c' class='xr-index-data-in' type='checkbox'/><label for='index-b330423a-a2e0-48e1-ae01-8ace5526ad7c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c8f7eba7-82df-4eac-961a-668b4fa20f24' class='xr-index-data-in' type='checkbox'/><label for='index-c8f7eba7-82df-4eac-961a-668b4fa20f24' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,\n",
+       "       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,\n",
+       "        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,\n",
+       "        -87.82123029232025, -103.31712663173676, -121.54724076390266,\n",
+       "       -142.99403876066208, -168.22507977485657,  -197.9080867022276,\n",
+       "       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,\n",
+       "       -379.10090386867523,   -445.992574095726,  -524.6871747076511,\n",
+       "        -609.7786948084831,  -691.3894303143024,   -763.404481112957,\n",
+       "        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,\n",
+       "         -912.644546944648,  -936.1983984708786,   -957.485479535535,\n",
+       "         -976.325407391414,   -992.556095123291],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d46453f2-e055-4de5-a4c5-61ff4a5d8c1a' class='xr-index-data-in' type='checkbox'/><label for='index-d46453f2-e055-4de5-a4c5-61ff4a5d8c1a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-15 12:00:00&#x27;, &#x27;1990-02-14 00:00:00&#x27;,\n",
+       "               &#x27;1990-03-15 12:00:00&#x27;, &#x27;1990-04-15 00:00:00&#x27;,\n",
+       "               &#x27;1990-05-15 12:00:00&#x27;, &#x27;1990-06-15 00:00:00&#x27;,\n",
+       "               &#x27;1990-07-15 12:00:00&#x27;, &#x27;1990-08-15 12:00:00&#x27;,\n",
+       "               &#x27;1990-09-15 00:00:00&#x27;, &#x27;1990-10-15 12:00:00&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2009-03-15 12:00:00&#x27;, &#x27;2009-04-15 00:00:00&#x27;,\n",
+       "               &#x27;2009-05-15 12:00:00&#x27;, &#x27;2009-06-15 00:00:00&#x27;,\n",
+       "               &#x27;2009-07-15 12:00:00&#x27;, &#x27;2009-08-15 12:00:00&#x27;,\n",
+       "               &#x27;2009-09-15 00:00:00&#x27;, &#x27;2009-10-15 12:00:00&#x27;,\n",
+       "               &#x27;2009-11-15 00:00:00&#x27;, &#x27;2009-12-15 12:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0658d920-9972-4c8d-ad0f-f8e397f8abc2' class='xr-section-summary-in' type='checkbox'  ><label for='section-0658d920-9972-4c8d-ad0f-f8e397f8abc2' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2GB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     nbnd: 2, lev: 32, time: 240)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * time            (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array<chunksize=(240, 2), meta=np.ndarray>\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    a               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    b               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 2GB dask.array<chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray>\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time, lat, lon) float32 53MB dask.array<chunksize=(10, 192, 288), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 120, 192, 288), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 120, 192, 288), meta=np.ndarray>\n",
+       "    T_C             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array<chunksize=(1, 1, 120, 192, 288), meta=np.ndarray>\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def convert_lon_to_180(ds):\n",
+    "    ds['lon'] =(ds['lon']+ 180) % 360 - 180\n",
+    "    ds = ds.sortby('lon')\n",
+    "    return ds\n",
+    "\n",
+    "def convert_lon_to_360(ds):\n",
+    "    ds['lon'] =ds['lon']% 360\n",
+    "    ds = ds.sortby('lon')\n",
+    "    return lon % 360"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "(migth want to move this to a module!) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dss = convert_lon_to_180(dss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dss['lon'].attrs['units'] = '$^\\circ$ East'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Notice how the labels use both the attribute \"standard_name\" and \"units\" from the dataset. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 4. The easiest interpolation: select with 'nearest' neighboor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f39f04b5a90>"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dss['T_C'].sel(lon=1.3,method='nearest').plot(x='time')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Example: let's select zeppelin station: \n",
+    "78.906661, 11.889203"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "lat_zep =78.906661\n",
+    "lon_zep = 11.889203"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f39f0598090>]"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dss['T_C'].sel(lon=lon_zep, lat=lat_zep, method='nearest').plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Super quick averaging etc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "da_so4 = dss['mmrso4']\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Mean: \n",
+    "  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f39f0552450>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "da_so4.mean(['time','lon'], keep_attrs=True).plot()#ylim=[1000,100], yscale='log')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "da_so4['lev'] = np.abs(da_so4['lev'].values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f39f030c790>"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "da_so4.mean(['time','lon'], keep_attrs=True).plot(ylim=[1000,100], yscale='log')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Standard deviation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f39f0291b10>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dss['T_C'].std(['time']).plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Temperature change much stronger over land than ocean..."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Mask data and groupby: pick out seasons"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "month = ds['time.month']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;month&#x27; (time: 1980)&gt; Size: 16kB\n",
+       "array([ 1,  2,  3, ..., 10, 11, 12])\n",
+       "Coordinates:\n",
+       "  * time     (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'month'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2a309a11-032f-421d-a589-d0a3343b8af3' class='xr-array-in' type='checkbox' checked><label for='section-2a309a11-032f-421d-a589-d0a3343b8af3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 ... 11 12 1 2 3 4 5 6 7 8 9 10 11 12</span></div><div class='xr-array-data'><pre>array([ 1,  2,  3, ..., 10, 11, 12])</pre></div></div></li><li class='xr-section-item'><input id='section-2a3f6928-3e08-4d17-a633-1ba797e235a7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2a3f6928-3e08-4d17-a633-1ba797e235a7' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-3da7b6aa-5114-482b-b16c-048387c6080b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3da7b6aa-5114-482b-b16c-048387c6080b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-527ab759-689a-414b-ad1c-c381e44c8d78' class='xr-var-data-in' type='checkbox'><label for='data-527ab759-689a-414b-ad1c-c381e44c8d78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f2836d4-b0f0-4792-ae7a-3ee1851d9ec1' class='xr-section-summary-in' type='checkbox'  ><label for='section-0f2836d4-b0f0-4792-ae7a-3ee1851d9ec1' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3e48fa5b-d994-4bc9-901a-87d20abe4dca' class='xr-index-data-in' type='checkbox'/><label for='index-3e48fa5b-d994-4bc9-901a-87d20abe4dca' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,\n",
+       "             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,\n",
+       "             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,\n",
+       "             1850-10-15 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,\n",
+       "             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,\n",
+       "             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,\n",
+       "             2014-12-15 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5d4e7c82-90a2-4824-a835-c93c553f5c5d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5d4e7c82-90a2-4824-a835-c93c553f5c5d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'month' (time: 1980)> Size: 16kB\n",
+       "array([ 1,  2,  3, ..., 10, 11, 12])\n",
+       "Coordinates:\n",
+       "  * time     (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dss_JA = dss.where(month.isin([7,8])).mean('time')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
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+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
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+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
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+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
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+       "\n",
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+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
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+       "\n",
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+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
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+       "\n",
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+       "  color: var(--xr-disabled-color);\n",
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+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 8MB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     lev: 32, nbnd: 2)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB -180.0 -178.8 -177.5 ... 176.2 177.5 178.8\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, lev, lat, lon) float32 7MB dask.array&lt;chunksize=(1, 1, 32, 192, 288), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B nan\n",
+       "    ps              (lat, lon) float32 221kB dask.array&lt;chunksize=(192, 288), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    T_C             (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6ab30d99-93fd-4a8d-b514-649f48821b91' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6ab30d99-93fd-4a8d-b514-649f48821b91' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span>nbnd</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b49dabfd-500b-4dda-be36-4f781a1b63b5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b49dabfd-500b-4dda-be36-4f781a1b63b5' class='xr-section-summary' >Coordinates: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-33674f01-9e3e-4510-83bd-5ad3122bf446' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33674f01-9e3e-4510-83bd-5ad3122bf446' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46fe1050-0dcb-4247-8918-b40600bdab39' class='xr-var-data-in' type='checkbox'><label for='data-46fe1050-0dcb-4247-8918-b40600bdab39' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -178.8 ... 177.5 178.8</div><input id='attrs-eaeb27f9-120a-4444-a916-687dee503e8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eaeb27f9-120a-4444-a916-687dee503e8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20c24ddb-3ffa-4a96-8aa0-a8533cad96a1' class='xr-var-data-in' type='checkbox'><label for='data-20c24ddb-3ffa-4a96-8aa0-a8533cad96a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array([-180.  , -178.75, -177.5 , ...,  176.25,  177.5 ,  178.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-5a480531-0240-4ea9-808b-b3a416e2dd79' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5a480531-0240-4ea9-808b-b3a416e2dd79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e94ea6be-fe52-4a24-9383-823e5b3ae83e' class='xr-var-data-in' type='checkbox'><label for='data-e94ea6be-fe52-4a24-9383-823e5b3ae83e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5abde633-e641-4220-a919-375f20c5ae30' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5abde633-e641-4220-a919-375f20c5ae30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-871d6ac5-16ff-4612-a23c-09cc01904708' class='xr-var-data-in' type='checkbox'><label for='data-871d6ac5-16ff-4612-a23c-09cc01904708' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-2f97f747-3b6a-4625-a797-86d347b84e83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f97f747-3b6a-4625-a797-86d347b84e83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-919ef6ea-69c9-4994-bd47-8369e7553277' class='xr-var-data-in' type='checkbox'><label for='data-919ef6ea-69c9-4994-bd47-8369e7553277' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,\n",
+       "        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,\n",
+       "       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,\n",
+       "       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,\n",
+       "       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,\n",
+       "       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,\n",
+       "       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-3adcf97c-29ea-48d6-93fd-a5e279d254a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3adcf97c-29ea-48d6-93fd-a5e279d254a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0343f0ee-7db1-4fa8-8049-a7f25a1c7245' class='xr-var-data-in' type='checkbox'><label for='data-0343f0ee-7db1-4fa8-8049-a7f25a1c7245' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 14 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-4bc0a916-5aaf-411e-8f92-a8042b2c31ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bc0a916-5aaf-411e-8f92-a8042b2c31ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb1a9a7f-dd5e-4b10-afad-c864cb72e5ec' class='xr-var-data-in' type='checkbox'><label for='data-bb1a9a7f-dd5e-4b10-afad-c864cb72e5ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-9a29220f-77bd-4220-8ba2-1047392e3d3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a29220f-77bd-4220-8ba2-1047392e3d3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2b8d808-8f39-40b9-bb33-16abcf1cc146' class='xr-var-data-in' type='checkbox'><label for='data-a2b8d808-8f39-40b9-bb33-16abcf1cc146' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-6ecfb1a7-833b-4f7b-9cdf-3909919d44f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ecfb1a7-833b-4f7b-9cdf-3909919d44f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bad563a1-53a4-4fd5-bb5d-02820b4f2ea5' class='xr-var-data-in' type='checkbox'><label for='data-bad563a1-53a4-4fd5-bb5d-02820b4f2ea5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
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+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 9 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-b5656784-5d2b-4cd0-a88a-8ffff282c9b2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b5656784-5d2b-4cd0-a88a-8ffff282c9b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59d347c0-3df9-4260-af59-daabc39ea097' class='xr-var-data-in' type='checkbox'><label for='data-59d347c0-3df9-4260-af59-daabc39ea097' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (32,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 7 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-5c477237-b74a-4276-8fe8-c669721bf56f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5c477237-b74a-4276-8fe8-c669721bf56f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a758ca3-59b5-4aa1-a909-643485e9f6ee' class='xr-var-data-in' type='checkbox'><label for='data-6a758ca3-59b5-4aa1-a909-643485e9f6ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 256 B </td>\n",
+       "                        <td> 256 B </td>\n",
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+       "                    \n",
+       "                    <tr>\n",
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+       "                        <td> (32,) </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-cf9a6892-b1f2-450a-8381-338ff7b5b314' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf9a6892-b1f2-450a-8381-338ff7b5b314' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d03878ec-e447-4e3a-9180-631cee6634e3' class='xr-var-data-in' type='checkbox'><label for='data-d03878ec-e447-4e3a-9180-631cee6634e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-72902d10-d78e-454b-8823-0bbd50dc110b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-72902d10-d78e-454b-8823-0bbd50dc110b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6eb6db53-9cf1-4ada-879c-3eac07e0cc5e' class='xr-var-data-in' type='checkbox'><label for='data-6eb6db53-9cf1-4ada-879c-3eac07e0cc5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(nan, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(192, 288), meta=np.ndarray&gt;</div><input id='attrs-d224ff9c-0258-4819-b332-2d38ab21a3c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d224ff9c-0258-4819-b332-2d38ab21a3c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3940d4d3-6538-4b71-a2af-b51a4186e86d' class='xr-var-data-in' type='checkbox'><label for='data-3940d4d3-6538-4b71-a2af-b51a4186e86d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (192, 288) </td>\n",
+       "                        <td> (192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 9 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-73598e69-6bb2-4af0-9dce-1b3e253da5ec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-73598e69-6bb2-4af0-9dce-1b3e253da5ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e119a1d8-8f8a-4396-81d8-c0eeac84dfa2' class='xr-var-data-in' type='checkbox'><label for='data-e119a1d8-8f8a-4396-81d8-c0eeac84dfa2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-f1ca5a7c-c139-4f4b-b951-73c6302c6ae6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f1ca5a7c-c139-4f4b-b951-73c6302c6ae6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-312ee31c-cbda-4a3a-ae84-fb892f4a7dea' class='xr-var-data-in' type='checkbox'><label for='data-312ee31c-cbda-4a3a-ae84-fb892f4a7dea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 10 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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+       "        </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T_C</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-9b8d747e-7931-454e-a4e0-8e8cbad8fb29' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b8d747e-7931-454e-a4e0-8e8cbad8fb29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2de619ec-eaef-4edb-a870-664b6a855668' class='xr-var-data-in' type='checkbox'><label for='data-2de619ec-eaef-4edb-a870-664b6a855668' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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+       "                        <td> </td>\n",
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+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
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+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
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+       "                    <tr>\n",
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+       "                    <tr>\n",
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+       "        </td>\n",
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+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-afffb41d-9621-4b5e-adc8-c877c3ce864b' class='xr-section-summary-in' type='checkbox'  ><label for='section-afffb41d-9621-4b5e-adc8-c877c3ce864b' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ca81f464-b384-4eb9-add6-71630534c652' class='xr-index-data-in' type='checkbox'/><label for='index-ca81f464-b384-4eb9-add6-71630534c652' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-11a637df-ec17-4c79-9034-0b27214101c9' class='xr-index-data-in' type='checkbox'/><label for='index-11a637df-ec17-4c79-9034-0b27214101c9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -180.0, -178.75,  -177.5, -176.25,  -175.0, -173.75,  -172.5, -171.25,\n",
+       "        -170.0, -168.75,\n",
+       "       ...\n",
+       "         167.5,  168.75,   170.0,  171.25,   172.5,  173.75,   175.0,  176.25,\n",
+       "         177.5,  178.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-14644386-645b-432a-bcab-0a3a1945e5d7' class='xr-index-data-in' type='checkbox'/><label for='index-14644386-645b-432a-bcab-0a3a1945e5d7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0cc5da31-f29a-4f4c-b685-5dfa5a4fb211' class='xr-index-data-in' type='checkbox'/><label for='index-0cc5da31-f29a-4f4c-b685-5dfa5a4fb211' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ddf25b1e-7433-42c4-ad0e-223c9f08fe04' class='xr-index-data-in' type='checkbox'/><label for='index-ddf25b1e-7433-42c4-ad0e-223c9f08fe04' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,\n",
+       "       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,\n",
+       "        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,\n",
+       "        -87.82123029232025, -103.31712663173676, -121.54724076390266,\n",
+       "       -142.99403876066208, -168.22507977485657,  -197.9080867022276,\n",
+       "       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,\n",
+       "       -379.10090386867523,   -445.992574095726,  -524.6871747076511,\n",
+       "        -609.7786948084831,  -691.3894303143024,   -763.404481112957,\n",
+       "        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,\n",
+       "         -912.644546944648,  -936.1983984708786,   -957.485479535535,\n",
+       "         -976.325407391414,   -992.556095123291],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-41449b54-fe2f-4e0d-9fca-9e6f7586284c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-41449b54-fe2f-4e0d-9fca-9e6f7586284c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 8MB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,\n",
+       "                     lev: 32, nbnd: 2)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB -180.0 -178.8 -177.5 ... 176.2 177.5 178.8\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    a               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    b               (lev) float64 256B dask.array<chunksize=(32,), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, lev, lat, lon) float32 7MB dask.array<chunksize=(1, 1, 32, 192, 288), meta=np.ndarray>\n",
+       "    p0              float32 4B nan\n",
+       "    ps              (lat, lon) float32 221kB dask.array<chunksize=(192, 288), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>\n",
+       "    T_C             (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array<chunksize=(1, 1, 192, 288), meta=np.ndarray>"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss_JA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dss_season = dss.groupby('time.season').mean(keep_attrs=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
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+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 33MB\n",
+       "Dimensions:         (season: 4, member_id: 1, dcpp_init_year: 1, lev: 32,\n",
+       "                     lat: 192, lon: 288, nbnd: 2)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB -180.0 -178.8 -177.5 ... 176.2 177.5 178.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;\n",
+       "  * season          (season) object 32B &#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    mmrso4          (season, member_id, dcpp_init_year, lev, lat, lon) float32 28MB dask.array&lt;chunksize=(4, 1, 1, 32, 192, 288), meta=np.ndarray&gt;\n",
+       "    ps              (season, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 192, 288), meta=np.ndarray&gt;\n",
+       "    hurs            (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    tas             (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    T_C             (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    areacella       (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;\n",
+       "    a               (season, lev) float64 1kB dask.array&lt;chunksize=(4, 32), meta=np.ndarray&gt;\n",
+       "    b               (season, lev) float64 1kB dask.array&lt;chunksize=(4, 32), meta=np.ndarray&gt;\n",
+       "    p0              (season) float32 16B 1e+05 1e+05 1e+05 1e+05\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5ff0d995-95bf-42b1-a6bd-b81b0b926176' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5ff0d995-95bf-42b1-a6bd-b81b0b926176' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>season</span>: 4</li><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a669e3fc-7e94-425e-9750-22339f68faaa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a669e3fc-7e94-425e-9750-22339f68faaa' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-67aa772d-3b21-4ee7-bf03-a6b854483a24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67aa772d-3b21-4ee7-bf03-a6b854483a24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9504ae63-bb8a-4835-9633-0cd567bb24bb' class='xr-var-data-in' type='checkbox'><label for='data-9504ae63-bb8a-4835-9633-0cd567bb24bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -178.8 ... 177.5 178.8</div><input id='attrs-679ccd82-84bc-409f-8157-f954622bdc9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-679ccd82-84bc-409f-8157-f954622bdc9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86ee9e78-b931-4b76-b8e3-fc28643445b3' class='xr-var-data-in' type='checkbox'><label for='data-86ee9e78-b931-4b76-b8e3-fc28643445b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array([-180.  , -178.75, -177.5 , ...,  176.25,  177.5 ,  178.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-d21f7fb7-d74b-46d5-9cbc-bf9650c98958' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d21f7fb7-d74b-46d5-9cbc-bf9650c98958' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78c9847a-b205-4fec-b66f-36d4f0008a8e' class='xr-var-data-in' type='checkbox'><label for='data-78c9847a-b205-4fec-b66f-36d4f0008a8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                        <td> 4.50 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                        <td> (288, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 14 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">288</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-24595160-8f93-4f2b-97ec-cda7a99914c0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24595160-8f93-4f2b-97ec-cda7a99914c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-358bcf22-f5b6-4060-82c1-0eaa229b3aad' class='xr-var-data-in' type='checkbox'><label for='data-358bcf22-f5b6-4060-82c1-0eaa229b3aad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-326f7d5d-372a-48f8-a8a4-9d55a797bf8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-326f7d5d-372a-48f8-a8a4-9d55a797bf8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05f703db-f19e-4574-901b-18b6eff27690' class='xr-var-data-in' type='checkbox'><label for='data-05f703db-f19e-4574-901b-18b6eff27690' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-6c953831-4148-4495-8aba-88de59c30ca0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c953831-4148-4495-8aba-88de59c30ca0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a4f3514-dd5a-4098-b102-1182e7860e38' class='xr-var-data-in' type='checkbox'><label for='data-1a4f3514-dd5a-4098-b102-1182e7860e38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-9cbea943-163c-4145-93dc-1b440f80db1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cbea943-163c-4145-93dc-1b440f80db1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1718c8d3-689f-4948-a94d-b91bee022f3e' class='xr-var-data-in' type='checkbox'><label for='data-1718c8d3-689f-4948-a94d-b91bee022f3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-d729580e-4513-4ff4-834c-22bef5b44e9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d729580e-4513-4ff4-834c-22bef5b44e9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b86b27b-f5e9-47a1-bdeb-b34e7dff51ef' class='xr-var-data-in' type='checkbox'><label for='data-6b86b27b-f5e9-47a1-bdeb-b34e7dff51ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,\n",
+       "        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,\n",
+       "       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,\n",
+       "       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,\n",
+       "       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,\n",
+       "       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,\n",
+       "       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-bad7011a-cf4e-4b48-aeaa-45f4c81a5b39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bad7011a-cf4e-4b48-aeaa-45f4c81a5b39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7122bbb3-cfd6-46ca-b58b-4e63d64aec3e' class='xr-var-data-in' type='checkbox'><label for='data-7122bbb3-cfd6-46ca-b58b-4e63d64aec3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512 B </td>\n",
+       "                        <td> 512 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                        <td> (32, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"85\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"35\" y1=\"0\" x2=\"35\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"17.929774\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"55.859547\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,55.859547,60.000000)\">32</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>season</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</div><input id='attrs-1bc04582-f52e-413c-9eee-777bef806aae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1bc04582-f52e-413c-9eee-777bef806aae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f709ec84-86d4-4be2-8a7d-1fe32ba0d348' class='xr-var-data-in' type='checkbox'><label for='data-f709ec84-86d4-4be2-8a7d-1fe32ba0d348' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b9074222-9e80-4b6a-9b87-30c5d9da6f9e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b9074222-9e80-4b6a-9b87-30c5d9da6f9e' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(season, member_id, dcpp_init_year, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1, 1, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-4dde5401-d947-41ba-a253-23b03fa55ef2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dde5401-d947-41ba-a253-23b03fa55ef2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25cda548-382b-41ff-99dc-46b9c2d6d562' class='xr-var-data-in' type='checkbox'><label for='data-25cda548-382b-41ff-99dc-46b9c2d6d562' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 27.00 MiB </td>\n",
+       "                        <td> 27.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (4, 1, 1, 32, 192, 288) </td>\n",
+       "                        <td> (4, 1, 1, 32, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 14 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"435\" height=\"153\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"25\" y2=\"15\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"10\" y1=\"25\" x2=\"25\" y2=\"41\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"15\" x2=\"25\" y2=\"41\" style=\"stroke-width:2\" />\n",
+       "\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(season, member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-9cb94b76-5f15-49b4-a2fe-cf5e40ca3487' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cb94b76-5f15-49b4-a2fe-cf5e40ca3487' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39392e18-3820-4a34-847c-fcb24e1c84d9' class='xr-var-data-in' type='checkbox'><label for='data-39392e18-3820-4a34-847c-fcb24e1c84d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 864.00 kiB </td>\n",
+       "                        <td> 864.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (4, 1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 12 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T_C</span></div><div class='xr-var-dims'>(season, member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-594bf1bd-fc36-46b7-a742-a71f31aaa09e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-594bf1bd-fc36-46b7-a742-a71f31aaa09e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78d50268-5a8b-48f5-85a9-4dd1c02512ab' class='xr-var-data-in' type='checkbox'><label for='data-78d50268-5a8b-48f5-85a9-4dd1c02512ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\\circ$C</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 864.00 kiB </td>\n",
+       "                        <td> 864.00 kiB </td>\n",
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+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (4, 1, 1, 192, 288) </td>\n",
+       "                        <td> (4, 1, 1, 192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 13 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(season, member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-88a7c5b5-a0f7-4c18-abac-d9edf6af93de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88a7c5b5-a0f7-4c18-abac-d9edf6af93de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9bd87d9-c7f3-4082-a953-6b0ea4673e67' class='xr-var-data-in' type='checkbox'><label for='data-d9bd87d9-c7f3-4082-a953-6b0ea4673e67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 864.00 kiB </td>\n",
+       "                        <td> 864.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (4, 1, 1, 192, 288) </td>\n",
+       "                        <td> (4, 1, 1, 192, 288) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(season, lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 32), meta=np.ndarray&gt;</div><input id='attrs-589fcc75-04ca-4413-b7b8-ebf977211c59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-589fcc75-04ca-4413-b7b8-ebf977211c59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11f0d8ec-fbb9-42ea-a5d7-d8c49dc8fb1b' class='xr-var-data-in' type='checkbox'><label for='data-11f0d8ec-fbb9-42ea-a5d7-d8c49dc8fb1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.00 kiB </td>\n",
+       "                        <td> 1.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (4, 32) </td>\n",
+       "                        <td> (4, 32) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"89\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"39\" x2=\"120\" y2=\"39\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"39\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"39\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,39.793935054828374 0.0,39.793935054828374\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"59.793935\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >32</text>\n",
+       "  <text x=\"140.000000\" y=\"19.896968\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,19.896968)\">4</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(season, lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 32), meta=np.ndarray&gt;</div><input id='attrs-d5efbafa-7f51-4358-b014-6e22e8e458b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5efbafa-7f51-4358-b014-6e22e8e458b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85ae5e22-0ed0-48d7-9415-e4bedb143727' class='xr-var-data-in' type='checkbox'><label for='data-85ae5e22-0ed0-48d7-9415-e4bedb143727' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.00 kiB </td>\n",
+       "                        <td> 1.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (4, 32) </td>\n",
+       "                        <td> (4, 32) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"89\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"39\" x2=\"120\" y2=\"39\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"39\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"39\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,39.793935054828374 0.0,39.793935054828374\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"59.793935\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >32</text>\n",
+       "  <text x=\"140.000000\" y=\"19.896968\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,19.896968)\">4</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1e+05 1e+05 1e+05 1e+05</div><input id='attrs-d5a332a2-2c48-45fe-98f6-0345628f322e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5a332a2-2c48-45fe-98f6-0345628f322e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eea7dba5-97ed-416c-817a-1870aee3b861' class='xr-var-data-in' type='checkbox'><label for='data-eea7dba5-97ed-416c-817a-1870aee3b861' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>array([100000., 100000., 100000., 100000.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5bbc8f0a-93a8-4172-89e5-c518dad58609' class='xr-section-summary-in' type='checkbox'  ><label for='section-5bbc8f0a-93a8-4172-89e5-c518dad58609' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cf216927-486b-4029-80e0-ee3a3cc7a722' class='xr-index-data-in' type='checkbox'/><label for='index-cf216927-486b-4029-80e0-ee3a3cc7a722' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-82f9ed0f-6ef1-4c9c-92d8-11892eee777a' class='xr-index-data-in' type='checkbox'/><label for='index-82f9ed0f-6ef1-4c9c-92d8-11892eee777a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -180.0, -178.75,  -177.5, -176.25,  -175.0, -173.75,  -172.5, -171.25,\n",
+       "        -170.0, -168.75,\n",
+       "       ...\n",
+       "         167.5,  168.75,   170.0,  171.25,   172.5,  173.75,   175.0,  176.25,\n",
+       "         177.5,  178.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ba55cccf-2b75-4000-be73-8d2cbbf44ce0' class='xr-index-data-in' type='checkbox'/><label for='index-ba55cccf-2b75-4000-be73-8d2cbbf44ce0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f17db395-c967-44a2-9a7e-323f25a27dff' class='xr-index-data-in' type='checkbox'/><label for='index-f17db395-c967-44a2-9a7e-323f25a27dff' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-625f8b56-9dc8-43e3-bbb1-186468e6ccfe' class='xr-index-data-in' type='checkbox'/><label for='index-625f8b56-9dc8-43e3-bbb1-186468e6ccfe' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,\n",
+       "       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,\n",
+       "        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,\n",
+       "        -87.82123029232025, -103.31712663173676, -121.54724076390266,\n",
+       "       -142.99403876066208, -168.22507977485657,  -197.9080867022276,\n",
+       "       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,\n",
+       "       -379.10090386867523,   -445.992574095726,  -524.6871747076511,\n",
+       "        -609.7786948084831,  -691.3894303143024,   -763.404481112957,\n",
+       "        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,\n",
+       "         -912.644546944648,  -936.1983984708786,   -957.485479535535,\n",
+       "         -976.325407391414,   -992.556095123291],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>season</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-eed6bbcb-db72-452c-ab4c-a301a6904771' class='xr-index-data-in' type='checkbox'/><label for='index-eed6bbcb-db72-452c-ab4c-a301a6904771' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=&#x27;object&#x27;, name=&#x27;season&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2ee5b3f0-ef63-466b-b5ac-4a47f9908646' class='xr-section-summary-in' type='checkbox'  ><label for='section-2ee5b3f0-ef63-466b-b5ac-4a47f9908646' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 33MB\n",
+       "Dimensions:         (season: 4, member_id: 1, dcpp_init_year: 1, lev: 32,\n",
+       "                     lat: 192, lon: 288, nbnd: 2)\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB -180.0 -178.8 -177.5 ... 176.2 177.5 178.8\n",
+       "    lon_bnds        (lon, nbnd) float64 5kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "    b_bnds          (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6\n",
+       "    lev_bnds        (lev, nbnd) float64 512B dask.array<chunksize=(32, 2), meta=np.ndarray>\n",
+       "  * season          (season) object 32B 'DJF' 'JJA' 'MAM' 'SON'\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    mmrso4          (season, member_id, dcpp_init_year, lev, lat, lon) float32 28MB dask.array<chunksize=(4, 1, 1, 32, 192, 288), meta=np.ndarray>\n",
+       "    ps              (season, lat, lon) float32 885kB dask.array<chunksize=(4, 192, 288), meta=np.ndarray>\n",
+       "    hurs            (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array<chunksize=(4, 1, 1, 192, 288), meta=np.ndarray>\n",
+       "    tas             (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array<chunksize=(4, 1, 1, 192, 288), meta=np.ndarray>\n",
+       "    T_C             (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array<chunksize=(4, 1, 1, 192, 288), meta=np.ndarray>\n",
+       "    areacella       (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array<chunksize=(4, 1, 1, 192, 288), meta=np.ndarray>\n",
+       "    a               (season, lev) float64 1kB dask.array<chunksize=(4, 32), meta=np.ndarray>\n",
+       "    b               (season, lev) float64 1kB dask.array<chunksize=(4, 32), meta=np.ndarray>\n",
+       "    p0              (season) float32 16B 1e+05 1e+05 1e+05 1e+05\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss_season"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<xarray.plot.facetgrid.FacetGrid at 0x7f39e8560790>"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1300x300 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dss_season['T_C'].plot(col='season')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Controle the plot visuals:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<xarray.plot.facetgrid.FacetGrid at 0x7f37d5e02fd0>"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1300x300 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dss_season['T_C'].plot(col='season',\n",
+    "                       cmap = 'coolwarm',#ax=ax,\n",
+    "                       xlim=[-100,100],\n",
+    "                       cbar_kwargs={'label':'Temperature [$^\\circ$C]'}\n",
+    "                      )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# 5. Plotting with cartopy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import cartopy as cy\n",
+    "import cartopy.crs as ccrs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "da_plt = dss['mmrso4'].isel(lev=-1).mean('time', keep_attrs=True).squeeze()#('member_id')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;mmrso4&#x27; (lat: 192, lon: 288)&gt; Size: 221kB\n",
+       "dask.array&lt;getitem, shape=(192, 288), dtype=float32, chunksize=(192, 288), chunktype=numpy.ndarray&gt;\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB -180.0 -178.8 -177.5 ... 176.2 177.5 178.8\n",
+       "    member_id       &lt;U8 32B &#x27;r1i1p1f1&#x27;\n",
+       "    dcpp_init_year  float64 8B nan\n",
+       "    lev             float64 8B -992.6\n",
+       "Attributes: (12/19)\n",
+       "    cell_measures:  area: areacella\n",
+       "    cell_methods:   area: time: mean\n",
+       "    comment:        Dry mass of sulfate (SO4) in aerosol particles as a fract...\n",
+       "    description:    Dry mass of sulfate (SO4) in aerosol particles as a fract...\n",
+       "    frequency:      mon\n",
+       "    id:             mmrso4\n",
+       "    ...             ...\n",
+       "    time_label:     time-mean\n",
+       "    time_title:     Temporal mean\n",
+       "    title:          Aerosol Sulfate Mass Mixing Ratio\n",
+       "    type:           real\n",
+       "    units:          kg kg-1\n",
+       "    variable_id:    mmrso4</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'mmrso4'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-24680508-0ef3-4c9b-9ab5-c73ed099d6b5' class='xr-array-in' type='checkbox' checked><label for='section-24680508-0ef3-4c9b-9ab5-c73ed099d6b5' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(192, 288), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                        <td> 216.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (192, 288) </td>\n",
+       "                        <td> (192, 288) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 11 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"130\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"80\" x2=\"120\" y2=\"80\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"80\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"80\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,80.0 0.0,80.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"100.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >288</text>\n",
+       "  <text x=\"140.000000\" y=\"40.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,40.000000)\">192</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-8c8ef4d7-220b-4090-a4de-d51bcb1d4479' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8c8ef4d7-220b-4090-a4de-d51bcb1d4479' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-45d91863-1243-4621-9a88-48de2f77cfa0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45d91863-1243-4621-9a88-48de2f77cfa0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb66a534-0435-430c-abc4-8e5e6c566164' class='xr-var-data-in' type='checkbox'><label for='data-cb66a534-0435-430c-abc4-8e5e6c566164' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,\n",
+       "       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,\n",
+       "       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,\n",
+       "       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,\n",
+       "       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,\n",
+       "       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,\n",
+       "       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,\n",
+       "       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,\n",
+       "       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,\n",
+       "       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,\n",
+       "       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,\n",
+       "       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,\n",
+       "       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,\n",
+       "       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,\n",
+       "       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,\n",
+       "        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,\n",
+       "         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,\n",
+       "         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,\n",
+       "        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,\n",
+       "        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,\n",
+       "        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,\n",
+       "        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,\n",
+       "        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,\n",
+       "        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,\n",
+       "        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,\n",
+       "        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,\n",
+       "        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,\n",
+       "        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,\n",
+       "        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,\n",
+       "        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,\n",
+       "        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,\n",
+       "        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -178.8 ... 177.5 178.8</div><input id='attrs-ea99162c-8811-425b-a90c-d78a4bffd88c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea99162c-8811-425b-a90c-d78a4bffd88c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c2fbfba-5abd-4911-9045-9aafd61eff2f' class='xr-var-data-in' type='checkbox'><label for='data-3c2fbfba-5abd-4911-9045-9aafd61eff2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array([-180.  , -178.75, -177.5 , ...,  176.25,  177.5 ,  178.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>member_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U8</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-c2d7c383-1a01-4d7b-96e8-a97422c34b6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2d7c383-1a01-4d7b-96e8-a97422c34b6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e75f2550-e7ff-4210-aec9-51ae4820a056' class='xr-var-data-in' type='checkbox'><label for='data-e75f2550-e7ff-4210-aec9-51ae4820a056' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;r1i1p1f1&#x27;, dtype=&#x27;&lt;U8&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dcpp_init_year</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-28bb3e63-23a1-4149-9f8a-79036f11e98f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28bb3e63-23a1-4149-9f8a-79036f11e98f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3995dd75-f4e2-4f71-824a-49536ec56e85' class='xr-var-data-in' type='checkbox'><label for='data-3995dd75-f4e2-4f71-824a-49536ec56e85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-992.6</div><input id='attrs-2a7e9fd3-5b1c-40d6-b663-47f0c9c44a90' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a7e9fd3-5b1c-40d6-b663-47f0c9c44a90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-495cfdf8-4eb1-41c5-873e-61215c1603d6' class='xr-var-data-in' type='checkbox'><label for='data-495cfdf8-4eb1-41c5-873e-61215c1603d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array(-992.55609512)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f93ad7ac-adbf-4fdb-9aba-ca06533c979f' class='xr-section-summary-in' type='checkbox'  ><label for='section-f93ad7ac-adbf-4fdb-9aba-ca06533c979f' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9e951233-7748-475b-9b83-0d60894bae96' class='xr-index-data-in' type='checkbox'/><label for='index-9e951233-7748-475b-9b83-0d60894bae96' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,\n",
+       "       -87.17277486910994,  -86.2303664921466, -85.28795811518324,\n",
+       "        -84.3455497382199, -83.40314136125654, -82.46073298429319,\n",
+       "       -81.51832460732984,\n",
+       "       ...\n",
+       "        81.51832460732984,   82.4607329842932,  83.40314136125653,\n",
+       "        84.34554973821989,  85.28795811518324,   86.2303664921466,\n",
+       "        87.17277486910996,  88.11518324607329,  89.05759162303664,\n",
+       "                     90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-028e3a8a-67f5-4e80-abab-f3212be3396f' class='xr-index-data-in' type='checkbox'/><label for='index-028e3a8a-67f5-4e80-abab-f3212be3396f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -180.0, -178.75,  -177.5, -176.25,  -175.0, -173.75,  -172.5, -171.25,\n",
+       "        -170.0, -168.75,\n",
+       "       ...\n",
+       "         167.5,  168.75,   170.0,  171.25,   172.5,  173.75,   175.0,  176.25,\n",
+       "         177.5,  178.75],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-08ca749c-6994-41a8-8efc-6a6ff4bf6cc3' class='xr-section-summary-in' type='checkbox'  ><label for='section-08ca749c-6994-41a8-8efc-6a6ff4bf6cc3' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'mmrso4' (lat: 192, lon: 288)> Size: 221kB\n",
+       "dask.array<getitem, shape=(192, 288), dtype=float32, chunksize=(192, 288), chunktype=numpy.ndarray>\n",
+       "Coordinates:\n",
+       "  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0\n",
+       "  * lon             (lon) float64 2kB -180.0 -178.8 -177.5 ... 176.2 177.5 178.8\n",
+       "    member_id       <U8 32B 'r1i1p1f1'\n",
+       "    dcpp_init_year  float64 8B nan\n",
+       "    lev             float64 8B -992.6\n",
+       "Attributes: (12/19)\n",
+       "    cell_measures:  area: areacella\n",
+       "    cell_methods:   area: time: mean\n",
+       "    comment:        Dry mass of sulfate (SO4) in aerosol particles as a fract...\n",
+       "    description:    Dry mass of sulfate (SO4) in aerosol particles as a fract...\n",
+       "    frequency:      mon\n",
+       "    id:             mmrso4\n",
+       "    ...             ...\n",
+       "    time_label:     time-mean\n",
+       "    time_title:     Temporal mean\n",
+       "    title:          Aerosol Sulfate Mass Mixing Ratio\n",
+       "    type:           real\n",
+       "    units:          kg kg-1\n",
+       "    variable_id:    mmrso4"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "da_plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib.colors import LogNorm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 960x720 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "f,ax = plt.subplots(1,1,dpi=150,subplot_kw={'projection':ccrs.Robinson()})\n",
+    "\n",
+    "\n",
+    "da_plt.plot.pcolormesh(\n",
+    "    cmap = plt.get_cmap('Reds'),\n",
+    "    ax=ax,\n",
+    "    norm = LogNorm(),\n",
+    "    cbar_kwargs={\n",
+    "        #'label':'Wind Speed [m/s]', \n",
+    "        'orientation':'horizontal',\n",
+    "        'shrink':.8\n",
+    "    },\n",
+    "    transform=ccrs.PlateCarree(), \n",
+    "    #x='lon',y='lat',\n",
+    "    levels = 6\n",
+    ")\n",
+    "ax.set_title('ilev:-1; Mean over Time')\n",
+    "ax.coastlines()\n",
+    "\n",
+    "gl = ax.gridlines(draw_labels=True)\n",
+    "#gl.xlabels_top = False\n",
+    "#gl.ylabels_right = False\n",
+    "#gl.top_labels(False)\n",
+    "ax.add_feature(cy.feature.BORDERS);\n",
+    "f.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# 6. Global average: weighted means!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
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+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;T_C&#x27; ()&gt; Size: 4B\n",
+       "array(5.447856, dtype=float32)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'T_C'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-835850cc-d6ee-437b-931c-f62f71bce594' class='xr-array-in' type='checkbox' checked><label for='section-835850cc-d6ee-437b-931c-f62f71bce594' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>5.448</span></div><div class='xr-array-data'><pre>array(5.447856, dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-cdb24954-63dd-49e8-a5cd-80d447d9fd3d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cdb24954-63dd-49e8-a5cd-80d447d9fd3d' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-30fe78df-f740-4925-ae61-dc2bb459e1c5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-30fe78df-f740-4925-ae61-dc2bb459e1c5' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-501b8884-65c3-482b-a16e-5a3acc300f35' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-501b8884-65c3-482b-a16e-5a3acc300f35' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'T_C' ()> Size: 4B\n",
+       "array(5.447856, dtype=float32)"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss['T_C'].mean().compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
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+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
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+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
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+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
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+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;T_C&#x27; ()&gt; Size: 4B\n",
+       "array(14.715081, dtype=float32)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'T_C'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3d93790d-7462-4a42-a457-e0641a890e02' class='xr-array-in' type='checkbox' checked><label for='section-3d93790d-7462-4a42-a457-e0641a890e02' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>14.72</span></div><div class='xr-array-data'><pre>array(14.715081, dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-0d93f88c-a0e7-4767-8b76-d17f29223a07' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0d93f88c-a0e7-4767-8b76-d17f29223a07' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-113699b5-8179-4ae6-81ba-e4773bebff54' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-113699b5-8179-4ae6-81ba-e4773bebff54' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-ea8ce804-d144-40a6-9ba9-c2245f800c0a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ea8ce804-d144-40a6-9ba9-c2245f800c0a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'T_C' ()> Size: 4B\n",
+       "array(14.715081, dtype=float32)"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dss['T_C'].weighted(dss['areacella']).mean().compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f38041ade50>"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dss['areacella'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# 7. Convert to pandas & do some random fun stuff: "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Maybe we e.g. want to compare with a station, or just use some of the considerable functionalities available from pandas. It's easy to convert back and forth between xarray and pandas:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "<span style=\"color:green;font-weight:700;font-size:20px\">\n",
+    "A lot of these functions also exist in xarray!\n",
+    "</span>\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Pick out station: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "lat_kristineberg = 58.24\n",
+    "lon_kristineberg = 11.44\n",
+    "# pick out surface\n",
+    "ds_surf =dss.isel(lev=-1)\n",
+    "ds_kristineberg = ds_surf.sel(lat=lat_kristineberg, lon = lon_kristineberg, method ='nearest')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 11kB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, nbnd: 2, time: 240)\n",
+       "Coordinates:\n",
+       "    lat             float64 8B 57.96\n",
+       "    lon             float64 8B 11.25\n",
+       "    lon_bnds        (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    a_bnds          (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;\n",
+       "    b_bnds          (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;\n",
+       "    lev             float64 8B -992.6\n",
+       "    lev_bnds        (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;\n",
+       "  * time            (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year) float32 4B dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;\n",
+       "    a               float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
+       "    b               float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;\n",
+       "    mmrso4          (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 10), meta=np.ndarray&gt;\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time) float32 960B dask.array&lt;chunksize=(10,), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;\n",
+       "    T_C             (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8a40df58-f854-4c4e-b647-2da8142b847d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8a40df58-f854-4c4e-b647-2da8142b847d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-898d1791-ace3-45e4-8ab5-7f9355e41f31' class='xr-section-summary-in' type='checkbox'  checked><label for='section-898d1791-ace3-45e4-8ab5-7f9355e41f31' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>57.96</div><input id='attrs-24f8af7e-84a1-4c04-89bc-51500e66b9e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24f8af7e-84a1-4c04-89bc-51500e66b9e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd5468a8-d299-458a-8a40-4ab4696eb5c6' class='xr-var-data-in' type='checkbox'><label for='data-cd5468a8-d299-458a-8a40-4ab4696eb5c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array(57.95811518)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>11.25</div><input id='attrs-61b747cf-4a4a-482a-9f42-9d20c0fcdb4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61b747cf-4a4a-482a-9f42-9d20c0fcdb4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86630b16-1a7b-47c6-84bc-90e6340af325' class='xr-var-data-in' type='checkbox'><label for='data-86630b16-1a7b-47c6-84bc-90e6340af325' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array(11.25)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-896cc5a6-5c6d-4e49-80d3-46af98a719e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-896cc5a6-5c6d-4e49-80d3-46af98a719e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a86f7966-82f1-4618-bac2-79345533ffa7' class='xr-var-data-in' type='checkbox'><label for='data-a86f7966-82f1-4618-bac2-79345533ffa7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 16 B </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2,) </td>\n",
+       "                        <td> (2,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 15 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,30.000000)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-b3cb8ae8-7a03-4c45-82b9-2253b9a52e54' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b3cb8ae8-7a03-4c45-82b9-2253b9a52e54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a88556ee-4bcd-42d8-9337-20cff99f0a7d' class='xr-var-data-in' type='checkbox'><label for='data-a88556ee-4bcd-42d8-9337-20cff99f0a7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-32dbf347-6cde-4bd8-9bdc-82bd8714b951' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-32dbf347-6cde-4bd8-9bdc-82bd8714b951' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b315b82-7b17-4cd9-a859-2997e0d9567b' class='xr-var-data-in' type='checkbox'><label for='data-3b315b82-7b17-4cd9-a859-2997e0d9567b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-6cf0d2d4-b3aa-46fa-ade4-eb8eab8cbe6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6cf0d2d4-b3aa-46fa-ade4-eb8eab8cbe6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-657915ef-76d1-473f-b8dd-0a43e046c382' class='xr-var-data-in' type='checkbox'><label for='data-657915ef-76d1-473f-b8dd-0a43e046c382' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 16 B </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2,) </td>\n",
+       "                        <td> (2,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,30.000000)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-d212a80a-99ad-48cf-a82a-8676aee0cef8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d212a80a-99ad-48cf-a82a-8676aee0cef8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-422bd8d8-2e18-4395-901d-26eefa1c5e44' class='xr-var-data-in' type='checkbox'><label for='data-422bd8d8-2e18-4395-901d-26eefa1c5e44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 16 B </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2,) </td>\n",
+       "                        <td> (2,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,30.000000)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-992.6</div><input id='attrs-96afb2ae-2d05-4f52-bee8-3726ddd58b87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96afb2ae-2d05-4f52-bee8-3726ddd58b87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adfe0c16-8929-4afa-81c0-74991782201d' class='xr-var-data-in' type='checkbox'><label for='data-adfe0c16-8929-4afa-81c0-74991782201d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array(-992.55609512)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-5b5653c2-0b57-458c-9f2f-5b3b38c7d84a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b5653c2-0b57-458c-9f2f-5b3b38c7d84a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c6ec933-f55d-40c2-be67-a847ccb5496a' class='xr-var-data-in' type='checkbox'><label for='data-4c6ec933-f55d-40c2-be67-a847ccb5496a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 16 B </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2,) </td>\n",
+       "                        <td> (2,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,30.000000)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-15T12:00:00 ... 2009-12-...</div><input id='attrs-5db3fee9-eab1-4e9c-8026-72e8a744435e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5db3fee9-eab1-4e9c-8026-72e8a744435e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-254458b7-94bf-4fe4-b3d4-c03e4337374f' class='xr-var-data-in' type='checkbox'><label for='data-254458b7-94bf-4fe4-b3d4-c03e4337374f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,\n",
+       "       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-19eaeb15-7cfc-4a72-9160-5f1c5839038d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-19eaeb15-7cfc-4a72-9160-5f1c5839038d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2be5e9e-a6bf-413e-8d97-d8428b755e44' class='xr-var-data-in' type='checkbox'><label for='data-c2be5e9e-a6bf-413e-8d97-d8428b755e44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                        <td> 3.75 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                        <td> (240, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 7 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">240</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2a7b08af-9e78-451c-bc8c-993d99178271' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2a7b08af-9e78-451c-bc8c-993d99178271' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;</div><input id='attrs-3a9bd0ab-afa5-451b-a237-4969aa2b9465' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a9bd0ab-afa5-451b-a237-4969aa2b9465' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2ce18ef-ab5b-4b7f-9e62-7bcb4009f0a4' class='xr-var-data-in' type='checkbox'><label for='data-b2ce18ef-ab5b-4b7f-9e62-7bcb4009f0a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 4 B </td>\n",
+       "                        <td> 4 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1, 1) </td>\n",
+       "                        <td> (1, 1) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-cf973191-b03d-48f1-ac29-f7fffd0cd2a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf973191-b03d-48f1-ac29-f7fffd0cd2a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd94f242-87b0-402d-9935-8264ed4cc7a8' class='xr-var-data-in' type='checkbox'><label for='data-cd94f242-87b0-402d-9935-8264ed4cc7a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
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+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8 B </td>\n",
+       "                        <td> 8 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> () </td>\n",
+       "                        <td> () </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        \n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-a572d68b-d847-47a3-8a5e-e54f6a773064' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a572d68b-d847-47a3-8a5e-e54f6a773064' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79ec675e-ea47-4cf6-bb98-f93394e7f05c' class='xr-var-data-in' type='checkbox'><label for='data-79ec675e-ea47-4cf6-bb98-f93394e7f05c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 8 B </td>\n",
+       "                        <td> 8 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> () </td>\n",
+       "                        <td> () </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        \n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10), meta=np.ndarray&gt;</div><input id='attrs-18fb0cbd-4181-4e9e-b0fd-eda83b99c5e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18fb0cbd-4181-4e9e-b0fd-eda83b99c5e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcd2584b-fd60-49d3-9e68-a69dd7b778a5' class='xr-var-data-in' type='checkbox'><label for='data-dcd2584b-fd60-49d3-9e68-a69dd7b778a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 0.94 kiB </td>\n",
+       "                        <td> 40 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <td> (1, 1, 10) </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 24 chunks in 7 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c4fa314d-cbf7-4f02-9ea8-4402b8fae7cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4fa314d-cbf7-4f02-9ea8-4402b8fae7cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7478526-9b21-438d-9f4b-ae0b04c460a2' class='xr-var-data-in' type='checkbox'><label for='data-c7478526-9b21-438d-9f4b-ae0b04c460a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10,), meta=np.ndarray&gt;</div><input id='attrs-2c6f63ed-e4a9-4266-90a4-9be28a40ae58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c6f63ed-e4a9-4266-90a4-9be28a40ae58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22e5387e-fd16-43fb-9894-f3a454114b7f' class='xr-var-data-in' type='checkbox'><label for='data-22e5387e-fd16-43fb-9894-f3a454114b7f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
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+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 0.94 kiB </td>\n",
+       "                        <td> 40 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (240,) </td>\n",
+       "                        <td> (10,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 24 chunks in 5 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-c3e70ba2-ce95-4c4c-b869-89b946252ab5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3e70ba2-ce95-4c4c-b869-89b946252ab5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89b56670-f8ac-4792-a7f4-2bbaabc8504d' class='xr-var-data-in' type='checkbox'><label for='data-89b56670-f8ac-4792-a7f4-2bbaabc8504d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 0.94 kiB </td>\n",
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+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 2 chunks in 6 graph layers </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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+       "        </td>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-4f8450ed-612a-4133-8019-d767fbcfa48b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f8450ed-612a-4133-8019-d767fbcfa48b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9677c7b7-90a3-44bc-b999-8960083c0edb' class='xr-var-data-in' type='checkbox'><label for='data-9677c7b7-90a3-44bc-b999-8960083c0edb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 0.94 kiB </td>\n",
+       "                        <td> 480 B </td>\n",
+       "                    </tr>\n",
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+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
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+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 2 chunks in 6 graph layers </td>\n",
+       "                    </tr>\n",
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+       "                        <th> Data type </th>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T_C</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-def62cb6-9e4f-4d94-974c-816aa464f7d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-def62cb6-9e4f-4d94-974c-816aa464f7d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-377a82fd-8802-4343-9dbd-6d9b3ba3aee9' class='xr-var-data-in' type='checkbox'><label for='data-377a82fd-8802-4343-9dbd-6d9b3ba3aee9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\\circ$C</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
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+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6de52f87-c974-42bf-ad1c-c6bd3c686407' class='xr-section-summary-in' type='checkbox'  ><label for='section-6de52f87-c974-42bf-ad1c-c6bd3c686407' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2c3e41f6-80d2-4aa6-9f19-6ea1dd0818ca' class='xr-index-data-in' type='checkbox'/><label for='index-2c3e41f6-80d2-4aa6-9f19-6ea1dd0818ca' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-66fe8f5f-1582-4d47-9e04-daeaa7c1c7dd' class='xr-index-data-in' type='checkbox'/><label for='index-66fe8f5f-1582-4d47-9e04-daeaa7c1c7dd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-57278806-d180-400c-bb42-e8629745a701' class='xr-index-data-in' type='checkbox'/><label for='index-57278806-d180-400c-bb42-e8629745a701' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-15 12:00:00&#x27;, &#x27;1990-02-14 00:00:00&#x27;,\n",
+       "               &#x27;1990-03-15 12:00:00&#x27;, &#x27;1990-04-15 00:00:00&#x27;,\n",
+       "               &#x27;1990-05-15 12:00:00&#x27;, &#x27;1990-06-15 00:00:00&#x27;,\n",
+       "               &#x27;1990-07-15 12:00:00&#x27;, &#x27;1990-08-15 12:00:00&#x27;,\n",
+       "               &#x27;1990-09-15 00:00:00&#x27;, &#x27;1990-10-15 12:00:00&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2009-03-15 12:00:00&#x27;, &#x27;2009-04-15 00:00:00&#x27;,\n",
+       "               &#x27;2009-05-15 12:00:00&#x27;, &#x27;2009-06-15 00:00:00&#x27;,\n",
+       "               &#x27;2009-07-15 12:00:00&#x27;, &#x27;2009-08-15 12:00:00&#x27;,\n",
+       "               &#x27;2009-09-15 00:00:00&#x27;, &#x27;2009-10-15 12:00:00&#x27;,\n",
+       "               &#x27;2009-11-15 00:00:00&#x27;, &#x27;2009-12-15 12:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-82c14247-cd87-4d1e-9e61-b2247c62979e' class='xr-section-summary-in' type='checkbox'  ><label for='section-82c14247-cd87-4d1e-9e61-b2247c62979e' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 11kB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, nbnd: 2, time: 240)\n",
+       "Coordinates:\n",
+       "    lat             float64 8B 57.96\n",
+       "    lon             float64 8B 11.25\n",
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+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
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+       "    a_bnds          (nbnd) float64 16B dask.array<chunksize=(2,), meta=np.ndarray>\n",
+       "    b_bnds          (nbnd) float64 16B dask.array<chunksize=(2,), meta=np.ndarray>\n",
+       "    lev             float64 8B -992.6\n",
+       "    lev_bnds        (nbnd) float64 16B dask.array<chunksize=(2,), meta=np.ndarray>\n",
+       "  * time            (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12...\n",
+       "    time_bnds       (time, nbnd) object 4kB dask.array<chunksize=(240, 2), meta=np.ndarray>\n",
+       "Dimensions without coordinates: nbnd\n",
+       "Data variables:\n",
+       "    areacella       (member_id, dcpp_init_year) float32 4B dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
+       "    a               float64 8B dask.array<chunksize=(), meta=np.ndarray>\n",
+       "    b               float64 8B dask.array<chunksize=(), meta=np.ndarray>\n",
+       "    mmrso4          (member_id, dcpp_init_year, time) float32 960B dask.array<chunksize=(1, 1, 10), meta=np.ndarray>\n",
+       "    p0              float32 4B ...\n",
+       "    ps              (time) float32 960B dask.array<chunksize=(10,), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, time) float32 960B dask.array<chunksize=(1, 1, 120), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time) float32 960B dask.array<chunksize=(1, 1, 120), meta=np.ndarray>\n",
+       "    T_C             (member_id, dcpp_init_year, time) float32 960B dask.array<chunksize=(1, 1, 120), meta=np.ndarray>\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_kristineberg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "vl = ['mmrso4','hurs','tas','T_C']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
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+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 6kB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, time: 240)\n",
+       "Coordinates:\n",
+       "    lat             float64 8B 57.96\n",
+       "    lon             float64 8B 11.25\n",
+       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    lev             float64 8B -992.6\n",
+       "  * time            (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12...\n",
+       "Data variables:\n",
+       "    mmrso4          (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 10), meta=np.ndarray&gt;\n",
+       "    hurs            (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;\n",
+       "    tas             (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;\n",
+       "    T_C             (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4391e9e8-70a4-4160-879d-af13d6564b81' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4391e9e8-70a4-4160-879d-af13d6564b81' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7940780e-531f-4e9f-8898-e82ee01c54be' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7940780e-531f-4e9f-8898-e82ee01c54be' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>57.96</div><input id='attrs-bcc14ebb-82e4-4dbd-a2a0-8d46abb9fc45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bcc14ebb-82e4-4dbd-a2a0-8d46abb9fc45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da82df85-6d45-47b4-9ec4-efdc3bb9848b' class='xr-var-data-in' type='checkbox'><label for='data-da82df85-6d45-47b4-9ec4-efdc3bb9848b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array(57.95811518)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>11.25</div><input id='attrs-9f87290c-e2d2-41a9-b7fe-58d451ccc4c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f87290c-e2d2-41a9-b7fe-58d451ccc4c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36ce72b3-70ed-44d5-90aa-abd0c9a5c094' class='xr-var-data-in' type='checkbox'><label for='data-36ce72b3-70ed-44d5-90aa-abd0c9a5c094' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array(11.25)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-330e0ec3-e5d6-4b04-a403-23be9ef2b866' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-330e0ec3-e5d6-4b04-a403-23be9ef2b866' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cc0c25a-9be5-49f8-bd76-b88fb9d02ae3' class='xr-var-data-in' type='checkbox'><label for='data-9cc0c25a-9be5-49f8-bd76-b88fb9d02ae3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-d69bc926-2ba5-4d2d-ab45-2743a5dee307' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d69bc926-2ba5-4d2d-ab45-2743a5dee307' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-079f58d4-55e7-4907-a0a5-96fefd0a8c38' class='xr-var-data-in' type='checkbox'><label for='data-079f58d4-55e7-4907-a0a5-96fefd0a8c38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-992.6</div><input id='attrs-5669a45f-028f-4efb-836e-c09aa47926ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5669a45f-028f-4efb-836e-c09aa47926ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-289739db-014d-4ca0-b1eb-aedef19ac01d' class='xr-var-data-in' type='checkbox'><label for='data-289739db-014d-4ca0-b1eb-aedef19ac01d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array(-992.55609512)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-15T12:00:00 ... 2009-12-...</div><input id='attrs-eaf7b075-577c-4316-b8a3-12df225c4180' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-eaf7b075-577c-4316-b8a3-12df225c4180' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e5a0022-a8cd-4096-a17b-f7b40c8ba2fb' class='xr-var-data-in' type='checkbox'><label for='data-4e5a0022-a8cd-4096-a17b-f7b40c8ba2fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,\n",
+       "       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-618ebcd8-56a9-4104-bae4-e0b06debf413' class='xr-section-summary-in' type='checkbox'  checked><label for='section-618ebcd8-56a9-4104-bae4-e0b06debf413' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10), meta=np.ndarray&gt;</div><input id='attrs-f889b26a-26c5-493b-aea7-a4656bf99ed1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f889b26a-26c5-493b-aea7-a4656bf99ed1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e592787b-78f0-4fc3-b1fa-65fa8415b3d2' class='xr-var-data-in' type='checkbox'><label for='data-e592787b-78f0-4fc3-b1fa-65fa8415b3d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-58b8f75f-b5e6-41ae-ada6-03ab64fe6cdc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58b8f75f-b5e6-41ae-ada6-03ab64fe6cdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a375f94-a2b3-4e65-b753-a4f280ac9c29' class='xr-var-data-in' type='checkbox'><label for='data-1a375f94-a2b3-4e65-b753-a4f280ac9c29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>\n",
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+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
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+       "                        <td colspan=\"2\"> 2 chunks in 6 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
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+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-4bbc3ab0-78bc-438f-b621-f4739c03cf4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bbc3ab0-78bc-438f-b621-f4739c03cf4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf1e51e6-b736-41e0-8af0-f0431359bdae' class='xr-var-data-in' type='checkbox'><label for='data-bf1e51e6-b736-41e0-8af0-f0431359bdae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
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+       "                    <tr>\n",
+       "                        <td> </td>\n",
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+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
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+       "                        <td> 0.94 kiB </td>\n",
+       "                        <td> 480 B </td>\n",
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+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 2 chunks in 6 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
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+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c682c4e6-58bc-4eee-8a2c-865fe7fb7076' class='xr-section-summary-in' type='checkbox'  ><label for='section-c682c4e6-58bc-4eee-8a2c-865fe7fb7076' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dc39be7a-d750-4eb9-a280-02f5551f6353' class='xr-index-data-in' type='checkbox'/><label for='index-dc39be7a-d750-4eb9-a280-02f5551f6353' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-95e6e4f4-091f-4067-8e85-550413165a51' class='xr-index-data-in' type='checkbox'/><label for='index-95e6e4f4-091f-4067-8e85-550413165a51' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-18af2285-7351-4322-874d-e0819ae152f6' class='xr-index-data-in' type='checkbox'/><label for='index-18af2285-7351-4322-874d-e0819ae152f6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-15 12:00:00&#x27;, &#x27;1990-02-14 00:00:00&#x27;,\n",
+       "               &#x27;1990-03-15 12:00:00&#x27;, &#x27;1990-04-15 00:00:00&#x27;,\n",
+       "               &#x27;1990-05-15 12:00:00&#x27;, &#x27;1990-06-15 00:00:00&#x27;,\n",
+       "               &#x27;1990-07-15 12:00:00&#x27;, &#x27;1990-08-15 12:00:00&#x27;,\n",
+       "               &#x27;1990-09-15 00:00:00&#x27;, &#x27;1990-10-15 12:00:00&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2009-03-15 12:00:00&#x27;, &#x27;2009-04-15 00:00:00&#x27;,\n",
+       "               &#x27;2009-05-15 12:00:00&#x27;, &#x27;2009-06-15 00:00:00&#x27;,\n",
+       "               &#x27;2009-07-15 12:00:00&#x27;, &#x27;2009-08-15 12:00:00&#x27;,\n",
+       "               &#x27;2009-09-15 00:00:00&#x27;, &#x27;2009-10-15 12:00:00&#x27;,\n",
+       "               &#x27;2009-11-15 00:00:00&#x27;, &#x27;2009-12-15 12:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b3b9c45-eafa-4274-a759-367fedd71f9f' class='xr-section-summary-in' type='checkbox'  ><label for='section-6b3b9c45-eafa-4274-a759-367fedd71f9f' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
+       "</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 6kB\n",
+       "Dimensions:         (member_id: 1, dcpp_init_year: 1, time: 240)\n",
+       "Coordinates:\n",
+       "    lat             float64 8B 57.96\n",
+       "    lon             float64 8B 11.25\n",
+       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
+       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
+       "    lev             float64 8B -992.6\n",
+       "  * time            (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12...\n",
+       "Data variables:\n",
+       "    mmrso4          (member_id, dcpp_init_year, time) float32 960B dask.array<chunksize=(1, 1, 10), meta=np.ndarray>\n",
+       "    hurs            (member_id, dcpp_init_year, time) float32 960B dask.array<chunksize=(1, 1, 120), meta=np.ndarray>\n",
+       "    tas             (member_id, dcpp_init_year, time) float32 960B dask.array<chunksize=(1, 1, 120), meta=np.ndarray>\n",
+       "    T_C             (member_id, dcpp_init_year, time) float32 960B dask.array<chunksize=(1, 1, 120), meta=np.ndarray>\n",
+       "Attributes: (12/60)\n",
+       "    Conventions:                      CF-1.7 CMIP-6.2\n",
+       "    activity_id:                      CMIP\n",
+       "    branch_method:                    standard\n",
+       "    branch_time_in_child:             674885.0\n",
+       "    branch_time_in_parent:            219000.0\n",
+       "    case_id:                          15\n",
+       "    ...                               ...\n",
+       "    intake_esm_attrs:variable_id:     areacella\n",
+       "    intake_esm_attrs:grid_label:      gn\n",
+       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...\n",
+       "    intake_esm_attrs:version:         20190308\n",
+       "    intake_esm_attrs:_data_format_:   zarr\n",
+       "    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_kristineberg[vl]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Resample:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "df_kristineberg = ds_kristineberg[vl].squeeze().to_dataframe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<style scoped>\n",
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+       "      <th></th>\n",
+       "      <th>mmrso4</th>\n",
+       "      <th>hurs</th>\n",
+       "      <th>tas</th>\n",
+       "      <th>T_C</th>\n",
+       "      <th>lat</th>\n",
+       "      <th>lon</th>\n",
+       "      <th>member_id</th>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <th>lev</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>time</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1990-01-15 12:00:00</th>\n",
+       "      <td>9.319389e-10</td>\n",
+       "      <td>85.651199</td>\n",
+       "      <td>277.036011</td>\n",
+       "      <td>3.886017</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-02-14 00:00:00</th>\n",
+       "      <td>9.139207e-10</td>\n",
+       "      <td>79.779701</td>\n",
+       "      <td>273.601807</td>\n",
+       "      <td>0.451813</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-03-15 12:00:00</th>\n",
+       "      <td>1.282672e-09</td>\n",
+       "      <td>82.473785</td>\n",
+       "      <td>277.405701</td>\n",
+       "      <td>4.255707</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-04-15 00:00:00</th>\n",
+       "      <td>7.225737e-10</td>\n",
+       "      <td>79.588730</td>\n",
+       "      <td>280.137329</td>\n",
+       "      <td>6.987335</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-05-15 12:00:00</th>\n",
+       "      <td>2.263646e-09</td>\n",
+       "      <td>80.421875</td>\n",
+       "      <td>283.043152</td>\n",
+       "      <td>9.893158</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2009-08-15 12:00:00</th>\n",
+       "      <td>6.469142e-10</td>\n",
+       "      <td>82.338539</td>\n",
+       "      <td>290.292358</td>\n",
+       "      <td>17.142365</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2009-09-15 00:00:00</th>\n",
+       "      <td>6.174767e-10</td>\n",
+       "      <td>75.105225</td>\n",
+       "      <td>288.502136</td>\n",
+       "      <td>15.352142</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2009-10-15 12:00:00</th>\n",
+       "      <td>5.226203e-10</td>\n",
+       "      <td>81.029533</td>\n",
+       "      <td>284.518219</td>\n",
+       "      <td>11.368225</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2009-11-15 00:00:00</th>\n",
+       "      <td>2.411485e-10</td>\n",
+       "      <td>83.641380</td>\n",
+       "      <td>278.707977</td>\n",
+       "      <td>5.557983</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2009-12-15 12:00:00</th>\n",
+       "      <td>4.485378e-10</td>\n",
+       "      <td>89.487213</td>\n",
+       "      <td>277.537415</td>\n",
+       "      <td>4.387421</td>\n",
+       "      <td>57.958115</td>\n",
+       "      <td>11.25</td>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>240 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           mmrso4       hurs         tas        T_C  \\\n",
+       "time                                                                  \n",
+       "1990-01-15 12:00:00  9.319389e-10  85.651199  277.036011   3.886017   \n",
+       "1990-02-14 00:00:00  9.139207e-10  79.779701  273.601807   0.451813   \n",
+       "1990-03-15 12:00:00  1.282672e-09  82.473785  277.405701   4.255707   \n",
+       "1990-04-15 00:00:00  7.225737e-10  79.588730  280.137329   6.987335   \n",
+       "1990-05-15 12:00:00  2.263646e-09  80.421875  283.043152   9.893158   \n",
+       "...                           ...        ...         ...        ...   \n",
+       "2009-08-15 12:00:00  6.469142e-10  82.338539  290.292358  17.142365   \n",
+       "2009-09-15 00:00:00  6.174767e-10  75.105225  288.502136  15.352142   \n",
+       "2009-10-15 12:00:00  5.226203e-10  81.029533  284.518219  11.368225   \n",
+       "2009-11-15 00:00:00  2.411485e-10  83.641380  278.707977   5.557983   \n",
+       "2009-12-15 12:00:00  4.485378e-10  89.487213  277.537415   4.387421   \n",
+       "\n",
+       "                           lat    lon member_id  dcpp_init_year         lev  \n",
+       "time                                                                         \n",
+       "1990-01-15 12:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "1990-02-14 00:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "1990-03-15 12:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "1990-04-15 00:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "1990-05-15 12:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "...                        ...    ...       ...             ...         ...  \n",
+       "2009-08-15 12:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "2009-09-15 00:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "2009-10-15 12:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "2009-11-15 00:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "2009-12-15 12:00:00  57.958115  11.25  r1i1p1f1             NaN -992.556095  \n",
+       "\n",
+       "[240 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_kristineberg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "df_yearly = df_kristineberg.resample('YE').mean(numeric_only=True)#.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='time'>"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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3Zom627aHPVmUgQkLEXXI5pOluFDdiNAAH9w5vJfc4XRZ/9gQZMSHwGwV8d3Ri3KHQx1w4qIBJYYmBPiqMS4lwu3Xn55h78lSWNWI/XnsySIXJixE1CGOUuYHrusNf1+1zNF0z+U9WUj5HFVpE/tGws/H/a899mRRBiYsRHRNx4v02J9bBY1KwEPj+sgdTrfNHhYPjUrAzxf0OFNaK3c4dA2OhEXq7rbtcUwLrT/GnixyYcJCRNf0aXMb/hmD49zSsEtqEUFa3JBu75S6mhsiKlqxvhHHiwwQBOCm/tJ2t20Pe7LIjwkLEbWrzNCE73+2r/XwxFLmtjh2cP7m8AVYFb6QUhRFrMzMw8rMvB63rYBjse3wxFBEBmlli4M9WeTHhIXc4vf/PIqb/rwd+gaz3KFQJ636KR9mq4iRfcIwLDFU7nBc5qYB0dD5+6DUYMSesxVyh9OuH3PK8PK3J/Dytyfw1vrsHpW0OLvbylAddCX2ZJEXExaSXJPZirVHinC+vB5bc0rlDoc6oclsxap9BQDspczeRKtR4/ahyu/JYrLY8Md12c6f/74rF+9vPSNjRO7TYLJgz7lKAO7rbtse9mSRFxMWktypklrnkPuO0+UyR0Od8d2Ri6iqNyFe54fpGfJ/YLiaoyfLxhMlqG1S5ujfZ3vzkFtRj8ggLZ6dng4AWLrlDP6x67zMkUlv15kKmCw29A4PQN/oILnDAcCeLHJiwkKSO3Hx0s64u85U8I/cQ4ii6Cxlfnh8EjRq73u7GJqgQ2pUIJrMNqw/Vix3OFcprzXig+bRlOemp+PJG9OwcFo/AMAf12Xji+bRL28lV3fb9rAni3y87x2IFOfERb3zv6vqTTh+2c+kXHvPVSKnpBYBvmrcN7q33OFIQhAE5yiLEquF/rzpFGqNFgzupXN+s3/yxjQ8PjkVAPCHtcew9rDy4nYFq03Ejzn2Bbc3K2A6yIE9WeTDhIUk5xhhCWhuNrbjFKeFPIGjlPnukQnQBfjIHI107hzeC4IA7M9V1kLK40V6fH3AXo3y6qyBUKnsIwyCIOD5W9Ixd1wfiCLw+38dxcYT3ldme6SwBpX1JgT7aTA6OVzucFpgTxZ5MGEhSVltInJK7AnLA9fZv6XvPMOERelyK+qxtfnb7SPjk+QNRmJxOuUtpBRFEa9/fxKiCNw+NB6jklp+YAuCgNdmZWDOiARYbSKe/uIwdnnZ35WjOuiG9Gj4KGw6kj1Z5KGsVwF5nfPldWgy2xDgq8bDzR98hwpqoG9U5gJHslvRvHblpv7RSIlSxmJHKc0Zae/JsuZQkSJKhtcdK8b+vCr4+ajwwq39Wz1GpRKwZM5g3DooFiarDb/+/ACyvGhNhaO77dQB8jWLawt7ssiDCQtJyjEdNCAuBInhAUiNCoTVJmKvwvte9GT6RjP+1Tw3722lzG2ZnhGLQF81CqoakJVXLWssTWYrFq/PAQA8PjkV8aFtdxbWqFV4/77huCE9Ck1mG+Ytz8KxC56/RqygsgGnS+ugVgm4oZ/yEhaAPVnkwISFJOVYcJsRHwIAmNz85sPyZuX6OqsADSYr0mOCcX2a+3fGlUOArwYzBtsXUq6WeSHlxzvPo6imEfE6P/xmUuo1j/fVqLDslyMxJjkctUYLHvp0H06VePb+SI7RldFJYYpdP8WeLO7HhIUk5RhhcSYs6VEAgJ2nyxUx9E4tWaw2fLY3HwAwb0KSYkpJ3cFRLbTuWDGazFZZYijWN+Kj7ecAAC/MGNDhXbH9fNT45JHRGJoYipoGM375yT7kVtRLGaqkHA0mldAsrj3syeJeTFhIMqIoXpaw6AAAY5LDodWocFHfhLNldXKGR63YdLIURTWNCA/0xexhveQOx62uSwpHQpg/6owW2apulvyQg0azFaP6hGFWc+lsRwVpNfjs0dHoHxuM8lojfvmPfSiqaZQoUukYmszYd96+FkfpCQt7srgXExaSTFFNI/SNZmhUAvrG2Bdu+vmoMSbFPs3AaSHlcZQyPzimN/x8Ovbt3luoVALuGm5P0uToyXIwvwprj1yEIACvzsro0uhWaIAvVv5qDFIiA1FU04hf/mMfymqbJIhWOjtOlcNiE5EWHYSkyEC5w2mXv68aMwezJ4u7MGEhyThGV9Kig6DVXPrwm9zPPi3EhEVZjhbW4EB+NXzUAn45to/c4cjirhH2If7dZ8pRanDfB73NJuJ/vj8JAPjFyAQMTtB1+bGigrVY9dgY9Ar1R25FPeZ+sh81DSZXhSo5x/qVKQqsDmrN3aPYk8VdmLCQZK6cDnJwJCz7cqvQaJJnrQBdzdGG/7Yh8YgJ8ZM5GnkkRQZiVJ8w2ETgGzd2kF1zuAg/X9AjSKvBwub9grojPtQf//fYGEQFa5FTUouHP92v2L2SLme22rBNgd1t2zOqTxj6sCeLWzBhIcmcvKJCyCE1KhC9Qv1hstjwU26lHKHRFUr0TVj3s30vnZ5SytwWZ6v+gxfcsjC8zmjBkg32Muanb0pDdLBrksWkyED832NjEBbgg6MX9PjVZwcU/wXhQF41DE0WhAf6YnjvMLnD6RBBEHD3iEuvGZIOExaSzMkrKoQcBEHAJMe0ENv0K8Jft52FxSbiuqTwbk1HeIOZQ+Kg1ahwpqwOx4qk72ny121nUV5rRFJEAB65Psmlj90vJhifzxuDYK0G+3Or8PiqgzBalJu0OLrb3pgeDbXKcyrU7hpp78mSeb6SPVkkxISFJFFdb8JFvX0NwMArEhbg0rQQ2/TL79gFPVbts5cyz5/aV+Zo5Bfi54NpGbEA7J1vpVRQ2YBPdtmn4v4wc2CLtV6uMjhBh08fHQ1/HzV2nC7H7748AovV5vLrdJcoiorubtueXqH+GJ9qLyb47uhFmaPxXkxYSBKO9St9IgIQ7Hd146fxaRFQqwScL6/nNxIZ2WwiXvr2uHPPmvFpkXKHpAh3jbBXC317pAgmi3Qf7m+uPwmT1YaJfSMl/ZAenRSOv88dBV+1ChtOlOC5f/+suL4h58rrkVfZAF+1ChObv9B4EkfjQUfSRa7HhIUkcWWH2yuF+PlgZPMcNauF5PNVViGOFtYgSKvBSzMHyB2OYkxMi0RUsBbVDWZsO1UmyTX2nq3AxhOlUKsEvHzbQMmb9E3oG4kPHxgOtUrAmsNFeOW744pq3uj4oB+XGoEgrUbmaDpvSn/7IuEjhTUorzXKHI13YsJCkmirQuhyl3e9JferrDM6F3suuLkfontoZVBrNGoV7nT0ZJFgIaXFasPr/7GXMf9yTG/0iwl2+TVaMy0jFu/dMxSCAKz6qQBvb8hRTNKy1UOngxxidX4Y3EsHUYSz0olcS5KEpba2FvPnz0efPn3g7++P8ePHIysrq83jt2/fDkEQrrrl5ORIER65gWOEpbX1Kw6OdSx7z1VKOuxOrVuyIQf6RjMGxIVg7rie2XelPXOaKz+2nSpDVb1r+5h8mVWInJJahAb44Jmb+7n0sa9l9rBeeOvOwQCA/7fjPD788axbr9+aqnoTDubbN52c4iHlzK1x9I7htJA0JElYHnvsMWzevBkrV67EsWPHMG3aNEydOhVFRe0vYDt16hSKi4udt759uQDQEzWYLDjfvI9JW1NCADAwLgQRgb6oM1pwqEDeHXJ7moP5VfjnAfvIwR/vyIBGzcHWK6XHBmNQrxCYrSK+O+K6xbf6BjPe23QKgH1kKzTA12WP3VH3X9fbOQX4582n8Ulzh2O5bMspg020vye0tzu10jm2Eth1pkK2/ai8mcvfpRobG7F69Wq88847mDRpEtLS0vDaa68hOTkZH330UbvnRkdHIzY21nlTq3tWa3BvkV1cC1G0d9xsr6eESnVZeTOnhdzGYrXhpbUnAAD3jErAyD7hMkekXI5RljUubCK3dOtpVDeY0S8mCA9c19tlj9tZj01MwTNT7aM7b/znJL7OKpAtFmd10EDPHV0B7F/Q4nR+aDRbkXmOPaZczeUJi8VigdVqhZ9fyw8qf39/7N69u91zhw8fjri4OEyZMgXbtm1r91ij0QiDwdDiRsrQVsO41jjLm5mwuM3nmfnILjZA5++D52/pL3c4inb70HhoVAJ+vqDHmdLabj/emdJafJ5pLyF/5Tb5R7Z+OyUN/zUpBQDwwppjspTkGi1W59+/p65fcRAEwTkttJnTQi7n8r+W4OBgjBs3Dm+88QYuXrwIq9WKVatWYd++fSguLm71nLi4OHz88cdYvXo11qxZg/T0dEyZMgU7d+5s8zqLFy+GTqdz3hITE139VKiLTrTRMK41E/pGOs/xtE3aPFGZoQnvbT4NAHjulnREBGlljkjZIoK0uCHd/gH070PdW3wriiJe/89JWG0ibh4Y43zty0kQBCy6tT8eHNMboggs+PoItpx07wftT+erUG+yIiZEi0HtLNL3FI41OFuzSxWzoNlbSJLer1y5EqIoolevXtBqtfjggw/wwAMPtDnFk56ejl//+tcYMWIExo0bh7/97W+YOXMm3n333TavsWjRIuj1euetsLBQiqdCXdCRCiGHyCAtBveyH7frdIWkcRHw5vps1BktGJoYivtGyzcd4UnuHmmvFlp7uAjWbvQu+TGnDLvOVMBHLeAPM5RTQi4IAt6YPQh3Du8Fi03EE18ccuuIp6M66Kb+MVB5UHfbtoxLiUCArxqlBiOOF3Hk35UkSVhSU1OxY8cO1NXVobCwEPv374fZbEZycsf3KBk7dizOnDnT5u+1Wi1CQkJa3Eh+ZqsNp0rsQ+cdGWEB2PXWXfaeq8C3Ry5CEIA/zh7kUa3P5XRj/2iEBvig1GDE7rNdS6pNFhv+uC4bADBvQjKSIgNdGWK3qVQC/nT3EEzPiIHJYsPcT/djwpIfseDrI/hqfwHOl9dJMlogiqJzROfmgZ49HeTg56PGxObRM1YLuZakE6iBgYGIi4tDdXU1Nm7ciNmzZ3f43MOHDyMuLk7C6EgKZ8vqYLLaEKzVIDEsoEPnXN6PpTvfYKltJosNL689DgD45Zg+PX6/oM7QatS4fWg8gK73ZPlsbx5yK+oRGaTFUzemuTI8l9GoVfjg/uG4fWg81CoBF6obseZwEV5Ycww3/XkHRr+5FU/830Gs2JOLExf1LvlbzS6uxUV9E/x8VBifKv8Umas4poWYsLiWJO0EN27cCFEUkZ6ejrNnz+LZZ59Feno6Hn30UQD26ZyioiJ8/vnnAIClS5ciKSkJGRkZMJlMWLVqFVavXo3Vq1dLER5JyDEdNCA+pMPDu8MSQxGs1aC6wYzjRXoMTQyVMMKe6ZPduThXXo+IQF8snJYudzgeZ86IBHyemY+NJ0pQ22RudbuJtlTUGfHBVvto8XO3pHfqXHfTatT44P7heOuuwTiUX42svCrsy63CkcIaVNQZsf5YCdYfKwEABPtpMDopHKOTwnFdcjgG99LBV9O578COD/SJfaPg5+M9VaE39Y+GINjfD4v1jYjTeW6ptpJIkrDo9XosWrQIFy5cQHh4OObMmYM333wTPj72P9Ti4mIUFFwqoTOZTFi4cCGKiorg7++PjIwMrFu3DjNmzJAiPJLQtVryt8ZHrcL1aZHYcKIEO06XM2FxsaKaRucH5oszBkAXoNwPTKUakqBDWnQQzpbVYf2xYtzbifU/f950CrVGCwb30uHu5jJppQvSajCpX5Sz7YDRYsXPF/TYn1uF/blVOJhfjdomC37MKcOPzV1d/XxUGJ4YhuuSwzEmORzDe4fB37f9JMTTu9u2JTJIi+GJoThUUIMt2WV4aCwbM7qCJAnLPffcg3vuuafN369YsaLFz8899xyee+45KUIhN+vMgtvLTU6PwoYTJdh5uhy/ncKGga70+vcn0Gi24rqkcOemftQ5giDgrhG98M6GU1h9sKjDCcvxIj2+yrIXBLw6a6DHLirVatTO0ZQnb7T38skursX+vCrsz61EVl41qupNyDxficzz9v4jGpWAwQk6XJccjuuSwjGqT3iLZLnU0ISjF/QQBPuCW28zdWAMDhXUYGt2KRMWF/G8HaZIsWw2EdnNCcvAuM4tgnZ8kztUUA19g5mjAC6y7VSZc4O91+/IkHyDPW925/Be+NPGU9ifV4WCygb0jmh/jZYoinj9+5POnbBHJXlPgz6NWoXBCToMTtDhVxOSIYoizpXXYV/zCMz+3CoU65twuKAGhwtq8P92nIcgAOkxwRiTHI7rkiOQX2Xvhj00IRRRwd5XXj91QAze2XAKe89Vot5oQaAHbuioNPwXJJcprG5ArdECX7UKfWOCOnVur1B/55D7nnMVzq3aqeuazFa89p29o+2j45PQP5aVdN0Rp/PHhLRI7DpTgdWHLlxzD6D1x0qwP68Kfj4qvHCrdzfoEwQBadHBSIsOxoNj+kAURVyobkRW3qUE5nxFPXJKapFTUovPmpvnAcDNHt7dti19o4PQOzwABVUN2HWmArcMipU7JI/HDUTIZRzTQf1ig+DThQ6e7HrrWst2nEN+ZQNiQrSY7+YN9rzVpVb9F2Brp0qmyWzFW+vtZcyPT0716P1xukIQBCSGB+CuEQl4e84Q/LjwBmT9YSr+9uAIPDI+CQPjQiAIgFajwkwv/XJyedfbrawWcgmOsJDLOBfcxnWtZHZyvyh8sjsXO06XQxRFTl90Q35lPf62/RwA4OXbBiKIw9EuMT0jFkFaDQqr7KMHY1IiWj3u453nUVTTiHidH34zKdXNUSpTVLAWMwbHOUdP9Y1m2GwiwgLdv/mju9w8IAbL9+Thx5wyWG0iex+1ot5owSvNLReuhSMs5DInHQtue3Vt6uG65HBoNSoU65twpqzOlaH1KKIo4tXvTsBksWFCWqTXfoOVg7+vGjMG24f21xxqfUPEYn0jPmpOFl+YMeCalTI9lc7fx6uTFQAYnRyOYD8NKutNOFJYI3c4irTxREmHNxdlwkIu05k9hFrj56PG2OZvrDtOcVqoqzaeKMX2U+XwVavw+mwutHW1u5qnhdYdK0ajyXrV75f8kINGsxWj+oRh1hAmiz2Zj1rlnOpmE7nWfdOJndCZsJBLlNcaUVZrhCCgW4s72aa/expMFrz+vX2h7X9NSkFKVOcWP9O1XZcUjoQwf9QZLdh0sqTF7w7mV2Nt8/YHr85iskiXFhVzHcvVymqbsKcT210wYSGXcKxfSY4M7Fb5nqO8ed/5KjSYLC6JrSf5YOtZXNQ3oVeoP55UaAt4T6dSCc5Rln9f1qrfZhOdyeI9IxO5/QEBAG7oFw21SsDp0joUVDbIHY6ifH+0GDYRGNrBvxUmLOQSXW0Yd6XUqED0CvWHyWrDvvNVrgitxzhbVot/7DoPAHjt9gyunZDQnOYGfHvOVqBE3wQAWHO4CEcv6BGk1WDhdG5/QHa6AB+MTgoDwGmhK61tng6aNbRjU6dMWMglTnZz/YqDIAjOzRB3sLy5w0RRxMtrT8BiEzF1QLTX9rZQij4RgRidFAabaJ+DrzNasGRDDgDg6ZvSvLIRGnXd1ObNELfmMGFxOFtWh2NFemhUAqZlMGEhN+rKHkJtmdSX/Vg667ujF5F5vhJajQqvzsqQO5wewdmT5dAF/HXbWZTXGpEUEYBHrk+SNzBSHMfuzfvOV8HQZJY5GmX49oh9dGVyvyiEd7BajAkLdVttkxl5zXOz3Z0SAoDxaRHQqAScr6hHYRXnfK/F0GTGH9fZm5Q9dWMaEsPbbxlPrjFjSBy0GhXOlNXh/+2wlzH/YeZAaDWciqOWkiMDkRoVCItNZAUk7CPCjuqgO4Z3fH8zJizUbdnFtQCAOJ1fhzPl9oT4+WBEH/ucL6eFru1/N59Gea0RyZGB+K/JKXKH02OE+PlgWoa9J4tNBCb2jfS6XYfJdaY2T9NyHYu9mu5CdSOCtBrndFlHMGGhbnPldJCDo7yZCUv7TlzU47O9eQCA/7k9g9/u3cyx+FatEvDybQNZxkxtcnwwb8spg9lqkzkaeTlGV6ZnxHaqOIAJC3Wbo0JooAumgxwcCcvesxUwWXr2H3dbbDYRL689DpsIzBwc5ywJJ/eZ1DcKz05Px//eOwz9YoLlDocUbETvMIQF+MDQZMGBvGq5w5GNyWLDumPFAOw7oHcGExbqtu52uG3NwLgQRAb5ot5kxcH8nvvH3Z5/H7yAQwU1CPBV46XbBsgdTo+kUgl48sY03D40Xu5QSOHUKgE39udmiDtOl6OmwYzoYC3Gpba+F1dbmLBQtxgtVpwpta9hcWXColIJl6qF2PX2KtX1Jiz+wb7Q9pmp/RCn61m7ARN5Ise00JbsUohi27t9ezNH75XZw+I7vRkkExbqljOldbDYROj8fdAr1LUfmo4pDq6qv9o7G0+husGMfjFBLKMl8hCT+kXBV61CXmUDzpXXyx2O2xmazNjcPLo0e1jnpoMAJizUTZcvuHX1gsOJfSMhCMDJYgPKaptc+tie7EhhDb7KKgAAvDF7EHzU/DMm8gRBWg3GpIQD6JnVQhuOlcBksaFvdFCXRuT5Tkfd4lxwG+e66SCHiCAtBveyL+TddbrjG2R5M6tNxEtrj0EUgbuG98KYlM7NARORvHryZohrj1zqvdKVL7hMWKhbnAtue7k+YQFY3nylL/bl43iRAcF+GiyawYW2RJ7mpuaFtwfzq1FVb5I5Gvcp1jci83wlAPv6la5gwkJdZrWJyC52zaaHbXGsY9l1phxWW89cpOZQXmvEOxtPAQCenZ7O/WqIPFBCWAAGxIXAJtp7svQU3x25CFEErksKR0JY17pxM2GhLsurrEeDyQqtRoWUyEBJrjE8MRTBfhpUN5hxrEgvyTU8xeIfslHbZMGgXiF4cEwfucMhoi5ydETuSZshdqUV/5WYsFCXOaaD+seFQCPRwk+NWoUJaZEAevZmiPtzq7DmUBEEwb7QtrPlgESkHI7y5h2nymG0WGWORno5JQbklNTCV63CzMEd25m5NUxYqMtOStAwrjWTevg6FrPVhpfXHgcA3De6N4b3DpM5IiLqjsG9dIgK1qLeZMW+81VyhyO5tYcvAgBu7B8FXYBPlx+HCQt1mRR7CLXGkbAcLqiGvqHnbc2+Yk8eTpXWIizAB89NT5c7HCLqJpVKcE4LeXt5s80m4tvm6qDOtuK/EhMW6hJRFC8bYZFmwa1Dr1B/9I0Ogk0E9pzrWeXNJfomLN1yGgDwwq39EeaC3bCJSH5T+jvKm8u8uuvtvtwqFOubEOynwQ3p3dvNnAkLdUmpwYjKehPUKgH9Y6Xf9G1yD+16+9b6bNSbrBjROxS/GJkodzhE5CLXp0VCq1GhqKYR2cW1cocjGUcr/pmD4+Dn073d5JmwUJc4poNSowK7/SLsiMvXsXjzt5HLHcirwndHL0IQgNdnD4KKC22JvIa/rxoT+9oLCry1iVyT2Yr1zTszd6c6yIEJC3XJCTdNBzlclxwOPx8VSgxNOF1a55ZryslmE/E/358EANw7KhGDernn35mI3GfKZZsheqNtOWWoNVoQr/PDdUnh3X48JizUJe5acOvg56PG2OY29D2hvPnfhy7gWJEewVoNfj+NC22JvNGU5q63Ry/oUWbwvv3SHL1Xbh/WyyUjxExYqEucewi5KWEBgEl9e0Z5c22TGe9ssHe0fXpKGjvaEnmp6BA/DE2wj57+6GVdb2saTNh2yv6culsd5MCEhTpN32DGhepGAEBGnPumKian2xOW/blVaDBZ3HZdd/vrtnOoqDMiOTIQj4xPljscIpLQVC+dFlp3rBhmq4gBcSFId1FhBhMW6rQTxfbpoIQw/241AeqslMhAJIT5w2S1eW2zpfzKeny6OxcA8IcZA+Cr4Z8okTdzrGPZfbYCjSbv6Xr7bXOzuDuHd22jw9bw3ZA6zV0dbq8kCILXd719c102TFYbJvaNxJQB3etZQETKNyAuGL1C/dFktmHPWe/oM1VY1YD9eVUQBOD2oa6ZDgKYsFAXuLtC6HKTvThh2XO2AptOlkKtEvDybQMhCCxjJvJ2giA4v5x4y2aI3x21j66MS4lArM7PZY/LhIU6zd0VQpcbnxoBjUpAbkU9Ciob3H59qVisNrzeXMb8yzG90S9G+mZ8RKQMl9axlMFm8+w+U6IoYs2hCwBc03vlckxYqFOazFacK68HIM8IS7CfD0b2sW/+t+OM94yyfJlViFOltQgN8MEzN/eTOxwicqMxKeEI9FWjvNaIY0V6ucPplhMXDThXXg+tRoVbBsW69LGZsFCn5JTUwmoTER7oi5gQecptJ3lZm359gxnvbbKXMT8ztR9CA7hfEFFPotWone9rnl4t5GjFP3VgDEL8XFuUIUnCUltbi/nz56NPnz7w9/fH+PHjkZWV1e45O3bswMiRI+Hn54eUlBQsW7ZMitComy6fDpJrjYVjHUvmuQqYLDZZYnClpVtPo7rBjH4xQXhwTG+5wyEiGVw+LeSprDYR3zavX7ljmGungwCJEpbHHnsMmzdvxsqVK3Hs2DFMmzYNU6dORVFRUavH5+bmYsaMGZg4cSIOHz6MF198Eb/97W+xevVqKcKjbpCjYdyVBsaFIDJIi3qTFQfzq2WLwxXOltXi88x8AMDLtw2ERs1BT6Ke6Mb+0VAJQHaxAReqPXN93t5zFSivNSI0wMf5xdKVXP7u2NjYiNWrV+Odd97BpEmTkJaWhtdeew3Jycn46KOPWj1n2bJl6N27N5YuXYoBAwbgsccew7x58/Duu++6OjzqJjkrhBxUKgGTmjcN8+RqIVEU8fp/smG1iZg6IAYT+7r+D5yIPEN4oK9zfZ6ndr11tOK/bUicJD2kXP6IFosFVqsVfn4tS5n8/f2xe/fuVs/JzMzEtGnTWtw3ffp0HDhwAGazudVzjEYjDAZDixtJy2K1IadYnh4sV3J0vfXkhGXbqTLsPF0OH7WAP8wcIHc4RCSzKR48LdRosmLj8RIArmvFfyWXJyzBwcEYN24c3njjDVy8eBFWqxWrVq3Cvn37UFxc3Oo5JSUliImJaXFfTEwMLBYLKipab6SzePFi6HQ65y0xMdHVT4WucL6iHkaLDQG+aiRHBMoay4S0SAjNw6eeuGmYyWLDH/+TDQCYd30ykiPl/fckIvk51rH8dK4SdUbP2n5kc3Yp6k1WJIb7Y0TvMEmuIcmE+cqVKyGKInr16gWtVosPPvgADzzwANRqdZvnXLmAUxTFVu93WLRoEfR6vfNWWFjouidArXJ0uB0QF+KSnTe7IyJIiyG97NNSO894XnfIzzPzcL6iHpFBvnjqpjS5wyEiBUiNCkRSRABMVht2edjosaM66I5hvSQryJAkYUlNTcWOHTtQV1eHwsJC7N+/H2azGcnJrW/kFhsbi5KSkhb3lZWVQaPRICIiotVztFotQkJCWtxIWnI2jGuNp7bpr6gz4v2tZwAAz05PR7CLS/+IyDMJguAcZdnsQeXNlXVG5/vwbAmqgxwkLUkIDAxEXFwcqqursXHjRsyePbvV48aNG4fNmze3uG/Tpk0YNWoUfHz4Zq4UJ2TaQ6gtjlXou86Uw+pB3SH/vOk0apssyIgPwd0jOZVJRJc41rFsyynzmPe1//xcDKtNxJAEHdKigyS7jiQJy8aNG7Fhwwbk5uZi8+bNuPHGG5Geno5HH30UgH06Z+7cuc7jH3/8ceTn52PBggXIzs7Gp59+ik8++QQLFy6UIjzqAlEUFVEhdLlhiaEI9tOgpsHsMd0hT1zU46usAgDAq7MyoJZ5ao2IlGVUUhh0/j6objDjUIFntG1Ye8Q+HSTl6AogUcKi1+vx5JNPon///pg7dy4mTJiATZs2OUdLiouLUVBQ4Dw+OTkZ69evx/bt2zFs2DC88cYb+OCDDzBnzhwpwqMuKKpphL7RDI1KQN8Y6TLoztCoVZiQ1lze7AFdb0VRxOvfn4QoAjOHxOG65HC5QyIihfFRq3BDuud0vc2rqMfhghqoBGDW0DhJr6WR4kHvuece3HPPPW3+fsWKFVfdN3nyZBw6dEiKcMgFHKMrfWOCodW0vXja3Sb3i8IPx0uw43QZfje1r9zhtGvD8RLsy62CVqPColv7yx0OESnUlAEx+PbIRWw5WYpFtyq75YFjdGVC3yhEB7tuZ+bWsK0mdYjS1q84OBbeHimsgb6h9Z49StBktuLN9fYy5t9MSkFCWIDMERGRUk3uFwWNSsC58nrkVdTLHU6bRFF0VgfdOTxe8usxYaEOOamwCiGH+FB/9IsJgk0Edp9VbnnzJ7tzcaG6EbEhfnj8hlS5wyEiBdP5+zinjJU8LXT0gh55lQ3w91Fj2kDX7szcGiYs1CFKW3B7uUl9HeXNyuwOWWpowl+3nQUAvHBrfwT4SjITS0Re5NJmiMpNWByjK9MyYhColf59jQkLXVNVvQnFens32QFxwTJHc7XL2/Q7Gg4qyZINOWgwWTGidyhmD5N+2JSIPJ8jYcnKq1bkdLfZasP3jp2ZJWrFfyUmLHRNjoZxSREBimxyNjopHH4+KpQajDhdWid3OC0cLqjGmkP2byGvzsqQrAMkEXmX3hEB6BcTBKtNxHYFjh7vPlOBynoTIgJ9MbG5WlNqTFjompQ8HQQAfj5qjE2xd0RW0rSQzSbif74/CQCYMyIBQxND5Q2IiDyKkjdDdOzMPGtoPDRq96QSTFjomhwJy0CFLbi93GQFtun/9mgRjhTWIMBXjeduSZc7HCLyMI5poe2nymC22mSO5pI6owWbTtq303HXdBDAhIU6wDEl5AkJS1ZuNRpM8u9yWm+04O0fcgAAT96YhpgQafsTEJH3GZYYiohAX9Q2WZCVWyV3OE6bTpSgyWxDcmQghia4b+SdCQu1q95oQW5zHwCllTRfLjkyEAlh/jBZbfjpfKXc4WDZjnMoNRiRGO6PX01ofdNPIqL2qFUCbuwfDUBZmyF+44admVvDhIXalVNigCgCUcFaybsYdocgCJemhWRu019Y1YCPd54HAPxhxgD4+SinMzAReZbLy5uVUAVZZmjCnuaeV3e4oVnc5ZiwULuU2uG2NUpZx/L2DzkwWmwYmxKO6RnSN1MiIu81sW8kfNUqFFY14kyZ/FWQ3x29CJsIDO8dij4RgW69NhMWateJIs9JWManRUKjEpBX2YB/7DoPQ5P7exfsO1+JdceKoRKAV25jGTMRdU+gVoPxafYqSCU0kfv2iL33yp1uXGzrwISF2nWi2NGSX5klzZcL0mqcIxp/XJeNsW9txYvfHMPJ5lEiqVkvK2O+77reil6kTESew1HevFXm8uazZbU4VqSHRiVg5mBpd2ZuDRMWapPZasPpEvsQpCeMsADAu78Yiv+5PQNp0UFoMFnxxb4CzPhgF+7+aC/WHi6C0WKV7Nr/OlCIk8UGBPtp8Pub+0l2HSLqWaYOsC+8PVRQjYo6o2xxrD1sH12Z3C8KEUFat1+fCQu16WxZHUxWG4K1GiR6yO7C/r5qPDw+CZufmYQvfz0WMwfHQaMScCC/GvO/PoLxi3/Ekg05KKxqcOl1DU1m/GnjKQDA76b0leWPmYi8U5zOHxnxIRBFYFuOPKMsoihi7ZHm6iAZpoMAJizUDseC2wHxIVCpPGsthiAIGJcagb8+OAJ7X7gJC27uh9gQP1TWm/DR9nOY9Kdt+NWKLGw7VQabrfsr7z/88Swq601IiQzE3HFJ3X8CRESXkXszxIP51bhQ3YhAX7UzFndjwkJtcjSM85TpoLZEh/jht1P6YvfzN2LZL0diYt9IiCKwNacMjy7PwuR3t2HZjnOoqjd16fFzK+qxfE8uAODl2wbCV8M/KyJyLUeSsOtMBZrM0k1tt8XRe+WWQXHw95WnVQPfWalNSt9DqLM0ahVuGRSLlb8agx9/Pxm/mpCMED8NCqsa8fYPORi7eCsWfH0EhwqqO9Xv4M11J2G2ipjcL8rZ5ImIyJUG9QpBTIgWDSYrMt3cHNNkseE/PxcDkKc6yIEJC7XKZhOR7UE9WDorJSoIL982EPtenIp35gzB4F46mCw2rDlchLv+thczP9iNL/cXXLPN/87T5diSXQaNSsDLtw1wU/RE1NMIgnBZtZB7p4W2nyqDvtGM6GAtxqVGuPXal2PCQq0qrG5ArdECX40KadFBcocjGX9fNe4ZnYjvn56Ab5+8HnePTIBWo8LJYgMWrTmGMW9uxWvfncDZVho2Waw2vPEfexnzQ+P6IC062N3hE1EP4qgW2ppd5taut47FtrcPjYdaxvWMGtmuTIrmmA5KjwmGj5u2Dpfb0MRQDE0MxUszB+DfBy9g1U/5yKtswIq9eVixNw/jUiLw0Lg+uHlgDHzUKvzfvgKcKatDWIAP5k9hGTMRSWt8aiT8fdQo1jfhxEUDBvWSfrre0GTGlub+L3JVBzkwYaFWecuC264IDfDFYxNTMO/6ZOw+W4GVP+Vja3YpMs9XIvN8JaKDtbh3dCI+z8wHACyYlg5dgI/MURORt/PzUWNC30hsPlmKO/+2BwPiQjA0wf5Fa1hiKFIiA11e0bnhWAlMFhv6RgfJ/nnAhIVa5Ul7CElFpRIwqV8UJvWLwsWaRny5vwBf7i9EWa0Rf/nxLACgf2ww7h+dKHOkRNRT/GpCMo4U1qC81oifL+jx8wU9Vv5k//IUrNVgSKIOwxJDMTTBnsREh3Rv01rnzszD3bszc2uYsFCrHAnLQC+pEOqu+FB//H5aOp6+qS82nijByp/ycbasDn+8YxA0PWTKjIjkNzYlAvtfnIIL1Y04eqEGRwpqcPRCDY4V6VFrtGDP2UrsOXupiihO52dPYJqTmCEJOgRqO/bRX6xvxE+59seaPcy9OzO3hgkLXaWstgnltUYIAjAgjgtJL+erUWHW0HjMGir/Hy8R9UyCICAxPACJ4QG4bYj9vchiteF0aR2OFNbgaKE9iTldWotifROK9SX44XgJAEAlAH2jgzE0UYdhiWEYmqhDekxwq1+8vjtyEaIIXJcUjgQFdDtnwkJXcYyupEQGIsCXLxEiIqXTqFUYGB+CgfEheGBMbwBAvdGCY0V6ZwJzpKAGF/VNOFVai1OltfjngQsAAD8fFQbF65wjMcMSQ5EQ5t9iOkgJvO7T6KF/7MN/TR2E6RkxHKrvopOcDiIi8niBWg3GpkRgbMql3illhiYcvaDHkcJqHC3U4+iFGtQ2WXAgvxoH8qudx4UF+KC6wQxftUqWnZlb43UJy+HCGjz5xSHE6/wwd3wS7hudiNAAX7nD8ig9uUKIiMibRYf44eaBfrh5oL0Jnc0mIrey3rkW5mhhDU4WG1DdYAYATB0YrZgqSK9LWB6fnIrVxypxUd+Et3/IwdItp3HXiAQ8Oj4JfWO4HqMjWCFERNQzqFQCUqOCkBoVhDkjEwAARosVJy8akFtRjxvSlbPdiCC6s12ehAwGA3Q6HfR6PXz9A/H90YtYvicPJ4sNzmMm9o3EvAnJmNw3yuN2H3YXQ5MZQ17bBAA49PLNCA/k6BQREUnn8s/vkJC2vyh73QgLYG+u84tRibh7ZAL25VZh+Z5cbDpZil1nKrDrTAVSIgPxyPVJmDMiocPlXT2FY/+gOJ0fkxUiIlIMr/60FgTBueCosKoBn+3Nw9dZhThfUY9Xvj2BP208hftGJ2LuuCQkhstfsqUEnA4iIiIl6jFlNInhAXjptoHIfHEK/uf2DCRHBqK2yYK/78rF5D9tw+MrD2Lf+Uq3biilRGwYR0RESuTVIyytCdJq8PD4JDw0tg+2ny7D8j152HWmAhtOlGDDiRJkxIfg0euTMWtoHLQatdzhuh0rhIiISIm8ctFte4t2WnO6tBbL9+Thm8MX0GS2AQAig3zx4Jg+eHBsb0QHd28vBk9htFiR8cpGWGwidj9/oyI6GxIRkXfr6Oc3E5bLVNeb8GVWAVZm5qNY3wQA8FELmDU0HvOuT3bLVt5yOl6kx21/2Q2dvw+OvHKz7BtdERGR9+vRVUJdFRboiyduSMOvJ6Zgw/ESLN+Ti0MFNVhzqAhrDhVhdFIY5l2fjJsHemcX3cung5isEBGRkjBhaYWP+tIGd0cKa7B8Ty7W/VyMrLxqZOVVY9rAGHw8d5TcYbocK4SIiEipvG+YwMWGJYbi/fuGY/fzN+G/JqUAAHaeKYfN5hUzaS1cSli8e+qLiIg8DxOWDorV+eG56enwVavQZLahqKZR7pBcymoTkV3MERYiIlImlycsFosFL730EpKTk+Hv74+UlBS8/vrrsNlsbZ6zfft2CIJw1S0nJ8fV4XWLRq1CUqS9cuZseZ3M0bhWXmU9GkxW+PmokBIVJHc4RERELbh8DcuSJUuwbNkyfPbZZ8jIyMCBAwfw6KOPQqfT4Xe/+1275546darFCuGoqChXh9dtadFBOF1ah3NldbhRQZtCdZdjOqh/bAjU3GeJiIgUxuUJS2ZmJmbPno2ZM2cCAJKSkvDll1/iwIED1zw3OjoaoaGhHbqO0WiE0Wh0/mwwGNo52nXSmkcfzpZ51wgLG8YREZGSuXxKaMKECdi6dStOnz4NADh69Ch2796NGTNmXPPc4cOHIy4uDlOmTMG2bdvaPXbx4sXQ6XTOW2Jiokviv5bUaO9MWE5ywS0RESmYy0dYnn/+eej1evTv3x9qtRpWqxVvvvkm7r///jbPiYuLw8cff4yRI0fCaDRi5cqVmDJlCrZv345Jkya1es6iRYuwYMEC588Gg8EtSUtq8wjLOS9awyKKIkuaiYhI0VyesHz99ddYtWoVvvjiC2RkZODIkSOYP38+4uPj8fDDD7d6Tnp6OtLT050/jxs3DoWFhXj33XfbTFi0Wi20Wq2rw7+m1KggCAJQ3WBGZZ0REUHuj8HVSgxNqKo3Qa0SkB4bLHc4REREV3H5lNCzzz6LF154Affddx8GDx6Mhx56CM888wwWL17cqccZO3Yszpw54+rwus3fV41eof4AvGda6ESRfXQlNSoQfj49b8NHIiJSPpcnLA0NDVCpWj6sWq1ut6y5NYcPH0ZcXJwrQ3MZx7SQt5Q2s2EcEREpncunhGbNmoU333wTvXv3RkZGBg4fPoz33nsP8+bNcx6zaNEiFBUV4fPPPwcALF26FElJScjIyIDJZMKqVauwevVqrF692tXhuURadBB2nC7HubJ6uUNxCVYIERGR0rk8YfnLX/6Cl19+GU888QTKysoQHx+P3/zmN3jllVecxxQXF6OgoMD5s8lkwsKFC1FUVAR/f39kZGRg3bp1HaoskkNatHeOsAxkwkJERAoliKLoFZvidHR7alfIyqvCL5ZloleoP/a8cJOk15JaTYMJw17fDAA4+so06AJ8ZI6IiIh6ko5+fnMvoS5wrGEpqmlEvdEiczTd4+i/khDmz2SFiIgUiwlLF4QH+iI80BcAkFvh2etY2H+FiIg8AROWLvKWFv2XFtyyQoiIiJSLCUsXeUuL/pPFHGEhIiLlY8LSRWlekLA0ma04V26f0uIICxERKRkTli5KjQoE4Nl7Cp0tq4PVJiIswAcxIZ6/xQAREXkvJixd5Bhhyaush8XauS6+SpHdPB2UHhsMQRBkjoaIiKhtTFi6KF7nD38fNcxWEflVDXKH0yU5JbUAgP6xXL9CRETKxoSli1QqAanR9mkhT13Hcqo5YRkQxx2aiYhI2ZiwdIOjgZynrmPJKXFMCXGEhYiIlI0JSzd4ci+W8lojKupMEASgX0yQ3OEQERG1iwlLNzgW3p7zwITFMR2UFBGIAF+X74FJRETkUkxYusGZsJTXw9P2kHROB8Vw/QoRESkfE5Zu6BMRCLVKQJ3RglKDUe5wOsVZIcQFt0RE5AGYsHSDr0aFPuEBADxvHYtjhIUlzURE5AmYsHTTpT2FamWOpOMsVhtOl9oTrP6xHGEhIiLlY8LSTc49hTyotDmvsgEmiw3+Pmr0bh4hIiIiUjImLN2U6oGlzZf6rwRDpWJLfiIiUj4mLN10eaWQp8gpdrTk53QQERF5BiYs3eTYtbm81gh9o1nmaDrm0h5CTFiIiMgzMGHppmA/H8SG+AHwnGkhtuQnIiJPw4TFBRybIHpCx9vaJjMuVDcC4AgLERF5DiYsLpDmQZsgni61TwfFhvghLNBX5miIiIg6hgmLCzhLmz1ghCW7ecFtOkdXiIjIgzBhcYFUD+rF4uxwy5b8RETkQZiwuIBjSqiwqgFNZqvM0bTPsUvzAC64JSIiD8KExQWigrUI9tPAJgJ5lcrtxyKKorMHC6eEiIjIkzBhcQFBEDxiHUtRTSNqjRZoVIKzQy8REZEnYMLiImke0KLfMR2UFh0EXw3/1xMRkefgp5aLpHrACIujwy2ng4iIyNMwYXGRS71YlLuG5VJLfi64JSIiz8KExUUca1jOl9fBahNljqZ1OcUsaSYiIs/EhMVFEsMD4KtRwWixoai59b2SGC1WnK+wj/6wJT8REXkaJiwuolYJSIm07yl0trxW5miudrbMPvKj87+0WSMREZGnYMLiQo5S4XNlylvH4ui/0j82GIIgyBwNERFR5zBhcSElVwo5W/JzOoiIiDwQExYXSlPwnkLOCqE4VggREZHnYcLiQpc3jxNFZVUKXSpp5ggLERF5HiYsLpQSFQhBAPSNZlTUmeQOx6myzojyWiMAoF8MExYiIvI8Lk9YLBYLXnrpJSQnJ8Pf3x8pKSl4/fXXYbPZ2j1vx44dGDlyJPz8/JCSkoJly5a5OjTJ+fmokRDmDwA4p6BpIUdL/j4RAQjUamSOhoiIqPNcnrAsWbIEy5Ytw4cffojs7Gy88847+NOf/oS//OUvbZ6Tm5uLGTNmYOLEiTh8+DBefPFF/Pa3v8Xq1atdHZ7klLinUDang4iIyMO5/Ot2ZmYmZs+ejZkzZwIAkpKS8OWXX+LAgQNtnrNs2TL07t0bS5cuBQAMGDAABw4cwLvvvos5c+a0eo7RaITRaHT+bDAYXPckuiEtOgjbTpUrKmFxdLhNZ0t+IiLyUC4fYZkwYQK2bt2K06dPAwCOHj2K3bt3Y8aMGW2ek5mZiWnTprW4b/r06Thw4ADMZnOr5yxevBg6nc55S0xMdN2T6AZnLxYlTQmV2kdYBnCEhYiIPJTLR1ief/556PV69O/fH2q1GlarFW+++Sbuv//+Ns8pKSlBTExMi/tiYmJgsVhQUVGBuLi4q85ZtGgRFixY4PzZYDAoImlxlDafU8gIi9UmOtewsKSZiIg8lcsTlq+//hqrVq3CF198gYyMDBw5cgTz589HfHw8Hn744TbPu7L7qqMsuK2urFqtFlqt1nWBu4gjYbmob0K90SL7Ite8ynoYLTb4+ajQOzxA1liIiIi6yuWfps8++yxeeOEF3HfffQCAwYMHIz8/H4sXL24zYYmNjUVJSUmL+8rKyqDRaBAREeHqECUVGuCLyCBfVNSZcK68DkMSQmWNxzG6kh4TDLWKLfmJiMgzuXwNS0NDA1Sqlg+rVqvbLWseN24cNm/e3OK+TZs2YdSoUfDx8XF1iJJLUVClkGPBbX8uuCUiIg/m8oRl1qxZePPNN7Fu3Trk5eXhm2++wXvvvYc777zTecyiRYswd+5c58+PP/448vPzsWDBAmRnZ+PTTz/FJ598goULF7o6PLdwrmNRwMJbR4fbdC64JSIiD+byKaG//OUvePnll/HEE0+grKwM8fHx+M1vfoNXXnnFeUxxcTEKCgqcPycnJ2P9+vV45pln8Ne//hXx8fH44IMP2ixpVjol9WK5tIcQExYiIvJcgqi0TW+6yGAwQKfTQa/XIyRE3umPnafLMffT/UiNCsTW398gWxx1RgsGvboRAHDo5ZsRHugrWyxERESt6ejnN/cSkkBq85RQfmUDzNb2tySQ0unm/ivRwVomK0RE5NGYsEggXueHAF81LDYR+ZUNssWRU8z+K0RE5B2YsEhAEARnx1s517HklDgqhLh+hYiIPBsTFokooVIoh5seEhGRl2DCIpHUqEAA8o2wiKLIHixEROQ1mLBIRO4RlmJ9EwxNFqhVAlKjA2WJgYiIyFWYsEjk8k0Q5agcd7TkT40KhFajdvv1iYiIXIkJi0T6RARCoxJQb7KiWN/k9utnl3A6iIiIvAcTFon4qFXoHWHfHVmOdSyOkma25CciIm/AhEVCjhb9cqxjcUwJDWBLfiIi8gJMWCTkWMfi7hEWo8XqTJI4JURERN6ACYuE5EpYzpXVw2ITEeynQZzOz63XJiIikgITFgnJVdp8qtS+4HZAbAgEQXDrtYmIiKTAhEVCKc1rWCrqTKhpMLntupf2EOL6FSIi8g5MWCQUpL00JePOURZHS35WCBERkbdgwiIxOdax5LAHCxEReRkmLBJz967N1fUmlBqMADjCQkRE3oMJi8RS3TzC4pgOSgz3R5BW45ZrEhERSY0Ji8QuNY+rd8v1OB1ERETeiAmLxBxrWAqrG9Bktkp+PUeF0ABOBxERkRdhwiKxyCBf6Px9IIrAeTeMsuSUOiqEOMJCRETegwmLxARBQGpUIADgrMSlzVabiNMl7MFCRETehwmLGzg73kq88LagqgGNZiu0GhWSIgIlvRYREZE7MWFxA2cvFolHWE41L7jtFxMMtYot+YmIyHswYXEDd42wZDta8nPBLREReRkmLG7gaB53vqIeVpso2XWcJc1xXHBLRETehQmLGySEBcBXo4LJYsOF6gbJrnOqhCMsRETknZiwuIFaJSAlsrlSSKJpoQaTBflV9mSICQsREXkbJixuIvUmiKdL6yCKQGSQFhFBWkmuQUREJBcmLG4i9SaIOcX29SsD2H+FiIi8EBMWN3FWCklU2pzD9StEROTFmLC4yeVTQqLo+kohR4UQW/ITEZE3YsLiJsmRgRAEwNBkQXmd0aWPLYoiR1iIiMirMWFxEz8fNRLDAgC4fh1LqcGImgYz1CrBOZJDRETkTZiwuJFUHW8d00HJkYHw81G79LGJiIiUgAmLG11aeFvv0sfldBAREXk7JixulCZRafOlkmYuuCUiIu/EhMWNUqOl6XbrGGFJj+EICxEReScmLG6UFmVPKEoMTahtMrvkMU0Wm7O3S382jSMiIi/l8oQlKSkJgiBcdXvyySdbPX779u2tHp+Tk+Pq0GSnC/BBZHPb/PMuWsdyvqIOZquIYK0GvUL9XfKYRERESqNx9QNmZWXBarU6fz5+/Dhuvvlm/OIXv2j3vFOnTiEk5NIajKioKFeHpghp0YGoqDPibFkdhiaGdvvxHDs0p8cGQxCEbj8eERGRErk8Ybky0Xj77beRmpqKyZMnt3tedHQ0QkNDXR2O4qRGBeGn81U466IW/dnFzRVCnA4iIiIvJukaFpPJhFWrVmHevHnX/PY/fPhwxMXFYcqUKdi2bds1H9toNMJgMLS4eQJX79rs6MHSny35iYjIi0masKxduxY1NTV45JFH2jwmLi4OH3/8MVavXo01a9YgPT0dU6ZMwc6dO9t97MWLF0On0zlviYmJLo5eGq7eBPEUe7AQEVEPIIhS7MTXbPr06fD19cX333/fqfNmzZoFQRDw3XfftXmM0WiE0XhpTx6DwYDExETo9foWa2GUpljfiHGLf4RaJSD79Vvgq+l6zqhvMGPo65sAAD+/Ng0hfj6uCpOIiMgtDAYDdDrdNT+/JRthyc/Px5YtW/DYY491+tyxY8fizJkz7R6j1WoREhLS4uYJYkP8EOirhtUmIr+ye5VCjumghDB/JitEROTVJEtYli9fjujoaMycObPT5x4+fBhxcXESRCU/QRCQ6qJ1LGzJT0REPYXLq4QAwGazYfny5Xj44Yeh0bS8xKJFi1BUVITPP/8cALB06VIkJSUhIyPDuUh39erVWL16tRShKUJaVBB+vqDv9joWLrglIqKeQpKEZcuWLSgoKMC8efOu+l1xcTEKCgqcP5tMJixcuBBFRUXw9/dHRkYG1q1bhxkzZkgRmiK4fISFJc1EROTlJElYpk2bhrbW8q5YsaLFz8899xyee+45KcJQLGdpczdGWGw2kRVCRETUY3AvIRmkNu/afK6sHjZb14q0Cqsb0GCywlejQlJEoCvDIyIiUhwmLDLoExEAjUpAo9mKYkNTlx7DMR3ULyYIGjX/NxIRkXfjJ50MfNQqJEXaR0W6uo4lp7klf3oMF9wSEZH3Y8Iik7So7i28dVQIDeCCWyIi6gGYsMgkNbp7IyyXFtxyhIWIiLwfExaZOPcU6kLC0miyIre5S246K4SIiKgHYMIik7Qoe6LRleZxp0trIYpAZJAvooK1rg6NiIhIcZiwyCQlyj4lVFlvQnW9qVPnOqaDOLpCREQ9BRMWmQRqNYjX+QHofAO5bLbkJyKiHoYJi4y62qLfUdLMDrdERNRTMGGRUVcW3oqiyE0PiYiox2HCIqOu7ClUXmtEdYMZKgHoGxMkVWhERESKwoRFRqldaB7naMmfHBkIPx+1JHEREREpDRMWGTlGWIpqGtFosnboHE4HERFRT8SERUYRgb4IDfCBKALnKzo2ysIFt0RE1BMxYZGRIAid3lPIMSXUP44jLERE1HMwYZGZYx1LRyqFzFabM7HhCAsREfUkTFhk1plKodyKepisNgRpNegV6i91aERERIrBhEVml3qx1F/z2JzLWvKrVIKkcRERESkJExaZORKW3Ip6WKy2do/NKbZXCHEPISIi6mmYsMgsPtQfWo0KJqsNhdWN7R7rGGEZwISFiIh6GCYsMlOrBKR0sFLoFCuEiIioh2LCogDOdSztLLzVN5pRVGMfgekXwxEWIiLqWZiwKEBHerE4Rld6hfpD5+/jlriIiIiUggmLAjhLm9tNWBwt+Tm6QkREPQ8TFgVIjQ4EYG8eJ4piq8dkX1bSTERE1NMwYVGA5MhAqASg1mhBea2x1WMcJc1ccEtERD0RExYF0GrU6B0eAKD1aSGbTcTpUvv9LGkmIqKeiAmLQrTXor+ophF1Rgt81SokRQa6OzQiIiLZMWFRiNR2KoUcDePSooPgo+b/MiIi6nn46acQqe1UCl1av8LpICIi6pmYsChEe83jHCMsLGkmIqKeigmLQjimhEoNRhiazC1+l+PswcIKISIi6pmYsCiEzt8HUcFaAPZ+LA5NZityK+oBcEqIiIh6LiYsCtJai/4zpXWwiUB4oC+igrRyhUZERCQrJiwKcmkdS73zvpzLWvILgiBLXERERHJjwqIgre0pdGnBLdevEBFRz8WERUEcC28vrxTK4aaHRERETFiUxDHCkl9ZD6PFCgA45Rhh4YJbIiLqwVyesCQlJUEQhKtuTz75ZJvn7NixAyNHjoSfnx9SUlKwbNkyV4flEWJCtAjSamATgfzKBpTXGlFRZ4IgAH2jmbAQEVHP5fKEJSsrC8XFxc7b5s2bAQC/+MUvWj0+NzcXM2bMwMSJE3H48GG8+OKL+O1vf4vVq1e7OjTFEwShRcdbx3RQckQg/H3VcoZGREQkK42rHzAqKqrFz2+//TZSU1MxefLkVo9ftmwZevfujaVLlwIABgwYgAMHDuDdd9/FnDlzXB2e4qVGBeJoYQ3OltUhoDlJ4XQQERH1dJKuYTGZTFi1ahXmzZvXZkluZmYmpk2b1uK+6dOn48CBAzCbza2eAwBGoxEGg6HFzRtcXimUXWxfv5IewwohIiLq2SRNWNauXYuamho88sgjbR5TUlKCmJiYFvfFxMTAYrGgoqKizfMWL14MnU7nvCUmJroqbFmlXVYp5KwQ4ggLERH1cJImLJ988gluvfVWxMfHt3vclaMvoii2ev/lFi1aBL1e77wVFhZ2P2AFuHwTxDPN/VgGsAcLERH1cC5fw+KQn5+PLVu2YM2aNe0eFxsbi5KSkhb3lZWVQaPRICIios3ztFottFrva1XfOzwAPmoBTWYbACDAV42EMH+ZoyIiIpKXZCMsy5cvR3R0NGbOnNnucePGjXNWEjls2rQJo0aNgo+Pj1ThKZZGrUJSRKDz5/TYYKhUbMlPREQ9myQJi81mw/Lly/Hwww9Do2k5iLNo0SLMnTvX+fPjjz+O/Px8LFiwANnZ2fj000/xySefYOHChVKE5hEc00IAW/ITEREBEiUsW7ZsQUFBAebNm3fV74qLi1FQUOD8OTk5GevXr8f27dsxbNgwvPHGG/jggw96ZEmzQ8uEhQtuiYiIJFnDMm3aNOfC2SutWLHiqvsmT56MQ4cOSRGKR3LsKQQwYSEiIgK4l5AicUqIiIioJcmqhKjr0mODcV1SOGJ1ftAF9LyFx0RERFdiwqJAPmoV/vn4OLnDICIiUgxOCREREZHiMWEhIiIixWPCQkRERIrHhIWIiIgUjwkLERERKR4TFiIiIlI8JixERESkeExYiIiISPGYsBAREZHiMWEhIiIixWPCQkRERIrHhIWIiIgUjwkLERERKR4TFiIiIlI8jdwBuIooigAAg8EgcyRERETUUY7PbcfneFu8JmGprKwEACQmJsocCREREXVWbW0tdDpdm7/3moQlPDwcAFBQUNDuE3aF0aNHIysrS9Jr8DpdYzAYkJiYiMLCQoSEhEh6LW/6d3P3tfha4HXcdR1vfB2481ruuI4oihg5ciTi4+PbPc5rEhaVyr4cR6fTSf6iVKvVkl+D1+mekJAQvg4UfC2+Fngdd14H8K7XgTuv5a7r+Pr6Oj/H28JFt13w5JNP8joKvo67eOO/mzc+J3fwtn83b7uOu/BvVdrrCOK1Vrl4CIPBAJ1OB71e77YMl5SHrwNy4GuBAL4OvInXjLBotVq8+uqr0Gq1codCMuLrgBz4WiCArwNv4jUjLEREROS9vGaEhYiIiLwXExYiIiJSPCYsREREpHhMWIiIiEjxFJWw7Ny5E7NmzUJ8fDwEQcDatWtb/L60tBSPPPII4uPjERAQgFtuuQVnzpxpccy5c+dw5513IioqCiEhIbjnnntQWlra4pjq6mo89NBD0Ol00Ol0eOihh1BTUyPxs6OOctfrICkpCYIgtLi98MILUj896qDFixdj9OjRCA4ORnR0NO644w6cOnWqxTGiKOK1115DfHw8/P39ccMNN+DEiRMtjjEajXj66acRGRmJwMBA3H777bhw4UKLY/ieoGzufC3wfUG5FJWw1NfXY+jQofjwww+v+p0oirjjjjtw/vx5fPvttzh8+DD69OmDqVOnor6+3nn+tGnTIAgCfvzxR+zZswcmkwmzZs2CzWZzPtYDDzyAI0eOYMOGDdiwYQOOHDmChx56yG3Pk9rnrtcBALz++usoLi523l566SW3PEe6th07duDJJ5/ETz/9hM2bN8NisWDatGnO/88A8M477+C9997Dhx9+iKysLMTGxuLmm29GbW2t85j58+fjm2++wVdffYXdu3ejrq4Ot912G6xWq/MYvicomztfCwDfFxRLVCgA4jfffOP8+dSpUyIA8fjx4877LBaLGB4eLv79738XRVEUN27cKKpUKlGv1zuPqaqqEgGImzdvFkVRFE+ePCkCEH/66SfnMZmZmSIAMScnR+JnRZ0l1etAFEWxT58+4v/+7/9K/hzINcrKykQA4o4dO0RRFEWbzSbGxsaKb7/9tvOYpqYmUafTicuWLRNFURRrampEHx8f8auvvnIeU1RUJKpUKnHDhg2iKPI9wRNJ9VoQRb4vKJmiRljaYzQaAQB+fn7O+9RqNXx9fbF7927nMYIgtGgQ5OfnB5VK5TwmMzMTOp0OY8aMcR4zduxY6HQ67N271x1PhbrBVa8DhyVLliAiIgLDhg3Dm2++CZPJ5IZnQV2h1+sBXNroNDc3FyUlJZg2bZrzGK1Wi8mTJzv/lg8ePAiz2dzimPj4eAwaNMh5DN8TPI9UrwUHvi8ok8ckLP3790efPn2waNEiVFdXw2Qy4e2330ZJSQmKi4sB2N9kAgMD8fzzz6OhoQH19fV49tlnYbPZnMeUlJQgOjr6qsePjo5GSUmJW58TdZ6rXgcA8Lvf/Q5fffUVtm3bhqeeegpLly7FE088IddTo3aIoogFCxZgwoQJGDRoEAA4/15jYmJaHBsTE+P8XUlJCXx9fREWFtbuMXxP8BxSvhYAvi8omcckLD4+Pli9ejVOnz6N8PBwBAQEYPv27bj11luhVqsBAFFRUfjXv/6F77//HkFBQc79I0aMGOE8BgAEQbjq8UVRbPV+UhZXvg6eeeYZTJ48GUOGDMFjjz2GZcuW4ZNPPkFlZaVcT4/a8NRTT+Hnn3/Gl19+edXvrvy77cjf8pXH8D3Bc0j9WuD7gnJp5A6gM0aOHIkjR45Ar9fDZDIhKioKY8aMwahRo5zHTJs2DefOnUNFRQU0Gg1CQ0MRGxuL5ORkAEBsbOxV1SIAUF5eflV2TsrkitdBa8aOHQsAOHv2LCIiIiR/HtQxTz/9NL777jvs3LkTCQkJzvtjY2MB2L85x8XFOe8vKytz/i3HxsbCZDKhurq6xTfrsrIyjB8/3nkM3xM8g9SvhdbwfUE5PGaE5XI6nQ5RUVE4c+YMDhw4gNmzZ191TGRkJEJDQ/Hjjz+irKwMt99+OwBg3Lhx0Ov12L9/v/PYffv2Qa/Xt/uiJeXpzuugNYcPHwaAFm94JB9RFPHUU09hzZo1+PHHH69KNpOTkxEbG4vNmzc77zOZTNixY4fzb3nkyJHw8fFpcUxxcTGOHz/uPIbvCcrnrtdCa/i+oCByrfZtTW1trXj48GHx8OHDIgDxvffeEw8fPizm5+eLoiiK//znP8Vt27aJ586dE9euXSv26dNHvOuuu1o8xqeffipmZmaKZ8+eFVeuXCmGh4eLCxYsaHHMLbfcIg4ZMkTMzMwUMzMzxcGDB4u33Xab254ntc8dr4O9e/c6H/f8+fPi119/LcbHx4u33367W58rte2///u/RZ1OJ27fvl0sLi523hoaGpzHvP3226JOpxPXrFkjHjt2TLz//vvFuLg40WAwOI95/PHHxYSEBHHLli3ioUOHxJtuukkcOnSoaLFYnMfwPUHZ3PVa4PuCsikqYdm2bZsI4Krbww8/LIqiKL7//vtiQkKC6OPjI/bu3Vt86aWXRKPR2OIxnn/+eTEmJkb08fER+/btK/75z38WbTZbi2MqKyvFBx98UAwODhaDg4PFBx98UKyurnbTs6Rrccfr4ODBg+KYMWNEnU4n+vn5ienp6eKrr74q1tfXu/OpUjtaew0AEJcvX+48xmazia+++qoYGxsrarVacdKkSeKxY8daPE5jY6P41FNPieHh4aK/v7942223iQUFBS2O4XuCsrnrtcD3BWUTRFEU3TeeQ0RERNR5HrmGhYiIiHoWJixERESkeExYiIiISPGYsBAREZHiMWEhIiIixWPCQkRERIrHhIWIiIgUjwkLERERKR4TFiKSzfbt2yEIAmpqauQOhYgUjp1uichtbrjhBgwbNgxLly4FYN+grqqqCjExMRAEQd7giEjRNHIHQEQ9l6+vL2JjY+UOg4g8AKeEiMgtHnnkEezYsQPvv/8+BEGAIAhYsWJFiymhFStWIDQ0FP/5z3+Qnp6OgIAA3H333aivr8dnn32GpKQkhIWF4emnn4bVanU+tslkwnPPPYdevXohMDAQY8aMwfbt2+V5okQkCY6wEJFbvP/++zh9+jQGDRqE119/HQBw4sSJq45raGjABx98gK+++gq1tbW46667cNdddyE0NBTr16/H+fPnMWfOHEyYMAH33nsvAODRRx9FXl4evvrqK8THx+Obb77BLbfcgmPHjqFv375ufZ5EJA0mLETkFjqdDr6+vggICHBOA+Xk5Fx1nNlsxkcffYTU1FQAwN13342VK1eitLQUQUFBGDhwIG688UZs27YN9957L86dO4cvv/wSFy5cQHx8PABg4cKF2LBhA5YvX4633nrLfU+SiCTDhIWIFCUgIMCZrABATEwMkpKSEBQU1OK+srIyAMChQ4cgiiL69evX4nGMRiMiIiLcEzQRSY4JCxEpio+PT4ufBUFo9T6bzQYAsNlsUKvVOHjwINRqdYvjLk9yiMizMWEhIrfx9fVtsVjWFYYPHw6r1YqysjJMnDjRpY9NRMrBKiEicpukpCTs27cPeXl5qKiocI6SdEe/fv3w4IMPYu7cuVizZg1yc3ORlZWFJUuWYP369S6ImoiUgAkLEbnNwoULoVarMXDgQERFRaGgoMAlj7t8+XLMnTsXv//975Geno7bb78d+/btQ2Jioksen4jkx063REREpHgcYSEiIiLFY8JCREREiseEhYiIiBSPCQsREREpHhMWIiIiUjwmLERERKR4TFiIiIhI8ZiwEBERkeIxYSEiIiLFY8JCREREiseEhYiIiBTv/wO6QDhIKor7lwAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_yearly['T_C'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "df_kristineberg['season'] = df_kristineberg.to_xarray()['time.season']\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f3565fe1890>"
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for s in ['MAM','JJA','SON','DJF']:\n",
+    "    df_kristineberg[df_kristineberg['season']==s]['T_C'].plot.hist(alpha=0.5, bins=20, label=s)\n",
+    "    \n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "df = dss.isel(lev=-1)[vl].to_dataframe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>member_id</th>\n",
+       "      <th>dcpp_init_year</th>\n",
+       "      <th>time</th>\n",
+       "      <th>lat</th>\n",
+       "      <th>lon</th>\n",
+       "      <th>mmrso4</th>\n",
+       "      <th>hurs</th>\n",
+       "      <th>tas</th>\n",
+       "      <th>T_C</th>\n",
+       "      <th>lev</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1990-01-15 12:00:00</td>\n",
+       "      <td>-90.0</td>\n",
+       "      <td>-180.00</td>\n",
+       "      <td>2.049096e-11</td>\n",
+       "      <td>98.689842</td>\n",
+       "      <td>242.897797</td>\n",
+       "      <td>-30.252197</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1990-01-15 12:00:00</td>\n",
+       "      <td>-90.0</td>\n",
+       "      <td>-178.75</td>\n",
+       "      <td>2.049095e-11</td>\n",
+       "      <td>98.675537</td>\n",
+       "      <td>242.903198</td>\n",
+       "      <td>-30.246796</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1990-01-15 12:00:00</td>\n",
+       "      <td>-90.0</td>\n",
+       "      <td>-177.50</td>\n",
+       "      <td>2.049095e-11</td>\n",
+       "      <td>98.675537</td>\n",
+       "      <td>242.903198</td>\n",
+       "      <td>-30.246796</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1990-01-15 12:00:00</td>\n",
+       "      <td>-90.0</td>\n",
+       "      <td>-176.25</td>\n",
+       "      <td>2.049095e-11</td>\n",
+       "      <td>98.675537</td>\n",
+       "      <td>242.903198</td>\n",
+       "      <td>-30.246796</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>r1i1p1f1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1990-01-15 12:00:00</td>\n",
+       "      <td>-90.0</td>\n",
+       "      <td>-175.00</td>\n",
+       "      <td>2.049095e-11</td>\n",
+       "      <td>98.675537</td>\n",
+       "      <td>242.903198</td>\n",
+       "      <td>-30.246796</td>\n",
+       "      <td>-992.556095</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  member_id  dcpp_init_year                time   lat     lon        mmrso4  \\\n",
+       "0  r1i1p1f1             NaN 1990-01-15 12:00:00 -90.0 -180.00  2.049096e-11   \n",
+       "1  r1i1p1f1             NaN 1990-01-15 12:00:00 -90.0 -178.75  2.049095e-11   \n",
+       "2  r1i1p1f1             NaN 1990-01-15 12:00:00 -90.0 -177.50  2.049095e-11   \n",
+       "3  r1i1p1f1             NaN 1990-01-15 12:00:00 -90.0 -176.25  2.049095e-11   \n",
+       "4  r1i1p1f1             NaN 1990-01-15 12:00:00 -90.0 -175.00  2.049095e-11   \n",
+       "\n",
+       "        hurs         tas        T_C         lev  \n",
+       "0  98.689842  242.897797 -30.252197 -992.556095  \n",
+       "1  98.675537  242.903198 -30.246796 -992.556095  \n",
+       "2  98.675537  242.903198 -30.246796 -992.556095  \n",
+       "3  98.675537  242.903198 -30.246796 -992.556095  \n",
+       "4  98.675537  242.903198 -30.246796 -992.556095  "
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_ri = df.reset_index()\n",
+    "df_ri.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### lets do something unnecesarily complicated :D "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## qcut, cut"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "qcut splits the data into quantile ranges"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "\n",
+    "\n",
+    "df_ri['hurs_cat'] = pd.qcut(df_ri['hurs'],\n",
+    "                            q=[0.05,0.17, 0.34,0.66, 0.83,0.95],\n",
+    "                            labels=['very low','low','med','high','very high'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Cut cuts into categories"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "df_ri['lat_cat'] = pd.cut(df_ri['lat'], [-90,-60,-30,0,30,60,90], \n",
+    "                          labels=['S polar','S mid','S tropics', 'N tropic', 'N mid','N polar'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_11040/3604578940.py:1: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
+      "  df_ri.groupby('lat_cat').mean()\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_ri.groupby('lat_cat').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "sns.boxenplot(x=\"lat_cat\", y=\"hurs\",\n",
+    "              color=\"b\",\n",
+    "              scale=\"linear\", data=df_ri)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "sns.boxenplot(x=\"hurs_cat\", y=\"mmrso4\",\n",
+    "              color=\"b\",\n",
+    "              scale=\"linear\", data=df_ri,\n",
+    "             )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "sns.displot(x=\"mmrso4\",\n",
+    "            hue='lat_cat',\n",
+    "            log_scale=True,\n",
+    "            kind='kde',\n",
+    "            data=df_ri, \n",
+    "            multiple=\"stack\"\n",
+    "           )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Convert back to xarray if we need:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "ds_new = df_ri.set_index(['time','lat','lon']).to_xarray()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "ds_new"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### mask by category "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "ds_new.where(ds_new['hurs_cat']=='very low').mean(['time','lon'])['mmrso4'].plot(label='very low')#vmin = 0, vmax = 1.5e-8)\n",
+    "ds_new.where(ds_new['hurs_cat']=='low').mean(['time','lon'])['mmrso4'].plot(label='low')#vmin = 0, vmax = 1.5e-8)\n",
+    "\n",
+    "ds_new.where(ds_new['hurs_cat']=='high').mean(['time','lon'])['mmrso4'].plot(label='high')#vmin = 0, vmax = 1.5e-8)\n",
+    "ds_new.where(ds_new['hurs_cat']=='very high').mean(['time','lon'], keep_attrs=True)['mmrso4'].plot(label='very high')#vmin = 0, vmax = 1.5e-8)\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "jupytext": {
+   "text_representation": {
+    "extension": ".py",
+    "format_name": "percent",
+    "format_version": "1.2",
+    "jupytext_version": "1.2.4"
+   }
+  },
+  "kernelspec": {
+   "display_name": "Python [conda env:pangeo-notebook]",
+   "language": "python",
+   "name": "conda-env-pangeo-notebook-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/_sources/learning/us-links.rst b/_sources/learning/us-links.rst
new file mode 100644
index 0000000..9b68ebc
--- /dev/null
+++ b/_sources/learning/us-links.rst
@@ -0,0 +1,34 @@
+Useful links
+============
+
+Some useful links
+~~~~~~~~~~~~~~~~~
+
+- `CodeRefinary Git Intro <https://coderefinery.github.io/git-intro>`_
+- `Pangeo Gallery <https://gallery.pangeo.io/>`_
+- `Intake-ESM <https://intake-esm.readthedocs.io/en/stable/>`_
+- `ACTRIS and EBAS example notebooks <https://github.com/ACTRIS-Data-Centre/actris-jupyter-hub>`_
+
+
+
+
+Documentation links
+~~~~~~~~~~~~~~~~~~~
+
+- `Xarray <https://docs.xarray.dev/en/stable/>`_
+- `Pandas <https://pandas.pydata.org/docs/user_guide/index.html#user-guide>`_
+- `pyaerocom <https://pyaerocom.readthedocs.io/en/latest/>`_
+- `ESEm <https://esem.readthedocs.io/en/latest/>`_
+
+
+
+
+Previous eScience Courses
+=========================
+
+- `2022 <https://pangeo-data.github.io/escience-2022/intro.html>`_
+- `2021 <https://nordicesmhub.github.io/forces-2021/intro.html>`_
+- `2020 <https://nordicesmhub.github.io/forces-2020/intro.html>`_
+- `2019 <https://nordicesmhub.github.io/NEGI-Abisko-2019/>`_
+- `2018 <https://nordicesmhub.github.io/NEGI-Andoya-2018/>`_
+
diff --git a/_sources/license.md b/_sources/license.md
new file mode 100644
index 0000000..e7f032f
--- /dev/null
+++ b/_sources/license.md
@@ -0,0 +1,15 @@
+# Credit
+
+## Sponsors:
+```{image} img/spon_comb_light.png
+:class: only-light
+```
+```{image} img/spon_comb_dark.png
+:class: only-dark
+```
+
+
+This webpage is adapted to eScience-2024's needs from the sphinx-lesson maintained and developed by [CodeRefinery](https://coderefinery.org/), and is Copyright (c) CodeRefinery and, is distributed under the following [license](https://creativecommons.org/licenses/by/4.0/).
+
+The website [template](https://github.com/coderefinery/documentation) is maintained by [CodeRefinery](https://coderefinery.org/)
+and rendered with [sphinx-lesson: structured lessons with Sphinx](https://coderefinery.github.io/sphinx-lesson/).
diff --git a/_sphinx_design_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css b/_sphinx_design_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css
new file mode 100644
index 0000000..eb19f69
--- /dev/null
+++ b/_sphinx_design_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css
@@ -0,0 +1 @@
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diff --git a/_sphinx_design_static/design-tabs.js b/_sphinx_design_static/design-tabs.js
new file mode 100644
index 0000000..36b38cf
--- /dev/null
+++ b/_sphinx_design_static/design-tabs.js
@@ -0,0 +1,27 @@
+var sd_labels_by_text = {};
+
+function ready() {
+  const li = document.getElementsByClassName("sd-tab-label");
+  for (const label of li) {
+    syncId = label.getAttribute("data-sync-id");
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+        sd_labels_by_text[syncId] = [];
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+      sd_labels_by_text[syncId].push(label);
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+}
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+function onLabelClick() {
+  // Activate other inputs with the same sync id.
+  syncId = this.getAttribute("data-sync-id");
+  for (label of sd_labels_by_text[syncId]) {
+    if (label === this) continue;
+    label.previousElementSibling.checked = true;
+  }
+  window.localStorage.setItem("sphinx-design-last-tab", syncId);
+}
+
+document.addEventListener("DOMContentLoaded", ready, false);
diff --git a/_static/basic.css b/_static/basic.css
new file mode 100644
index 0000000..2af6139
--- /dev/null
+++ b/_static/basic.css
@@ -0,0 +1,925 @@
+/*
+ * basic.css
+ * ~~~~~~~~~
+ *
+ * Sphinx stylesheet -- basic theme.
+ *
+ * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+
+/* -- main layout ----------------------------------------------------------- */
+
+div.clearer {
+    clear: both;
+}
+
+div.section::after {
+    display: block;
+    content: '';
+    clear: left;
+}
+
+/* -- relbar ---------------------------------------------------------------- */
+
+div.related {
+    width: 100%;
+    font-size: 90%;
+}
+
+div.related h3 {
+    display: none;
+}
+
+div.related ul {
+    margin: 0;
+    padding: 0 0 0 10px;
+    list-style: none;
+}
+
+div.related li {
+    display: inline;
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+    float: right;
+    margin-right: 5px;
+}
+
+/* -- sidebar --------------------------------------------------------------- */
+
+div.sphinxsidebarwrapper {
+    padding: 10px 5px 0 10px;
+}
+
+div.sphinxsidebar {
+    float: left;
+    width: 270px;
+    margin-left: -100%;
+    font-size: 90%;
+    word-wrap: break-word;
+    overflow-wrap : break-word;
+}
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+div.sphinxsidebar ul {
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+div.sphinxsidebar ul ul,
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+    font-size: 1em;
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+div.sphinxsidebar #searchbox input[type="text"] {
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+    box-sizing: border-box;
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+div.sphinxsidebar #searchbox input[type="submit"] {
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+    width: 20%;
+    border-left: none;
+    padding: 0.25em;
+    box-sizing: border-box;
+}
+
+
+img {
+    border: 0;
+    max-width: 100%;
+}
+
+/* -- search page ----------------------------------------------------------- */
+
+ul.search {
+    margin: 10px 0 0 20px;
+    padding: 0;
+}
+
+ul.search li {
+    padding: 5px 0 5px 20px;
+    background-image: url(file.png);
+    background-repeat: no-repeat;
+    background-position: 0 7px;
+}
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+ul.search li a {
+    font-weight: bold;
+}
+
+ul.search li p.context {
+    color: #888;
+    margin: 2px 0 0 30px;
+    text-align: left;
+}
+
+ul.keywordmatches li.goodmatch a {
+    font-weight: bold;
+}
+
+/* -- index page ------------------------------------------------------------ */
+
+table.contentstable {
+    width: 90%;
+    margin-left: auto;
+    margin-right: auto;
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+
+span.linkdescr {
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+    padding-top: 5px;
+    font-size: 90%;
+}
+
+/* -- general index --------------------------------------------------------- */
+
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+    width: 100%;
+}
+
+table.indextable td {
+    text-align: left;
+    vertical-align: top;
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+img.toggler {
+    margin-right: 3px;
+    margin-top: 3px;
+    cursor: pointer;
+}
+
+div.modindex-jumpbox {
+    border-top: 1px solid #ddd;
+    border-bottom: 1px solid #ddd;
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+    padding: 0.4em;
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+    border-bottom: 1px solid #ddd;
+    margin: 1em 0 1em 0;
+    padding: 0.4em;
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+
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+/* -- sidebars -------------------------------------------------------------- */
+
+div.sidebar,
+aside.sidebar {
+    margin: 0 0 0.5em 1em;
+    border: 1px solid #ddb;
+    padding: 7px;
+    background-color: #ffe;
+    width: 40%;
+    float: right;
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+p.sidebar-title {
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+
+nav.contents,
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+    clear: left;
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+
+/* -- topics ---------------------------------------------------------------- */
+
+nav.contents,
+aside.topic,
+div.topic {
+    border: 1px solid #ccc;
+    padding: 7px;
+    margin: 10px 0 10px 0;
+}
+
+p.topic-title {
+    font-size: 1.1em;
+    font-weight: bold;
+    margin-top: 10px;
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+/* -- admonitions ----------------------------------------------------------- */
+
+div.admonition {
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+div.admonition dt {
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+div.body p.centered {
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+/* -- content of sidebars/topics/admonitions -------------------------------- */
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+    -ms-hyphens: manual;
+    -webkit-hyphens: manual;
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+}
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+div.citation > p:last-of-type {
+    margin-bottom: 0em;
+}
+aside.footnote > p:last-of-type:after,
+div.citation > p:last-of-type:after {
+    content: "";
+    clear: both;
+}
+
+dl.field-list {
+    display: grid;
+    grid-template-columns: fit-content(30%) auto;
+}
+
+dl.field-list > dt {
+    font-weight: bold;
+    word-break: break-word;
+    padding-left: 0.5em;
+    padding-right: 5px;
+}
+
+dl.field-list > dd {
+    padding-left: 0.5em;
+    margin-top: 0em;
+    margin-left: 0em;
+    margin-bottom: 0em;
+}
+
+dl {
+    margin-bottom: 15px;
+}
+
+dd > :first-child {
+    margin-top: 0px;
+}
+
+dd ul, dd table {
+    margin-bottom: 10px;
+}
+
+dd {
+    margin-top: 3px;
+    margin-bottom: 10px;
+    margin-left: 30px;
+}
+
+.sig dd {
+    margin-top: 0px;
+    margin-bottom: 0px;
+}
+
+.sig dl {
+    margin-top: 0px;
+    margin-bottom: 0px;
+}
+
+dl > dd:last-child,
+dl > dd:last-child > :last-child {
+    margin-bottom: 0;
+}
+
+dt:target, span.highlighted {
+    background-color: #fbe54e;
+}
+
+rect.highlighted {
+    fill: #fbe54e;
+}
+
+dl.glossary dt {
+    font-weight: bold;
+    font-size: 1.1em;
+}
+
+.versionmodified {
+    font-style: italic;
+}
+
+.system-message {
+    background-color: #fda;
+    padding: 5px;
+    border: 3px solid red;
+}
+
+.footnote:target  {
+    background-color: #ffa;
+}
+
+.line-block {
+    display: block;
+    margin-top: 1em;
+    margin-bottom: 1em;
+}
+
+.line-block .line-block {
+    margin-top: 0;
+    margin-bottom: 0;
+    margin-left: 1.5em;
+}
+
+.guilabel, .menuselection {
+    font-family: sans-serif;
+}
+
+.accelerator {
+    text-decoration: underline;
+}
+
+.classifier {
+    font-style: oblique;
+}
+
+.classifier:before {
+    font-style: normal;
+    margin: 0 0.5em;
+    content: ":";
+    display: inline-block;
+}
+
+abbr, acronym {
+    border-bottom: dotted 1px;
+    cursor: help;
+}
+
+.translated {
+    background-color: rgba(207, 255, 207, 0.2)
+}
+
+.untranslated {
+    background-color: rgba(255, 207, 207, 0.2)
+}
+
+/* -- code displays --------------------------------------------------------- */
+
+pre {
+    overflow: auto;
+    overflow-y: hidden;  /* fixes display issues on Chrome browsers */
+}
+
+pre, div[class*="highlight-"] {
+    clear: both;
+}
+
+span.pre {
+    -moz-hyphens: none;
+    -ms-hyphens: none;
+    -webkit-hyphens: none;
+    hyphens: none;
+    white-space: nowrap;
+}
+
+div[class*="highlight-"] {
+    margin: 1em 0;
+}
+
+td.linenos pre {
+    border: 0;
+    background-color: transparent;
+    color: #aaa;
+}
+
+table.highlighttable {
+    display: block;
+}
+
+table.highlighttable tbody {
+    display: block;
+}
+
+table.highlighttable tr {
+    display: flex;
+}
+
+table.highlighttable td {
+    margin: 0;
+    padding: 0;
+}
+
+table.highlighttable td.linenos {
+    padding-right: 0.5em;
+}
+
+table.highlighttable td.code {
+    flex: 1;
+    overflow: hidden;
+}
+
+.highlight .hll {
+    display: block;
+}
+
+div.highlight pre,
+table.highlighttable pre {
+    margin: 0;
+}
+
+div.code-block-caption + div {
+    margin-top: 0;
+}
+
+div.code-block-caption {
+    margin-top: 1em;
+    padding: 2px 5px;
+    font-size: small;
+}
+
+div.code-block-caption code {
+    background-color: transparent;
+}
+
+table.highlighttable td.linenos,
+span.linenos,
+div.highlight span.gp {  /* gp: Generic.Prompt */
+  user-select: none;
+  -webkit-user-select: text; /* Safari fallback only */
+  -webkit-user-select: none; /* Chrome/Safari */
+  -moz-user-select: none; /* Firefox */
+  -ms-user-select: none; /* IE10+ */
+}
+
+div.code-block-caption span.caption-number {
+    padding: 0.1em 0.3em;
+    font-style: italic;
+}
+
+div.code-block-caption span.caption-text {
+}
+
+div.literal-block-wrapper {
+    margin: 1em 0;
+}
+
+code.xref, a code {
+    background-color: transparent;
+    font-weight: bold;
+}
+
+h1 code, h2 code, h3 code, h4 code, h5 code, h6 code {
+    background-color: transparent;
+}
+
+.viewcode-link {
+    float: right;
+}
+
+.viewcode-back {
+    float: right;
+    font-family: sans-serif;
+}
+
+div.viewcode-block:target {
+    margin: -1px -10px;
+    padding: 0 10px;
+}
+
+/* -- math display ---------------------------------------------------------- */
+
+img.math {
+    vertical-align: middle;
+}
+
+div.body div.math p {
+    text-align: center;
+}
+
+span.eqno {
+    float: right;
+}
+
+span.eqno a.headerlink {
+    position: absolute;
+    z-index: 1;
+}
+
+div.math:hover a.headerlink {
+    visibility: visible;
+}
+
+/* -- printout stylesheet --------------------------------------------------- */
+
+@media print {
+    div.document,
+    div.documentwrapper,
+    div.bodywrapper {
+        margin: 0 !important;
+        width: 100%;
+    }
+
+    div.sphinxsidebar,
+    div.related,
+    div.footer,
+    #top-link {
+        display: none;
+    }
+}
\ No newline at end of file
diff --git a/_static/check-solid.svg b/_static/check-solid.svg
new file mode 100644
index 0000000..92fad4b
--- /dev/null
+++ b/_static/check-solid.svg
@@ -0,0 +1,4 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-check" width="44" height="44" viewBox="0 0 24 24" stroke-width="2" stroke="#22863a" fill="none" stroke-linecap="round" stroke-linejoin="round">
+  <path stroke="none" d="M0 0h24v24H0z" fill="none"/>
+  <path d="M5 12l5 5l10 -10" />
+</svg>
diff --git a/_static/clipboard.min.js b/_static/clipboard.min.js
new file mode 100644
index 0000000..54b3c46
--- /dev/null
+++ b/_static/clipboard.min.js
@@ -0,0 +1,7 @@
+/*!
+ * clipboard.js v2.0.8
+ * https://clipboardjs.com/
+ *
+ * Licensed MIT © Zeno Rocha
+ */
+!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return o}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),c=n.n(e);function a(t){try{return document.execCommand(t)}catch(t){return}}var f=function(t){t=c()(t);return a("cut"),t};var l=function(t){var e,n,o,r=1<arguments.length&&void 0!==arguments[1]?arguments[1]:{container:document.body},i="";return"string"==typeof t?(e=t,n="rtl"===document.documentElement.getAttribute("dir"),(o=document.createElement("textarea")).style.fontSize="12pt",o.style.border="0",o.style.padding="0",o.style.margin="0",o.style.position="absolute",o.style[n?"right":"left"]="-9999px",n=window.pageYOffset||document.documentElement.scrollTop,o.style.top="".concat(n,"px"),o.setAttribute("readonly",""),o.value=e,o=o,r.container.appendChild(o),i=c()(o),a("copy"),o.remove()):(i=c()(t),a("copy")),i};function r(t){return(r="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}var s=function(){var t=0<arguments.length&&void 0!==arguments[0]?arguments[0]:{},e=t.action,n=void 0===e?"copy":e,o=t.container,e=t.target,t=t.text;if("copy"!==n&&"cut"!==n)throw new Error('Invalid "action" value, use either "copy" or "cut"');if(void 0!==e){if(!e||"object"!==r(e)||1!==e.nodeType)throw new Error('Invalid "target" value, use a valid Element');if("copy"===n&&e.hasAttribute("disabled"))throw new Error('Invalid "target" attribute. 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You can\'t cut text from elements with "readonly" or "disabled" attributes')}return t?l(t,{container:o}):e?"cut"===n?f(e):l(e,{container:o}):void 0};function d(t){return(d="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}function p(t,e){for(var n=0;n<e.length;n++){var o=e[n];o.enumerable=o.enumerable||!1,o.configurable=!0,"value"in o&&(o.writable=!0),Object.defineProperty(t,o.key,o)}}function y(t,e){return(y=Object.setPrototypeOf||function(t,e){return t.__proto__=e,t})(t,e)}function h(n){var o=function(){if("undefined"==typeof Reflect||!Reflect.construct)return!1;if(Reflect.construct.sham)return!1;if("function"==typeof Proxy)return!0;try{return Date.prototype.toString.call(Reflect.construct(Date,[],function(){})),!0}catch(t){return!1}}();return function(){var t,e=m(n);return t=o?(t=m(this).constructor,Reflect.construct(e,arguments,t)):e.apply(this,arguments),e=this,!(t=t)||"object"!==d(t)&&"function"!=typeof t?function(t){if(void 0!==t)return t;throw new ReferenceError("this hasn't been initialised - super() hasn't been called")}(e):t}}function m(t){return(m=Object.setPrototypeOf?Object.getPrototypeOf:function(t){return t.__proto__||Object.getPrototypeOf(t)})(t)}function v(t,e){t="data-clipboard-".concat(t);if(e.hasAttribute(t))return e.getAttribute(t)}var o=function(){!function(t,e){if("function"!=typeof e&&null!==e)throw new TypeError("Super expression must either be null or a function");t.prototype=Object.create(e&&e.prototype,{constructor:{value:t,writable:!0,configurable:!0}}),e&&y(t,e)}(r,i());var t,e,n,o=h(r);function r(t,e){var n;return function(t){if(!(t instanceof r))throw new TypeError("Cannot call a class as a function")}(this),(n=o.call(this)).resolveOptions(e),n.listenClick(t),n}return t=r,n=[{key:"copy",value:function(t){var 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e=t.delegateTarget||t.currentTarget,t=s({action:this.action(e),container:this.container,target:this.target(e),text:this.text(e)});this.emit(t?"success":"error",{action:this.action,text:t,trigger:e,clearSelection:function(){e&&e.focus(),document.activeElement.blur(),window.getSelection().removeAllRanges()}})}},{key:"defaultAction",value:function(t){return v("action",t)}},{key:"defaultTarget",value:function(t){t=v("target",t);if(t)return document.querySelector(t)}},{key:"defaultText",value:function(t){return v("text",t)}},{key:"destroy",value:function(){this.listener.destroy()}}])&&p(t.prototype,e),n&&p(t,n),r}()},828:function(t){var e;"undefined"==typeof Element||Element.prototype.matches||((e=Element.prototype).matches=e.matchesSelector||e.mozMatchesSelector||e.msMatchesSelector||e.oMatchesSelector||e.webkitMatchesSelector),t.exports=function(t,e){for(;t&&9!==t.nodeType;){if("function"==typeof t.matches&&t.matches(e))return t;t=t.parentNode}}},438:function(t,e,n){var u=n(828);function 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f=n(879),l=n(438);t.exports=function(t,e,n){if(!t&&!e&&!n)throw new Error("Missing required arguments");if(!f.string(e))throw new TypeError("Second argument must be a String");if(!f.fn(n))throw new TypeError("Third argument must be a Function");if(f.node(t))return c=e,a=n,(u=t).addEventListener(c,a),{destroy:function(){u.removeEventListener(c,a)}};if(f.nodeList(t))return o=t,r=e,i=n,Array.prototype.forEach.call(o,function(t){t.addEventListener(r,i)}),{destroy:function(){Array.prototype.forEach.call(o,function(t){t.removeEventListener(r,i)})}};if(f.string(t))return t=t,e=e,n=n,l(document.body,t,e,n);throw new TypeError("First argument must be a String, HTMLElement, HTMLCollection, or NodeList");var o,r,i,u,c,a}},817:function(t){t.exports=function(t){var e,n="SELECT"===t.nodeName?(t.focus(),t.value):"INPUT"===t.nodeName||"TEXTAREA"===t.nodeName?((e=t.hasAttribute("readonly"))||t.setAttribute("readonly",""),t.select(),t.setSelectionRange(0,t.value.length),e||t.removeAttribute("readonly"),t.value):(t.hasAttribute("contenteditable")&&t.focus(),n=window.getSelection(),(e=document.createRange()).selectNodeContents(t),n.removeAllRanges(),n.addRange(e),n.toString());return n}},279:function(t){function e(){}e.prototype={on:function(t,e,n){var o=this.e||(this.e={});return(o[t]||(o[t]=[])).push({fn:e,ctx:n}),this},once:function(t,e,n){var o=this;function r(){o.off(t,r),e.apply(n,arguments)}return r._=e,this.on(t,r,n)},emit:function(t){for(var e=[].slice.call(arguments,1),n=((this.e||(this.e={}))[t]||[]).slice(),o=0,r=n.length;o<r;o++)n[o].fn.apply(n[o].ctx,e);return this},off:function(t,e){var n=this.e||(this.e={}),o=n[t],r=[];if(o&&e)for(var i=0,u=o.length;i<u;i++)o[i].fn!==e&&o[i].fn._!==e&&r.push(o[i]);return r.length?n[t]=r:delete n[t],this}},t.exports=e,t.exports.TinyEmitter=e}},r={},o.n=function(t){var e=t&&t.__esModule?function(){return t.default}:function(){return t};return o.d(e,{a:e}),e},o.d=function(t,e){for(var n in e)o.o(e,n)&&!o.o(t,n)&&Object.defineProperty(t,n,{enumerable:!0,get:e[n]})},o.o=function(t,e){return Object.prototype.hasOwnProperty.call(t,e)},o(686).default;function o(t){if(r[t])return r[t].exports;var e=r[t]={exports:{}};return n[t](e,e.exports,o),e.exports}var n,r});
\ No newline at end of file
diff --git a/_static/copy-button.svg b/_static/copy-button.svg
new file mode 100644
index 0000000..9c074da
--- /dev/null
+++ b/_static/copy-button.svg
@@ -0,0 +1,5 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-copy" width="44" height="44" viewBox="0 0 24 24" stroke-width="1.5" stroke="#000000" fill="none" stroke-linecap="round" stroke-linejoin="round">
+  <path stroke="none" d="M0 0h24v24H0z" fill="none"/>
+  <rect x="8" y="8" width="12" height="12" rx="2" />
+  <path d="M16 8v-2a2 2 0 0 0 -2 -2h-8a2 2 0 0 0 -2 2v8a2 2 0 0 0 2 2h2" />
+</svg>
diff --git a/_static/copybutton.css b/_static/copybutton.css
new file mode 100644
index 0000000..f1916ec
--- /dev/null
+++ b/_static/copybutton.css
@@ -0,0 +1,94 @@
+/* Copy buttons */
+button.copybtn {
+    position: absolute;
+    display: flex;
+    top: .3em;
+    right: .3em;
+    width: 1.7em;
+    height: 1.7em;
+	opacity: 0;
+    transition: opacity 0.3s, border .3s, background-color .3s;
+    user-select: none;
+    padding: 0;
+    border: none;
+    outline: none;
+    border-radius: 0.4em;
+    /* The colors that GitHub uses */
+    border: #1b1f2426 1px solid;
+    background-color: #f6f8fa;
+    color: #57606a;
+}
+
+button.copybtn.success {
+    border-color: #22863a;
+    color: #22863a;
+}
+
+button.copybtn svg {
+    stroke: currentColor;
+    width: 1.5em;
+    height: 1.5em;
+    padding: 0.1em;
+}
+
+div.highlight  {
+    position: relative;
+}
+
+/* Show the copybutton */
+.highlight:hover button.copybtn, button.copybtn.success {
+	opacity: 1;
+}
+
+.highlight button.copybtn:hover {
+    background-color: rgb(235, 235, 235);
+}
+
+.highlight button.copybtn:active {
+    background-color: rgb(187, 187, 187);
+}
+
+/**
+ * A minimal CSS-only tooltip copied from:
+ *   https://codepen.io/mildrenben/pen/rVBrpK
+ *
+ * To use, write HTML like the following:
+ *
+ * <p class="o-tooltip--left" data-tooltip="Hey">Short</p>
+ */
+ .o-tooltip--left {
+  position: relative;
+ }
+
+ .o-tooltip--left:after {
+    opacity: 0;
+    visibility: hidden;
+    position: absolute;
+    content: attr(data-tooltip);
+    padding: .2em;
+    font-size: .8em;
+    left: -.2em;
+    background: grey;
+    color: white;
+    white-space: nowrap;
+    z-index: 2;
+    border-radius: 2px;
+    transform: translateX(-102%) translateY(0);
+    transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1);
+}
+
+.o-tooltip--left:hover:after {
+    display: block;
+    opacity: 1;
+    visibility: visible;
+    transform: translateX(-100%) translateY(0);
+    transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1);
+    transition-delay: .5s;
+}
+
+/* By default the copy button shouldn't show up when printing a page */
+@media print {
+    button.copybtn {
+        display: none;
+    }
+}
diff --git a/_static/copybutton.js b/_static/copybutton.js
new file mode 100644
index 0000000..2ea7ff3
--- /dev/null
+++ b/_static/copybutton.js
@@ -0,0 +1,248 @@
+// Localization support
+const messages = {
+  'en': {
+    'copy': 'Copy',
+    'copy_to_clipboard': 'Copy to clipboard',
+    'copy_success': 'Copied!',
+    'copy_failure': 'Failed to copy',
+  },
+  'es' : {
+    'copy': 'Copiar',
+    'copy_to_clipboard': 'Copiar al portapapeles',
+    'copy_success': '¡Copiado!',
+    'copy_failure': 'Error al copiar',
+  },
+  'de' : {
+    'copy': 'Kopieren',
+    'copy_to_clipboard': 'In die Zwischenablage kopieren',
+    'copy_success': 'Kopiert!',
+    'copy_failure': 'Fehler beim Kopieren',
+  },
+  'fr' : {
+    'copy': 'Copier',
+    'copy_to_clipboard': 'Copier dans le presse-papier',
+    'copy_success': 'Copié !',
+    'copy_failure': 'Échec de la copie',
+  },
+  'ru': {
+    'copy': 'Скопировать',
+    'copy_to_clipboard': 'Скопировать в буфер',
+    'copy_success': 'Скопировано!',
+    'copy_failure': 'Не удалось скопировать',
+  },
+  'zh-CN': {
+    'copy': '复制',
+    'copy_to_clipboard': '复制到剪贴板',
+    'copy_success': '复制成功!',
+    'copy_failure': '复制失败',
+  },
+  'it' : {
+    'copy': 'Copiare',
+    'copy_to_clipboard': 'Copiato negli appunti',
+    'copy_success': 'Copiato!',
+    'copy_failure': 'Errore durante la copia',
+  }
+}
+
+let locale = 'en'
+if( document.documentElement.lang !== undefined
+    && messages[document.documentElement.lang] !== undefined ) {
+  locale = document.documentElement.lang
+}
+
+let doc_url_root = DOCUMENTATION_OPTIONS.URL_ROOT;
+if (doc_url_root == '#') {
+    doc_url_root = '';
+}
+
+/**
+ * SVG files for our copy buttons
+ */
+let iconCheck = `<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-check" width="44" height="44" viewBox="0 0 24 24" stroke-width="2" stroke="#22863a" fill="none" stroke-linecap="round" stroke-linejoin="round">
+  <title>${messages[locale]['copy_success']}</title>
+  <path stroke="none" d="M0 0h24v24H0z" fill="none"/>
+  <path d="M5 12l5 5l10 -10" />
+</svg>`
+
+// If the user specified their own SVG use that, otherwise use the default
+let iconCopy = ``;
+if (!iconCopy) {
+  iconCopy = `<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-copy" width="44" height="44" viewBox="0 0 24 24" stroke-width="1.5" stroke="#000000" fill="none" stroke-linecap="round" stroke-linejoin="round">
+  <title>${messages[locale]['copy_to_clipboard']}</title>
+  <path stroke="none" d="M0 0h24v24H0z" fill="none"/>
+  <rect x="8" y="8" width="12" height="12" rx="2" />
+  <path d="M16 8v-2a2 2 0 0 0 -2 -2h-8a2 2 0 0 0 -2 2v8a2 2 0 0 0 2 2h2" />
+</svg>`
+}
+
+/**
+ * Set up copy/paste for code blocks
+ */
+
+const runWhenDOMLoaded = cb => {
+  if (document.readyState != 'loading') {
+    cb()
+  } else if (document.addEventListener) {
+    document.addEventListener('DOMContentLoaded', cb)
+  } else {
+    document.attachEvent('onreadystatechange', function() {
+      if (document.readyState == 'complete') cb()
+    })
+  }
+}
+
+const codeCellId = index => `codecell${index}`
+
+// Clears selected text since ClipboardJS will select the text when copying
+const clearSelection = () => {
+  if (window.getSelection) {
+    window.getSelection().removeAllRanges()
+  } else if (document.selection) {
+    document.selection.empty()
+  }
+}
+
+// Changes tooltip text for a moment, then changes it back
+// We want the timeout of our `success` class to be a bit shorter than the
+// tooltip and icon change, so that we can hide the icon before changing back.
+var timeoutIcon = 2000;
+var timeoutSuccessClass = 1500;
+
+const temporarilyChangeTooltip = (el, oldText, newText) => {
+  el.setAttribute('data-tooltip', newText)
+  el.classList.add('success')
+  // Remove success a little bit sooner than we change the tooltip
+  // So that we can use CSS to hide the copybutton first
+  setTimeout(() => el.classList.remove('success'), timeoutSuccessClass)
+  setTimeout(() => el.setAttribute('data-tooltip', oldText), timeoutIcon)
+}
+
+// Changes the copy button icon for two seconds, then changes it back
+const temporarilyChangeIcon = (el) => {
+  el.innerHTML = iconCheck;
+  setTimeout(() => {el.innerHTML = iconCopy}, timeoutIcon)
+}
+
+const addCopyButtonToCodeCells = () => {
+  // If ClipboardJS hasn't loaded, wait a bit and try again. This
+  // happens because we load ClipboardJS asynchronously.
+  if (window.ClipboardJS === undefined) {
+    setTimeout(addCopyButtonToCodeCells, 250)
+    return
+  }
+
+  // Add copybuttons to all of our code cells
+  const COPYBUTTON_SELECTOR = 'div.highlight pre';
+  const codeCells = document.querySelectorAll(COPYBUTTON_SELECTOR)
+  codeCells.forEach((codeCell, index) => {
+    const id = codeCellId(index)
+    codeCell.setAttribute('id', id)
+
+    const clipboardButton = id =>
+    `<button class="copybtn o-tooltip--left" data-tooltip="${messages[locale]['copy']}" data-clipboard-target="#${id}">
+      ${iconCopy}
+    </button>`
+    codeCell.insertAdjacentHTML('afterend', clipboardButton(id))
+  })
+
+function escapeRegExp(string) {
+    return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string
+}
+
+/**
+ * Removes excluded text from a Node.
+ *
+ * @param {Node} target Node to filter.
+ * @param {string} exclude CSS selector of nodes to exclude.
+ * @returns {DOMString} Text from `target` with text removed.
+ */
+function filterText(target, exclude) {
+    const clone = target.cloneNode(true);  // clone as to not modify the live DOM
+    if (exclude) {
+        // remove excluded nodes
+        clone.querySelectorAll(exclude).forEach(node => node.remove());
+    }
+    return clone.innerText;
+}
+
+// Callback when a copy button is clicked. Will be passed the node that was clicked
+// should then grab the text and replace pieces of text that shouldn't be used in output
+function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") {
+    var regexp;
+    var match;
+
+    // Do we check for line continuation characters and "HERE-documents"?
+    var useLineCont = !!lineContinuationChar
+    var useHereDoc = !!hereDocDelim
+
+    // create regexp to capture prompt and remaining line
+    if (isRegexp) {
+        regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)')
+    } else {
+        regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)')
+    }
+
+    const outputLines = [];
+    var promptFound = false;
+    var gotLineCont = false;
+    var gotHereDoc = false;
+    const lineGotPrompt = [];
+    for (const line of textContent.split('\n')) {
+        match = line.match(regexp)
+        if (match || gotLineCont || gotHereDoc) {
+            promptFound = regexp.test(line)
+            lineGotPrompt.push(promptFound)
+            if (removePrompts && promptFound) {
+                outputLines.push(match[2])
+            } else {
+                outputLines.push(line)
+            }
+            gotLineCont = line.endsWith(lineContinuationChar) & useLineCont
+            if (line.includes(hereDocDelim) & useHereDoc)
+                gotHereDoc = !gotHereDoc
+        } else if (!onlyCopyPromptLines) {
+            outputLines.push(line)
+        } else if (copyEmptyLines && line.trim() === '') {
+            outputLines.push(line)
+        }
+    }
+
+    // If no lines with the prompt were found then just use original lines
+    if (lineGotPrompt.some(v => v === true)) {
+        textContent = outputLines.join('\n');
+    }
+
+    // Remove a trailing newline to avoid auto-running when pasting
+    if (textContent.endsWith("\n")) {
+        textContent = textContent.slice(0, -1)
+    }
+    return textContent
+}
+
+
+var copyTargetText = (trigger) => {
+  var target = document.querySelector(trigger.attributes['data-clipboard-target'].value);
+
+  // get filtered text
+  let exclude = '.linenos';
+
+  let text = filterText(target, exclude);
+  return formatCopyText(text, '', false, true, true, true, '', '')
+}
+
+  // Initialize with a callback so we can modify the text before copy
+  const clipboard = new ClipboardJS('.copybtn', {text: copyTargetText})
+
+  // Update UI with error/success messages
+  clipboard.on('success', event => {
+    clearSelection()
+    temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_success'])
+    temporarilyChangeIcon(event.trigger)
+  })
+
+  clipboard.on('error', event => {
+    temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_failure'])
+  })
+}
+
+runWhenDOMLoaded(addCopyButtonToCodeCells)
\ No newline at end of file
diff --git a/_static/copybutton_funcs.js b/_static/copybutton_funcs.js
new file mode 100644
index 0000000..dbe1aaa
--- /dev/null
+++ b/_static/copybutton_funcs.js
@@ -0,0 +1,73 @@
+function escapeRegExp(string) {
+    return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string
+}
+
+/**
+ * Removes excluded text from a Node.
+ *
+ * @param {Node} target Node to filter.
+ * @param {string} exclude CSS selector of nodes to exclude.
+ * @returns {DOMString} Text from `target` with text removed.
+ */
+export function filterText(target, exclude) {
+    const clone = target.cloneNode(true);  // clone as to not modify the live DOM
+    if (exclude) {
+        // remove excluded nodes
+        clone.querySelectorAll(exclude).forEach(node => node.remove());
+    }
+    return clone.innerText;
+}
+
+// Callback when a copy button is clicked. Will be passed the node that was clicked
+// should then grab the text and replace pieces of text that shouldn't be used in output
+export function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") {
+    var regexp;
+    var match;
+
+    // Do we check for line continuation characters and "HERE-documents"?
+    var useLineCont = !!lineContinuationChar
+    var useHereDoc = !!hereDocDelim
+
+    // create regexp to capture prompt and remaining line
+    if (isRegexp) {
+        regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)')
+    } else {
+        regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)')
+    }
+
+    const outputLines = [];
+    var promptFound = false;
+    var gotLineCont = false;
+    var gotHereDoc = false;
+    const lineGotPrompt = [];
+    for (const line of textContent.split('\n')) {
+        match = line.match(regexp)
+        if (match || gotLineCont || gotHereDoc) {
+            promptFound = regexp.test(line)
+            lineGotPrompt.push(promptFound)
+            if (removePrompts && promptFound) {
+                outputLines.push(match[2])
+            } else {
+                outputLines.push(line)
+            }
+            gotLineCont = line.endsWith(lineContinuationChar) & useLineCont
+            if (line.includes(hereDocDelim) & useHereDoc)
+                gotHereDoc = !gotHereDoc
+        } else if (!onlyCopyPromptLines) {
+            outputLines.push(line)
+        } else if (copyEmptyLines && line.trim() === '') {
+            outputLines.push(line)
+        }
+    }
+
+    // If no lines with the prompt were found then just use original lines
+    if (lineGotPrompt.some(v => v === true)) {
+        textContent = outputLines.join('\n');
+    }
+
+    // Remove a trailing newline to avoid auto-running when pasting
+    if (textContent.endsWith("\n")) {
+        textContent = textContent.slice(0, -1)
+    }
+    return textContent
+}
diff --git a/_static/css/sphinx-toolbox.css b/_static/css/sphinx-toolbox.css
new file mode 100644
index 0000000..58a349a
--- /dev/null
+++ b/_static/css/sphinx-toolbox.css
@@ -0,0 +1,74 @@
+p.source-link {
+	margin-bottom: 0
+}
+
+p.source-link + hr.docutils {
+	margin-top: 10px
+}
+
+p.sphinx-toolbox-extensions, div.sphinx-toolbox-extensions.highlight-python, div.sphinx-toolbox-extensions.highlight-python div.highlight {
+	margin-bottom: 10px
+}
+
+div.rest-example.docutils.container {
+	padding-left: 5px;
+	border-style: dotted;
+	border-width: 1px;
+	border-color: darkgray
+}
+
+div[id*="installation"] .sphinx-tabs-tab {
+	color: #2980b9
+}
+
+button.sphinx-tabs-tab, div.sphinx-tabs-panel {
+	outline: None !important
+}
+
+.table-wrapper td p img.sphinx_toolbox_shield {
+	vertical-align: middle
+}
+
+span.regex_literal {
+	color: dimgrey
+}
+
+span.regex_at {
+	color: orangered
+}
+
+span.regex_repeat_brace {
+	color: orangered
+}
+
+span.regex_branch {
+	color: orangered
+}
+
+span.regex_subpattern {
+	color: dodgerblue
+}
+
+span.regex_in {
+	color: darkorange
+}
+
+span.regex_category {
+	color: darkseagreen
+}
+
+span.regex_repeat {
+	color: orangered
+}
+
+span.regex_any {
+	color: orangered
+}
+
+code.regex {
+	font-size: 80%
+}
+
+span.regex {
+	font-weight: bold
+}
diff --git a/_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css b/_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css
new file mode 100644
index 0000000..eb19f69
--- /dev/null
+++ b/_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css
@@ -0,0 +1 @@
+.sd-bg-primary{background-color:var(--sd-color-primary) !important}.sd-bg-text-primary{color:var(--sd-color-primary-text) !important}button.sd-bg-primary:focus,button.sd-bg-primary:hover{background-color:var(--sd-color-primary-highlight) !important}a.sd-bg-primary:focus,a.sd-bg-primary:hover{background-color:var(--sd-color-primary-highlight) !important}.sd-bg-secondary{background-color:var(--sd-color-secondary) !important}.sd-bg-text-secondary{color:var(--sd-color-secondary-text) !important}button.sd-bg-secondary:focus,button.sd-bg-secondary:hover{background-color:var(--sd-color-secondary-highlight) !important}a.sd-bg-secondary:focus,a.sd-bg-secondary:hover{background-color:var(--sd-color-secondary-highlight) !important}.sd-bg-success{background-color:var(--sd-color-success) !important}.sd-bg-text-success{color:var(--sd-color-success-text) !important}button.sd-bg-success:focus,button.sd-bg-success:hover{background-color:var(--sd-color-success-highlight) !important}a.sd-bg-success:focus,a.sd-bg-success:hover{background-color:var(--sd-color-success-highlight) !important}.sd-bg-info{background-color:var(--sd-color-info) !important}.sd-bg-text-info{color:var(--sd-color-info-text) !important}button.sd-bg-info:focus,button.sd-bg-info:hover{background-color:var(--sd-color-info-highlight) !important}a.sd-bg-info:focus,a.sd-bg-info:hover{background-color:var(--sd-color-info-highlight) !important}.sd-bg-warning{background-color:var(--sd-color-warning) !important}.sd-bg-text-warning{color:var(--sd-color-warning-text) !important}button.sd-bg-warning:focus,button.sd-bg-warning:hover{background-color:var(--sd-color-warning-highlight) !important}a.sd-bg-warning:focus,a.sd-bg-warning:hover{background-color:var(--sd-color-warning-highlight) !important}.sd-bg-danger{background-color:var(--sd-color-danger) !important}.sd-bg-text-danger{color:var(--sd-color-danger-text) !important}button.sd-bg-danger:focus,button.sd-bg-danger:hover{background-color:var(--sd-color-danger-highlight) !important}a.sd-bg-danger:focus,a.sd-bg-danger:hover{background-color:var(--sd-color-danger-highlight) !important}.sd-bg-light{background-color:var(--sd-color-light) !important}.sd-bg-text-light{color:var(--sd-color-light-text) !important}button.sd-bg-light:focus,button.sd-bg-light:hover{background-color:var(--sd-color-light-highlight) !important}a.sd-bg-light:focus,a.sd-bg-light:hover{background-color:var(--sd-color-light-highlight) !important}.sd-bg-muted{background-color:var(--sd-color-muted) !important}.sd-bg-text-muted{color:var(--sd-color-muted-text) !important}button.sd-bg-muted:focus,button.sd-bg-muted:hover{background-color:var(--sd-color-muted-highlight) !important}a.sd-bg-muted:focus,a.sd-bg-muted:hover{background-color:var(--sd-color-muted-highlight) !important}.sd-bg-dark{background-color:var(--sd-color-dark) 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!important}.sd-text-primary,.sd-text-primary>p{color:var(--sd-color-primary) !important}a.sd-text-primary:focus,a.sd-text-primary:hover{color:var(--sd-color-primary-highlight) !important}.sd-text-secondary,.sd-text-secondary>p{color:var(--sd-color-secondary) !important}a.sd-text-secondary:focus,a.sd-text-secondary:hover{color:var(--sd-color-secondary-highlight) !important}.sd-text-success,.sd-text-success>p{color:var(--sd-color-success) !important}a.sd-text-success:focus,a.sd-text-success:hover{color:var(--sd-color-success-highlight) !important}.sd-text-info,.sd-text-info>p{color:var(--sd-color-info) !important}a.sd-text-info:focus,a.sd-text-info:hover{color:var(--sd-color-info-highlight) !important}.sd-text-warning,.sd-text-warning>p{color:var(--sd-color-warning) !important}a.sd-text-warning:focus,a.sd-text-warning:hover{color:var(--sd-color-warning-highlight) !important}.sd-text-danger,.sd-text-danger>p{color:var(--sd-color-danger) !important}a.sd-text-danger:focus,a.sd-text-danger:hover{color:var(--sd-color-danger-highlight) !important}.sd-text-light,.sd-text-light>p{color:var(--sd-color-light) !important}a.sd-text-light:focus,a.sd-text-light:hover{color:var(--sd-color-light-highlight) !important}.sd-text-muted,.sd-text-muted>p{color:var(--sd-color-muted) !important}a.sd-text-muted:focus,a.sd-text-muted:hover{color:var(--sd-color-muted-highlight) !important}.sd-text-dark,.sd-text-dark>p{color:var(--sd-color-dark) !important}a.sd-text-dark:focus,a.sd-text-dark:hover{color:var(--sd-color-dark-highlight) !important}.sd-text-black,.sd-text-black>p{color:var(--sd-color-black) !important}a.sd-text-black:focus,a.sd-text-black:hover{color:var(--sd-color-black-highlight) !important}.sd-text-white,.sd-text-white>p{color:var(--sd-color-white) !important}a.sd-text-white:focus,a.sd-text-white:hover{color:var(--sd-color-white-highlight) !important}.sd-outline-primary{border-color:var(--sd-color-primary) !important;border-style:solid !important;border-width:1px !important}a.sd-outline-primary:focus,a.sd-outline-primary:hover{border-color:var(--sd-color-primary-highlight) !important}.sd-outline-secondary{border-color:var(--sd-color-secondary) !important;border-style:solid !important;border-width:1px !important}a.sd-outline-secondary:focus,a.sd-outline-secondary:hover{border-color:var(--sd-color-secondary-highlight) !important}.sd-outline-success{border-color:var(--sd-color-success) !important;border-style:solid !important;border-width:1px !important}a.sd-outline-success:focus,a.sd-outline-success:hover{border-color:var(--sd-color-success-highlight) !important}.sd-outline-info{border-color:var(--sd-color-info) !important;border-style:solid !important;border-width:1px !important}a.sd-outline-info:focus,a.sd-outline-info:hover{border-color:var(--sd-color-info-highlight) !important}.sd-outline-warning{border-color:var(--sd-color-warning) !important;border-style:solid !important;border-width:1px !important}a.sd-outline-warning:focus,a.sd-outline-warning:hover{border-color:var(--sd-color-warning-highlight) !important}.sd-outline-danger{border-color:var(--sd-color-danger) !important;border-style:solid !important;border-width:1px !important}a.sd-outline-danger:focus,a.sd-outline-danger:hover{border-color:var(--sd-color-danger-highlight) !important}.sd-outline-light{border-color:var(--sd-color-light) !important;border-style:solid !important;border-width:1px !important}a.sd-outline-light:focus,a.sd-outline-light:hover{border-color:var(--sd-color-light-highlight) !important}.sd-outline-muted{border-color:var(--sd-color-muted) !important;border-style:solid !important;border-width:1px !important}a.sd-outline-muted:focus,a.sd-outline-muted:hover{border-color:var(--sd-color-muted-highlight) !important}.sd-outline-dark{border-color:var(--sd-color-dark) !important;border-style:solid !important;border-width:1px 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diff --git a/_static/design-tabs.js b/_static/design-tabs.js
new file mode 100644
index 0000000..36b38cf
--- /dev/null
+++ b/_static/design-tabs.js
@@ -0,0 +1,27 @@
+var sd_labels_by_text = {};
+
+function ready() {
+  const li = document.getElementsByClassName("sd-tab-label");
+  for (const label of li) {
+    syncId = label.getAttribute("data-sync-id");
+    if (syncId) {
+      label.onclick = onLabelClick;
+      if (!sd_labels_by_text[syncId]) {
+        sd_labels_by_text[syncId] = [];
+      }
+      sd_labels_by_text[syncId].push(label);
+    }
+  }
+}
+
+function onLabelClick() {
+  // Activate other inputs with the same sync id.
+  syncId = this.getAttribute("data-sync-id");
+  for (label of sd_labels_by_text[syncId]) {
+    if (label === this) continue;
+    label.previousElementSibling.checked = true;
+  }
+  window.localStorage.setItem("sphinx-design-last-tab", syncId);
+}
+
+document.addEventListener("DOMContentLoaded", ready, false);
diff --git a/_static/doctools.js b/_static/doctools.js
new file mode 100644
index 0000000..4d67807
--- /dev/null
+++ b/_static/doctools.js
@@ -0,0 +1,156 @@
+/*
+ * doctools.js
+ * ~~~~~~~~~~~
+ *
+ * Base JavaScript utilities for all Sphinx HTML documentation.
+ *
+ * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+"use strict";
+
+const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([
+  "TEXTAREA",
+  "INPUT",
+  "SELECT",
+  "BUTTON",
+]);
+
+const _ready = (callback) => {
+  if (document.readyState !== "loading") {
+    callback();
+  } else {
+    document.addEventListener("DOMContentLoaded", callback);
+  }
+};
+
+/**
+ * Small JavaScript module for the documentation.
+ */
+const Documentation = {
+  init: () => {
+    Documentation.initDomainIndexTable();
+    Documentation.initOnKeyListeners();
+  },
+
+  /**
+   * i18n support
+   */
+  TRANSLATIONS: {},
+  PLURAL_EXPR: (n) => (n === 1 ? 0 : 1),
+  LOCALE: "unknown",
+
+  // gettext and ngettext don't access this so that the functions
+  // can safely bound to a different name (_ = Documentation.gettext)
+  gettext: (string) => {
+    const translated = Documentation.TRANSLATIONS[string];
+    switch (typeof translated) {
+      case "undefined":
+        return string; // no translation
+      case "string":
+        return translated; // translation exists
+      default:
+        return translated[0]; // (singular, plural) translation tuple exists
+    }
+  },
+
+  ngettext: (singular, plural, n) => {
+    const translated = Documentation.TRANSLATIONS[singular];
+    if (typeof translated !== "undefined")
+      return translated[Documentation.PLURAL_EXPR(n)];
+    return n === 1 ? singular : plural;
+  },
+
+  addTranslations: (catalog) => {
+    Object.assign(Documentation.TRANSLATIONS, catalog.messages);
+    Documentation.PLURAL_EXPR = new Function(
+      "n",
+      `return (${catalog.plural_expr})`
+    );
+    Documentation.LOCALE = catalog.locale;
+  },
+
+  /**
+   * helper function to focus on search bar
+   */
+  focusSearchBar: () => {
+    document.querySelectorAll("input[name=q]")[0]?.focus();
+  },
+
+  /**
+   * Initialise the domain index toggle buttons
+   */
+  initDomainIndexTable: () => {
+    const toggler = (el) => {
+      const idNumber = el.id.substr(7);
+      const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`);
+      if (el.src.substr(-9) === "minus.png") {
+        el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`;
+        toggledRows.forEach((el) => (el.style.display = "none"));
+      } else {
+        el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`;
+        toggledRows.forEach((el) => (el.style.display = ""));
+      }
+    };
+
+    const togglerElements = document.querySelectorAll("img.toggler");
+    togglerElements.forEach((el) =>
+      el.addEventListener("click", (event) => toggler(event.currentTarget))
+    );
+    togglerElements.forEach((el) => (el.style.display = ""));
+    if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler);
+  },
+
+  initOnKeyListeners: () => {
+    // only install a listener if it is really needed
+    if (
+      !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS &&
+      !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS
+    )
+      return;
+
+    document.addEventListener("keydown", (event) => {
+      // bail for input elements
+      if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return;
+      // bail with special keys
+      if (event.altKey || event.ctrlKey || event.metaKey) return;
+
+      if (!event.shiftKey) {
+        switch (event.key) {
+          case "ArrowLeft":
+            if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+            const prevLink = document.querySelector('link[rel="prev"]');
+            if (prevLink && prevLink.href) {
+              window.location.href = prevLink.href;
+              event.preventDefault();
+            }
+            break;
+          case "ArrowRight":
+            if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+            const nextLink = document.querySelector('link[rel="next"]');
+            if (nextLink && nextLink.href) {
+              window.location.href = nextLink.href;
+              event.preventDefault();
+            }
+            break;
+        }
+      }
+
+      // some keyboard layouts may need Shift to get /
+      switch (event.key) {
+        case "/":
+          if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break;
+          Documentation.focusSearchBar();
+          event.preventDefault();
+      }
+    });
+  },
+};
+
+// quick alias for translations
+const _ = Documentation.gettext;
+
+_ready(Documentation.init);
diff --git a/_static/documentation_options.js b/_static/documentation_options.js
new file mode 100644
index 0000000..920be3d
--- /dev/null
+++ b/_static/documentation_options.js
@@ -0,0 +1,13 @@
+const DOCUMENTATION_OPTIONS = {
+    VERSION: '',
+    LANGUAGE: 'en',
+    COLLAPSE_INDEX: false,
+    BUILDER: 'dirhtml',
+    FILE_SUFFIX: '.html',
+    LINK_SUFFIX: '.html',
+    HAS_SOURCE: true,
+    SOURCELINK_SUFFIX: '',
+    NAVIGATION_WITH_KEYS: false,
+    SHOW_SEARCH_SUMMARY: true,
+    ENABLE_SEARCH_SHORTCUTS: true,
+};
\ No newline at end of file
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diff --git a/_static/images/logo_deepnote.svg b/_static/images/logo_deepnote.svg
new file mode 100644
index 0000000..fa77ebf
--- /dev/null
+++ b/_static/images/logo_deepnote.svg
@@ -0,0 +1 @@
+<svg viewBox="0 0 128 128" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M0 128h52.512l29.539-11.077-11.077-43.487-34.051 3.693L0 128Z" fill="#0076D4"/><path fill-rule="evenodd" clip-rule="evenodd" d="M52.513 128s16.6-8.759 19.673-24.277c3.072-15.517-12.091-26.594-35.263-26.594 0-.41 20.343-28.718 20.343-28.718l49.4 1.435L95.71 107.7l-20.452 15.978L52.513 128Z" fill="#002868"/><path fill-rule="evenodd" clip-rule="evenodd" d="M0 60.718 41.025.001s1.006.01 3.282 0c16.082-.068 81.23 3.12 81.23 60.368 0 65.352-73.025 67.631-73.025 67.631s30.495-5.839 30.495-34.816c0-28.978-27.541-32.466-45.264-32.466H0Z" fill="#00A9FF"/></svg>
diff --git a/_static/images/logo_jupyterhub.svg b/_static/images/logo_jupyterhub.svg
new file mode 100644
index 0000000..60cfe9f
--- /dev/null
+++ b/_static/images/logo_jupyterhub.svg
@@ -0,0 +1 @@
+<svg id="Layer_1" data-name="Layer 1" xmlns="http://www.w3.org/2000/svg" width="38.73" height="50" viewBox="0 0 38.73 50"><defs><style>.cls-1{fill:#767677;}.cls-2{fill:#f37726;}.cls-3{fill:#9e9e9e;}.cls-4{fill:#616262;}.cls-5{font-size:17.07px;fill:#fff;font-family:Roboto-Regular, Roboto;}</style></defs><title>logo_jupyterhub</title><g id="Canvas"><path id="path7_fill" data-name="path7 fill" class="cls-1" d="M39.51,3.53a3,3,0,0,1-1.7,2.9A3,3,0,0,1,34.48,6a3,3,0,0,1-.82-3.26,3,3,0,0,1,1.05-1.41A3,3,0,0,1,37.52.86a2.88,2.88,0,0,1,1,.6,3,3,0,0,1,.7.93,3.18,3.18,0,0,1,.28,1.14Z" transform="translate(-1.87 -0.69)"/><path id="path8_fill" data-name="path8 fill" class="cls-2" d="M21.91,38.39c-8,0-15.06-2.87-18.7-7.12a19.93,19.93,0,0,0,37.39,0C37,35.52,30,38.39,21.91,38.39Z" transform="translate(-1.87 -0.69)"/><path id="path9_fill" data-name="path9 fill" class="cls-2" d="M21.91,10.78c8,0,15.05,2.87,18.69,7.12a19.93,19.93,0,0,0-37.39,0C6.85,13.64,13.86,10.78,21.91,10.78Z" transform="translate(-1.87 -0.69)"/><path id="path10_fill" data-name="path10 fill" class="cls-3" d="M10.88,46.66a3.86,3.86,0,0,1-.52,2.15,3.81,3.81,0,0,1-1.62,1.51,3.93,3.93,0,0,1-2.19.34,3.79,3.79,0,0,1-2-.94,3.73,3.73,0,0,1-1.14-1.9,3.79,3.79,0,0,1,.1-2.21,3.86,3.86,0,0,1,1.33-1.78,3.92,3.92,0,0,1,3.54-.53,3.85,3.85,0,0,1,2.14,1.93,3.74,3.74,0,0,1,.37,1.43Z" transform="translate(-1.87 -0.69)"/><path id="path11_fill" data-name="path11 fill" class="cls-4" d="M4.12,9.81A2.18,2.18,0,0,1,2.9,9.48a2.23,2.23,0,0,1-.84-1A2.26,2.26,0,0,1,1.9,7.26a2.13,2.13,0,0,1,.56-1.13,2.18,2.18,0,0,1,2.36-.56,2.13,2.13,0,0,1,1,.76,2.18,2.18,0,0,1,.42,1.2A2.22,2.22,0,0,1,4.12,9.81Z" transform="translate(-1.87 -0.69)"/></g><text class="cls-5" transform="translate(5.24 30.01)">Hub</text></svg>
diff --git a/_static/language_data.js b/_static/language_data.js
new file mode 100644
index 0000000..367b8ed
--- /dev/null
+++ b/_static/language_data.js
@@ -0,0 +1,199 @@
+/*
+ * language_data.js
+ * ~~~~~~~~~~~~~~~~
+ *
+ * This script contains the language-specific data used by searchtools.js,
+ * namely the list of stopwords, stemmer, scorer and splitter.
+ *
+ * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+
+var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"];
+
+
+/* Non-minified version is copied as a separate JS file, if available */
+
+/**
+ * Porter Stemmer
+ */
+var Stemmer = function() {
+
+  var step2list = {
+    ational: 'ate',
+    tional: 'tion',
+    enci: 'ence',
+    anci: 'ance',
+    izer: 'ize',
+    bli: 'ble',
+    alli: 'al',
+    entli: 'ent',
+    eli: 'e',
+    ousli: 'ous',
+    ization: 'ize',
+    ation: 'ate',
+    ator: 'ate',
+    alism: 'al',
+    iveness: 'ive',
+    fulness: 'ful',
+    ousness: 'ous',
+    aliti: 'al',
+    iviti: 'ive',
+    biliti: 'ble',
+    logi: 'log'
+  };
+
+  var step3list = {
+    icate: 'ic',
+    ative: '',
+    alize: 'al',
+    iciti: 'ic',
+    ical: 'ic',
+    ful: '',
+    ness: ''
+  };
+
+  var c = "[^aeiou]";          // consonant
+  var v = "[aeiouy]";          // vowel
+  var C = c + "[^aeiouy]*";    // consonant sequence
+  var V = v + "[aeiou]*";      // vowel sequence
+
+  var mgr0 = "^(" + C + ")?" + V + C;                      // [C]VC... is m>0
+  var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$";    // [C]VC[V] is m=1
+  var mgr1 = "^(" + C + ")?" + V + C + V + C;              // [C]VCVC... is m>1
+  var s_v   = "^(" + C + ")?" + v;                         // vowel in stem
+
+  this.stemWord = function (w) {
+    var stem;
+    var suffix;
+    var firstch;
+    var origword = w;
+
+    if (w.length < 3)
+      return w;
+
+    var re;
+    var re2;
+    var re3;
+    var re4;
+
+    firstch = w.substr(0,1);
+    if (firstch == "y")
+      w = firstch.toUpperCase() + w.substr(1);
+
+    // Step 1a
+    re = /^(.+?)(ss|i)es$/;
+    re2 = /^(.+?)([^s])s$/;
+
+    if (re.test(w))
+      w = w.replace(re,"$1$2");
+    else if (re2.test(w))
+      w = w.replace(re2,"$1$2");
+
+    // Step 1b
+    re = /^(.+?)eed$/;
+    re2 = /^(.+?)(ed|ing)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      re = new RegExp(mgr0);
+      if (re.test(fp[1])) {
+        re = /.$/;
+        w = w.replace(re,"");
+      }
+    }
+    else if (re2.test(w)) {
+      var fp = re2.exec(w);
+      stem = fp[1];
+      re2 = new RegExp(s_v);
+      if (re2.test(stem)) {
+        w = stem;
+        re2 = /(at|bl|iz)$/;
+        re3 = new RegExp("([^aeiouylsz])\\1$");
+        re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+        if (re2.test(w))
+          w = w + "e";
+        else if (re3.test(w)) {
+          re = /.$/;
+          w = w.replace(re,"");
+        }
+        else if (re4.test(w))
+          w = w + "e";
+      }
+    }
+
+    // Step 1c
+    re = /^(.+?)y$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(s_v);
+      if (re.test(stem))
+        w = stem + "i";
+    }
+
+    // Step 2
+    re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      suffix = fp[2];
+      re = new RegExp(mgr0);
+      if (re.test(stem))
+        w = stem + step2list[suffix];
+    }
+
+    // Step 3
+    re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      suffix = fp[2];
+      re = new RegExp(mgr0);
+      if (re.test(stem))
+        w = stem + step3list[suffix];
+    }
+
+    // Step 4
+    re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
+    re2 = /^(.+?)(s|t)(ion)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(mgr1);
+      if (re.test(stem))
+        w = stem;
+    }
+    else if (re2.test(w)) {
+      var fp = re2.exec(w);
+      stem = fp[1] + fp[2];
+      re2 = new RegExp(mgr1);
+      if (re2.test(stem))
+        w = stem;
+    }
+
+    // Step 5
+    re = /^(.+?)e$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(mgr1);
+      re2 = new RegExp(meq1);
+      re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+      if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
+        w = stem;
+    }
+    re = /ll$/;
+    re2 = new RegExp(mgr1);
+    if (re.test(w) && re2.test(w)) {
+      re = /.$/;
+      w = w.replace(re,"");
+    }
+
+    // and turn initial Y back to y
+    if (firstch == "y")
+      w = firstch.toLowerCase() + w.substr(1);
+    return w;
+  }
+}
+
diff --git a/_static/locales/ar/LC_MESSAGES/booktheme.mo b/_static/locales/ar/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..15541a6a375f93efed3f410c2f892174ba91aaa0
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/ar/LC_MESSAGES/booktheme.po b/_static/locales/ar/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..edae2ec
--- /dev/null
+++ b/_static/locales/ar/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ar\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "موضوع بواسطة"
+
+msgid "Open an issue"
+msgstr "افتح قضية"
+
+msgid "Contents"
+msgstr "محتويات"
+
+msgid "Download notebook file"
+msgstr "تنزيل ملف دفتر الملاحظات"
+
+msgid "Sphinx Book Theme"
+msgstr "موضوع كتاب أبو الهول"
+
+msgid "Fullscreen mode"
+msgstr "وضع ملء الشاشة"
+
+msgid "Edit this page"
+msgstr "قم بتحرير هذه الصفحة"
+
+msgid "By"
+msgstr "بواسطة"
+
+msgid "Copyright"
+msgstr "حقوق النشر"
+
+msgid "Source repository"
+msgstr "مستودع المصدر"
+
+msgid "previous page"
+msgstr "الصفحة السابقة"
+
+msgid "next page"
+msgstr "الصفحة التالية"
+
+msgid "Toggle navigation"
+msgstr "تبديل التنقل"
+
+msgid "repository"
+msgstr "مخزن"
+
+msgid "suggest edit"
+msgstr "أقترح تحرير"
+
+msgid "open issue"
+msgstr "قضية مفتوحة"
+
+msgid "Launch"
+msgstr "إطلاق"
+
+msgid "Print to PDF"
+msgstr "طباعة إلى PDF"
+
+msgid "By the"
+msgstr "بواسطة"
+
+msgid "Last updated on"
+msgstr "آخر تحديث في"
+
+msgid "Download source file"
+msgstr "تنزيل ملف المصدر"
+
+msgid "Download this page"
+msgstr "قم بتنزيل هذه الصفحة"
diff --git a/_static/locales/bg/LC_MESSAGES/booktheme.mo b/_static/locales/bg/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..da95120037f8d7c52ad1f166a7682ea55ca47a01
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literal 0
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diff --git a/_static/locales/bg/LC_MESSAGES/booktheme.po b/_static/locales/bg/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..1f363b9
--- /dev/null
+++ b/_static/locales/bg/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: bg\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Тема от"
+
+msgid "Open an issue"
+msgstr "Отворете проблем"
+
+msgid "Contents"
+msgstr "Съдържание"
+
+msgid "Download notebook file"
+msgstr "Изтеглете файла на бележника"
+
+msgid "Sphinx Book Theme"
+msgstr "Тема на книгата Sphinx"
+
+msgid "Fullscreen mode"
+msgstr "Режим на цял екран"
+
+msgid "Edit this page"
+msgstr "Редактирайте тази страница"
+
+msgid "By"
+msgstr "От"
+
+msgid "Copyright"
+msgstr "Авторско право"
+
+msgid "Source repository"
+msgstr "Хранилище на източника"
+
+msgid "previous page"
+msgstr "предишна страница"
+
+msgid "next page"
+msgstr "Следваща страница"
+
+msgid "Toggle navigation"
+msgstr "Превключване на навигацията"
+
+msgid "repository"
+msgstr "хранилище"
+
+msgid "suggest edit"
+msgstr "предложи редактиране"
+
+msgid "open issue"
+msgstr "отворен брой"
+
+msgid "Launch"
+msgstr "Стартиране"
+
+msgid "Print to PDF"
+msgstr "Печат в PDF"
+
+msgid "By the"
+msgstr "По"
+
+msgid "Last updated on"
+msgstr "Последна актуализация на"
+
+msgid "Download source file"
+msgstr "Изтеглете изходния файл"
+
+msgid "Download this page"
+msgstr "Изтеглете тази страница"
diff --git a/_static/locales/bn/LC_MESSAGES/booktheme.mo b/_static/locales/bn/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..6b96639b726a2fa959a6419b6f8b7e0dfcce33ae
GIT binary patch
literal 1646
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literal 0
HcmV?d00001

diff --git a/_static/locales/bn/LC_MESSAGES/booktheme.po b/_static/locales/bn/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..fa54372
--- /dev/null
+++ b/_static/locales/bn/LC_MESSAGES/booktheme.po
@@ -0,0 +1,63 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: bn\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "থিম দ্বারা"
+
+msgid "Open an issue"
+msgstr "একটি সমস্যা খুলুন"
+
+msgid "Download notebook file"
+msgstr "নোটবুক ফাইল ডাউনলোড করুন"
+
+msgid "Sphinx Book Theme"
+msgstr "স্পিনিক্স বুক থিম"
+
+msgid "Edit this page"
+msgstr "এই পৃষ্ঠাটি সম্পাদনা করুন"
+
+msgid "By"
+msgstr "দ্বারা"
+
+msgid "Copyright"
+msgstr "কপিরাইট"
+
+msgid "Source repository"
+msgstr "উত্স সংগ্রহস্থল"
+
+msgid "previous page"
+msgstr "আগের পৃষ্ঠা"
+
+msgid "next page"
+msgstr "পরবর্তী পৃষ্ঠা"
+
+msgid "Toggle navigation"
+msgstr "নেভিগেশন টগল করুন"
+
+msgid "open issue"
+msgstr "খোলা সমস্যা"
+
+msgid "Launch"
+msgstr "শুরু করা"
+
+msgid "Print to PDF"
+msgstr "পিডিএফ প্রিন্ট করুন"
+
+msgid "By the"
+msgstr "দ্বারা"
+
+msgid "Last updated on"
+msgstr "সর্বশেষ আপডেট"
+
+msgid "Download source file"
+msgstr "উত্স ফাইল ডাউনলোড করুন"
+
+msgid "Download this page"
+msgstr "এই পৃষ্ঠাটি ডাউনলোড করুন"
diff --git a/_static/locales/ca/LC_MESSAGES/booktheme.mo b/_static/locales/ca/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..a4dd30e9bd762578b119c4401d082ea4fa430613
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/ca/LC_MESSAGES/booktheme.po b/_static/locales/ca/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..22f1569
--- /dev/null
+++ b/_static/locales/ca/LC_MESSAGES/booktheme.po
@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ca\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema del"
+
+msgid "Open an issue"
+msgstr "Obriu un número"
+
+msgid "Download notebook file"
+msgstr "Descarregar fitxer de quadern"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema del llibre Esfinx"
+
+msgid "Edit this page"
+msgstr "Editeu aquesta pàgina"
+
+msgid "By"
+msgstr "Per"
+
+msgid "Copyright"
+msgstr "Copyright"
+
+msgid "Source repository"
+msgstr "Dipòsit de fonts"
+
+msgid "previous page"
+msgstr "Pàgina anterior"
+
+msgid "next page"
+msgstr "pàgina següent"
+
+msgid "Toggle navigation"
+msgstr "Commuta la navegació"
+
+msgid "suggest edit"
+msgstr "suggerir edició"
+
+msgid "open issue"
+msgstr "número obert"
+
+msgid "Launch"
+msgstr "Llançament"
+
+msgid "Print to PDF"
+msgstr "Imprimeix a PDF"
+
+msgid "By the"
+msgstr "Per la"
+
+msgid "Last updated on"
+msgstr "Darrera actualització el"
+
+msgid "Download source file"
+msgstr "Baixeu el fitxer font"
+
+msgid "Download this page"
+msgstr "Descarregueu aquesta pàgina"
diff --git a/_static/locales/cs/LC_MESSAGES/booktheme.mo b/_static/locales/cs/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..c39e01a6ae9ae5242f04566ffa2cda96b328ca18
GIT binary patch
literal 1405
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literal 0
HcmV?d00001

diff --git a/_static/locales/cs/LC_MESSAGES/booktheme.po b/_static/locales/cs/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..afecd9e
--- /dev/null
+++ b/_static/locales/cs/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: cs\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Téma od"
+
+msgid "Open an issue"
+msgstr "Otevřete problém"
+
+msgid "Contents"
+msgstr "Obsah"
+
+msgid "Download notebook file"
+msgstr "Stáhnout soubor poznámkového bloku"
+
+msgid "Sphinx Book Theme"
+msgstr "Téma knihy Sfinga"
+
+msgid "Fullscreen mode"
+msgstr "Režim celé obrazovky"
+
+msgid "Edit this page"
+msgstr "Upravit tuto stránku"
+
+msgid "By"
+msgstr "Podle"
+
+msgid "Copyright"
+msgstr "autorská práva"
+
+msgid "Source repository"
+msgstr "Zdrojové úložiště"
+
+msgid "previous page"
+msgstr "předchozí stránka"
+
+msgid "next page"
+msgstr "další strana"
+
+msgid "Toggle navigation"
+msgstr "Přepnout navigaci"
+
+msgid "repository"
+msgstr "úložiště"
+
+msgid "suggest edit"
+msgstr "navrhnout úpravy"
+
+msgid "open issue"
+msgstr "otevřené číslo"
+
+msgid "Launch"
+msgstr "Zahájení"
+
+msgid "Print to PDF"
+msgstr "Tisk do PDF"
+
+msgid "By the"
+msgstr "Podle"
+
+msgid "Last updated on"
+msgstr "Naposledy aktualizováno"
+
+msgid "Download source file"
+msgstr "Stáhněte si zdrojový soubor"
+
+msgid "Download this page"
+msgstr "Stáhněte si tuto stránku"
diff --git a/_static/locales/da/LC_MESSAGES/booktheme.mo b/_static/locales/da/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..f43157d70c63ff21b4385dc36cb73f5b14eb6b01
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/da/LC_MESSAGES/booktheme.po b/_static/locales/da/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..649c78a
--- /dev/null
+++ b/_static/locales/da/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: da\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema af"
+
+msgid "Open an issue"
+msgstr "Åbn et problem"
+
+msgid "Contents"
+msgstr "Indhold"
+
+msgid "Download notebook file"
+msgstr "Download notesbog-fil"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx bogtema"
+
+msgid "Fullscreen mode"
+msgstr "Fuldskærmstilstand"
+
+msgid "Edit this page"
+msgstr "Rediger denne side"
+
+msgid "By"
+msgstr "Ved"
+
+msgid "Copyright"
+msgstr "ophavsret"
+
+msgid "Source repository"
+msgstr "Kildelager"
+
+msgid "previous page"
+msgstr "forrige side"
+
+msgid "next page"
+msgstr "Næste side"
+
+msgid "Toggle navigation"
+msgstr "Skift navigation"
+
+msgid "repository"
+msgstr "lager"
+
+msgid "suggest edit"
+msgstr "foreslå redigering"
+
+msgid "open issue"
+msgstr "åbent nummer"
+
+msgid "Launch"
+msgstr "Start"
+
+msgid "Print to PDF"
+msgstr "Udskriv til PDF"
+
+msgid "By the"
+msgstr "Ved"
+
+msgid "Last updated on"
+msgstr "Sidst opdateret den"
+
+msgid "Download source file"
+msgstr "Download kildefil"
+
+msgid "Download this page"
+msgstr "Download denne side"
diff --git a/_static/locales/de/LC_MESSAGES/booktheme.mo b/_static/locales/de/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..648b565c7829535bc5f26f86909f458d0cd0fe1b
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/de/LC_MESSAGES/booktheme.po b/_static/locales/de/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..f51d2ec
--- /dev/null
+++ b/_static/locales/de/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: de\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Thema von der"
+
+msgid "Open an issue"
+msgstr "Öffnen Sie ein Problem"
+
+msgid "Contents"
+msgstr "Inhalt"
+
+msgid "Download notebook file"
+msgstr "Notebook-Datei herunterladen"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx-Buch-Thema"
+
+msgid "Fullscreen mode"
+msgstr "Vollbildmodus"
+
+msgid "Edit this page"
+msgstr "Bearbeite diese Seite"
+
+msgid "By"
+msgstr "Durch"
+
+msgid "Copyright"
+msgstr "Urheberrechte ©"
+
+msgid "Source repository"
+msgstr "Quell-Repository"
+
+msgid "previous page"
+msgstr "vorherige Seite"
+
+msgid "next page"
+msgstr "Nächste Seite"
+
+msgid "Toggle navigation"
+msgstr "Navigation umschalten"
+
+msgid "repository"
+msgstr "Repository"
+
+msgid "suggest edit"
+msgstr "vorschlagen zu bearbeiten"
+
+msgid "open issue"
+msgstr "offenes Thema"
+
+msgid "Launch"
+msgstr "Starten"
+
+msgid "Print to PDF"
+msgstr "In PDF drucken"
+
+msgid "By the"
+msgstr "Bis zum"
+
+msgid "Last updated on"
+msgstr "Zuletzt aktualisiert am"
+
+msgid "Download source file"
+msgstr "Quelldatei herunterladen"
+
+msgid "Download this page"
+msgstr "Laden Sie diese Seite herunter"
diff --git a/_static/locales/el/LC_MESSAGES/booktheme.mo b/_static/locales/el/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..fca6e9355f314677f2890f5679fd79dd67a7a5a2
GIT binary patch
literal 1722
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literal 0
HcmV?d00001

diff --git a/_static/locales/el/LC_MESSAGES/booktheme.po b/_static/locales/el/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..8bec790
--- /dev/null
+++ b/_static/locales/el/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: el\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Θέμα από το"
+
+msgid "Open an issue"
+msgstr "Ανοίξτε ένα ζήτημα"
+
+msgid "Contents"
+msgstr "Περιεχόμενα"
+
+msgid "Download notebook file"
+msgstr "Λήψη αρχείου σημειωματάριου"
+
+msgid "Sphinx Book Theme"
+msgstr "Θέμα βιβλίου Sphinx"
+
+msgid "Fullscreen mode"
+msgstr "ΛΕΙΤΟΥΡΓΙΑ ΠΛΗΡΟΥΣ ΟΘΟΝΗΣ"
+
+msgid "Edit this page"
+msgstr "Επεξεργαστείτε αυτήν τη σελίδα"
+
+msgid "By"
+msgstr "Με"
+
+msgid "Copyright"
+msgstr "Πνευματική ιδιοκτησία"
+
+msgid "Source repository"
+msgstr "Αποθήκη πηγής"
+
+msgid "previous page"
+msgstr "προηγούμενη σελίδα"
+
+msgid "next page"
+msgstr "επόμενη σελίδα"
+
+msgid "Toggle navigation"
+msgstr "Εναλλαγή πλοήγησης"
+
+msgid "repository"
+msgstr "αποθήκη"
+
+msgid "suggest edit"
+msgstr "προτείνω επεξεργασία"
+
+msgid "open issue"
+msgstr "ανοιχτό ζήτημα"
+
+msgid "Launch"
+msgstr "Εκτόξευση"
+
+msgid "Print to PDF"
+msgstr "Εκτύπωση σε PDF"
+
+msgid "By the"
+msgstr "Από το"
+
+msgid "Last updated on"
+msgstr "Τελευταία ενημέρωση στις"
+
+msgid "Download source file"
+msgstr "Λήψη αρχείου προέλευσης"
+
+msgid "Download this page"
+msgstr "Λήψη αυτής της σελίδας"
diff --git a/_static/locales/eo/LC_MESSAGES/booktheme.mo b/_static/locales/eo/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..d1072bbec62959524a87953d3f41b7c272ecbe37
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/eo/LC_MESSAGES/booktheme.po b/_static/locales/eo/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..d72a048
--- /dev/null
+++ b/_static/locales/eo/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: eo\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Temo de la"
+
+msgid "Open an issue"
+msgstr "Malfermu numeron"
+
+msgid "Contents"
+msgstr "Enhavo"
+
+msgid "Download notebook file"
+msgstr "Elŝutu kajeran dosieron"
+
+msgid "Sphinx Book Theme"
+msgstr "Sfinksa Libro-Temo"
+
+msgid "Fullscreen mode"
+msgstr "Plenekrana reĝimo"
+
+msgid "Edit this page"
+msgstr "Redaktu ĉi tiun paĝon"
+
+msgid "By"
+msgstr "De"
+
+msgid "Copyright"
+msgstr "Kopirajto"
+
+msgid "Source repository"
+msgstr "Fonto-deponejo"
+
+msgid "previous page"
+msgstr "antaŭa paĝo"
+
+msgid "next page"
+msgstr "sekva paĝo"
+
+msgid "Toggle navigation"
+msgstr "Ŝalti navigadon"
+
+msgid "repository"
+msgstr "deponejo"
+
+msgid "suggest edit"
+msgstr "sugesti redaktadon"
+
+msgid "open issue"
+msgstr "malferma numero"
+
+msgid "Launch"
+msgstr "Lanĉo"
+
+msgid "Print to PDF"
+msgstr "Presi al PDF"
+
+msgid "By the"
+msgstr "Per la"
+
+msgid "Last updated on"
+msgstr "Laste ĝisdatigita la"
+
+msgid "Download source file"
+msgstr "Elŝutu fontodosieron"
+
+msgid "Download this page"
+msgstr "Elŝutu ĉi tiun paĝon"
diff --git a/_static/locales/es/LC_MESSAGES/booktheme.mo b/_static/locales/es/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..ba2ee4dc22148ed53f2aeba32c5965654d4a5a2f
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/es/LC_MESSAGES/booktheme.po b/_static/locales/es/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..611834b
--- /dev/null
+++ b/_static/locales/es/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: es\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema por el"
+
+msgid "Open an issue"
+msgstr "Abrir un problema"
+
+msgid "Contents"
+msgstr "Contenido"
+
+msgid "Download notebook file"
+msgstr "Descargar archivo de cuaderno"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema del libro de la esfinge"
+
+msgid "Fullscreen mode"
+msgstr "Modo de pantalla completa"
+
+msgid "Edit this page"
+msgstr "Edita esta página"
+
+msgid "By"
+msgstr "Por"
+
+msgid "Copyright"
+msgstr "Derechos de autor"
+
+msgid "Source repository"
+msgstr "Repositorio de origen"
+
+msgid "previous page"
+msgstr "pagina anterior"
+
+msgid "next page"
+msgstr "siguiente página"
+
+msgid "Toggle navigation"
+msgstr "Navegación de palanca"
+
+msgid "repository"
+msgstr "repositorio"
+
+msgid "suggest edit"
+msgstr "sugerir editar"
+
+msgid "open issue"
+msgstr "Tema abierto"
+
+msgid "Launch"
+msgstr "Lanzamiento"
+
+msgid "Print to PDF"
+msgstr "Imprimir en PDF"
+
+msgid "By the"
+msgstr "Por el"
+
+msgid "Last updated on"
+msgstr "Ultima actualización en"
+
+msgid "Download source file"
+msgstr "Descargar archivo fuente"
+
+msgid "Download this page"
+msgstr "Descarga esta pagina"
diff --git a/_static/locales/et/LC_MESSAGES/booktheme.mo b/_static/locales/et/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..983b82391f499b67a9046c15d0dd8744650ad925
GIT binary patch
literal 1341
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P_MW2m5}a<3ol*Y+f5$~k

literal 0
HcmV?d00001

diff --git a/_static/locales/et/LC_MESSAGES/booktheme.po b/_static/locales/et/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..345088f
--- /dev/null
+++ b/_static/locales/et/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: et\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Teema"
+
+msgid "Open an issue"
+msgstr "Avage probleem"
+
+msgid "Contents"
+msgstr "Sisu"
+
+msgid "Download notebook file"
+msgstr "Laadige sülearvuti fail alla"
+
+msgid "Sphinx Book Theme"
+msgstr "Sfinksiraamatu teema"
+
+msgid "Fullscreen mode"
+msgstr "Täisekraanirežiim"
+
+msgid "Edit this page"
+msgstr "Muutke seda lehte"
+
+msgid "By"
+msgstr "Kõrval"
+
+msgid "Copyright"
+msgstr "Autoriõigus"
+
+msgid "Source repository"
+msgstr "Allikahoidla"
+
+msgid "previous page"
+msgstr "eelmine leht"
+
+msgid "next page"
+msgstr "järgmine leht"
+
+msgid "Toggle navigation"
+msgstr "Lülita navigeerimine sisse"
+
+msgid "repository"
+msgstr "hoidla"
+
+msgid "suggest edit"
+msgstr "soovita muuta"
+
+msgid "open issue"
+msgstr "avatud küsimus"
+
+msgid "Launch"
+msgstr "Käivitage"
+
+msgid "Print to PDF"
+msgstr "Prindi PDF-i"
+
+msgid "By the"
+msgstr "Autor"
+
+msgid "Last updated on"
+msgstr "Viimati uuendatud"
+
+msgid "Download source file"
+msgstr "Laadige alla lähtefail"
+
+msgid "Download this page"
+msgstr "Laadige see leht alla"
diff --git a/_static/locales/fi/LC_MESSAGES/booktheme.mo b/_static/locales/fi/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..d8ac054597c924e3010f629caeac1c748b7211cd
GIT binary patch
literal 1368
zcmZ9KJ#5r46vquMU&lA4Af!r|g^wXX5kqz52B58kprWEjclYv|xbfLh>>S*}#K;Cr
ztS2O9B*cCTVrBw~l?gF1AR)y6B`K}2;{5K}=lB1=7k@o5`BGq<#+<?Ygn1V8*)F^=
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H66VBTf3Z^G

literal 0
HcmV?d00001

diff --git a/_static/locales/fi/LC_MESSAGES/booktheme.po b/_static/locales/fi/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..d97a08d
--- /dev/null
+++ b/_static/locales/fi/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: fi\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Teeman tekijä"
+
+msgid "Open an issue"
+msgstr "Avaa ongelma"
+
+msgid "Contents"
+msgstr "Sisällys"
+
+msgid "Download notebook file"
+msgstr "Lataa muistikirjatiedosto"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx-kirjan teema"
+
+msgid "Fullscreen mode"
+msgstr "Koko näytön tila"
+
+msgid "Edit this page"
+msgstr "Muokkaa tätä sivua"
+
+msgid "By"
+msgstr "Tekijä"
+
+msgid "Copyright"
+msgstr "Tekijänoikeus"
+
+msgid "Source repository"
+msgstr "Lähteen arkisto"
+
+msgid "previous page"
+msgstr "Edellinen sivu"
+
+msgid "next page"
+msgstr "seuraava sivu"
+
+msgid "Toggle navigation"
+msgstr "Vaihda navigointia"
+
+msgid "repository"
+msgstr "arkisto"
+
+msgid "suggest edit"
+msgstr "ehdottaa muokkausta"
+
+msgid "open issue"
+msgstr "avoin ongelma"
+
+msgid "Launch"
+msgstr "Tuoda markkinoille"
+
+msgid "Print to PDF"
+msgstr "Tulosta PDF-tiedostoon"
+
+msgid "By the"
+msgstr "Mukaan"
+
+msgid "Last updated on"
+msgstr "Viimeksi päivitetty"
+
+msgid "Download source file"
+msgstr "Lataa lähdetiedosto"
+
+msgid "Download this page"
+msgstr "Lataa tämä sivu"
diff --git a/_static/locales/fr/LC_MESSAGES/booktheme.mo b/_static/locales/fr/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..f663d39f0faa76c5b9bd504c51252eef74cca5de
GIT binary patch
literal 1412
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z@(VpgvBl*|+YE)ZQEjFj&wG?C)!uDalV>RR`l$A11nWA{5XsPS+9@lOaXon+Y2Ue0
zE>oVUGO*E>4ZSkmuAAH}>yV{N!q<m8Mp~IdGCLao4;4&dwOl&l#q>_?5zAzp!&O#!
T<A7>A2+cw{Vw>h7Yg+MtLz81?

literal 0
HcmV?d00001

diff --git a/_static/locales/fr/LC_MESSAGES/booktheme.po b/_static/locales/fr/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..88f3517
--- /dev/null
+++ b/_static/locales/fr/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: fr\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Thème par le"
+
+msgid "Open an issue"
+msgstr "Ouvrez un problème"
+
+msgid "Contents"
+msgstr "Contenu"
+
+msgid "Download notebook file"
+msgstr "Télécharger le fichier notebook"
+
+msgid "Sphinx Book Theme"
+msgstr "Thème du livre Sphinx"
+
+msgid "Fullscreen mode"
+msgstr "Mode plein écran"
+
+msgid "Edit this page"
+msgstr "Modifier cette page"
+
+msgid "By"
+msgstr "Par"
+
+msgid "Copyright"
+msgstr "droits d'auteur"
+
+msgid "Source repository"
+msgstr "Dépôt source"
+
+msgid "previous page"
+msgstr "page précédente"
+
+msgid "next page"
+msgstr "page suivante"
+
+msgid "Toggle navigation"
+msgstr "Basculer la navigation"
+
+msgid "repository"
+msgstr "dépôt"
+
+msgid "suggest edit"
+msgstr "suggestion de modification"
+
+msgid "open issue"
+msgstr "signaler un problème"
+
+msgid "Launch"
+msgstr "lancement"
+
+msgid "Print to PDF"
+msgstr "Imprimer au format PDF"
+
+msgid "By the"
+msgstr "Par le"
+
+msgid "Last updated on"
+msgstr "Dernière mise à jour le"
+
+msgid "Download source file"
+msgstr "Télécharger le fichier source"
+
+msgid "Download this page"
+msgstr "Téléchargez cette page"
diff --git a/_static/locales/hr/LC_MESSAGES/booktheme.mo b/_static/locales/hr/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..eca4a1a2842830f06bd5f6235bf01d07bdd313d2
GIT binary patch
literal 1402
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z%T4MpwK#{4ax`^Pw+`@7ELnZzY-Ae)KI#K+iZZI(?h9Kvos)Hu_nn*4eN*x2ba2UM
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zh&bB0JyN@EJkPZYCOUthcI(pE2XsrkjZ2=fYTmTp<}`LiQ88IPH-(M{K`cLrtve@i
z+90*(xpAqpy(Aw}Q7~LGGJzF0;VkyI^8P*c0crzk<M$<gzlq$tyLET-bp6_U@AtaG
z_QwY`4=BRGdR=K_Hz+H$4;+Vk<5B<S={~P*xX-@7X)~7_TMX#tzKOj%+7=0Q9Z>0e
zJ5}<!>W`eCg#p>R8HV8p8`ORd-?8+@kgmPE(NjB4ZRZpsbXo1{+%JywM17c0!7$ZS
zdp+04j?>}H5RL<fJx#Q4stGTStjXjQ+C_6XciyHan@$!YlbfeDgvpZH^HQ;=CO^@~
zUmJ^XJav?r30JP5Lmet-5#9xa%k6|oFOHHoFgxJ^=BJ)5wA6M)Y!NkwxvZ(JP~&Q)
z=4Na)#vBEx&&=X`>>u+?)6`B(!QC;nQ(E%YYHwOi5)9EgF2Tundr{ymsm2Z;f2mKh
k(#nYgw(f}olqHrfw@Z7L48TfWxy6y8<oWoKnK!Qg2ay|IDF6Tf

literal 0
HcmV?d00001

diff --git a/_static/locales/hr/LC_MESSAGES/booktheme.po b/_static/locales/hr/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..fb9440a
--- /dev/null
+++ b/_static/locales/hr/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: hr\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema autora"
+
+msgid "Open an issue"
+msgstr "Otvorite izdanje"
+
+msgid "Contents"
+msgstr "Sadržaj"
+
+msgid "Download notebook file"
+msgstr "Preuzmi datoteku bilježnice"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema knjige Sphinx"
+
+msgid "Fullscreen mode"
+msgstr "Način preko cijelog zaslona"
+
+msgid "Edit this page"
+msgstr "Uredite ovu stranicu"
+
+msgid "By"
+msgstr "Po"
+
+msgid "Copyright"
+msgstr "Autorska prava"
+
+msgid "Source repository"
+msgstr "Izvorno spremište"
+
+msgid "previous page"
+msgstr "Prethodna stranica"
+
+msgid "next page"
+msgstr "sljedeća stranica"
+
+msgid "Toggle navigation"
+msgstr "Uključi / isključi navigaciju"
+
+msgid "repository"
+msgstr "spremište"
+
+msgid "suggest edit"
+msgstr "predloži uređivanje"
+
+msgid "open issue"
+msgstr "otvoreno izdanje"
+
+msgid "Launch"
+msgstr "Pokrenite"
+
+msgid "Print to PDF"
+msgstr "Ispis u PDF"
+
+msgid "By the"
+msgstr "Od strane"
+
+msgid "Last updated on"
+msgstr "Posljednje ažuriranje:"
+
+msgid "Download source file"
+msgstr "Preuzmi izvornu datoteku"
+
+msgid "Download this page"
+msgstr "Preuzmite ovu stranicu"
diff --git a/_static/locales/id/LC_MESSAGES/booktheme.mo b/_static/locales/id/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..d07a06a9d27aaf6d67234c227c22d61d5a23203b
GIT binary patch
literal 1323
zcmZ9JIfxWN6oyOJV;%2ZZx$>Q4`jSBkXa^hFIaGO(a}_Drr&ngPIpyPhwkKtCW1zS
zxtWoenhB;xBBn-yn24D8zwTalu&Ao9Uv<5s{`Yli#|wdR9BT&a6V_?0r`xb$Ol}tf
zQ|!UE3)}}zg45t0a0WaEo&}G9U2qD#3myOoJP3w{Pe6|I9NZ7S1owfj!NcI&h98>q
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z4R3=dU_S)+f*T;`dD8G1$o{WD_Im?z{P&Ih5#&5yK-S?0$ohz#wGPuD`<((=a*oaa
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zg2zWWayrd|Sg?;xZdD?U4b-=GDA#mOTgTo;H=zFxL#DkfRZ3zp(E*`1&83*<e&C3V
zENnvJmhwTyGEspNX$|aX2AQ~1;({_#dml-xI&Bcd%GHG>aj(wjsI*=O>qg>UnQ5~j
z=eV|BMg@s#m;L%pJ)5RENuwU=R0WMBhBiW7o#i}rlG4#5ZDUjRSa=`Plu#w%B`C$N
z(;&2$llB909??3o&fn(z?J9F?WqD<B>;KhDS6Yp*?cS)QjtnT^a+xb_X5}DL&Qs{#
z?=7`&Y~6Fp_%(9vMKiF8HfcxR=<CqBrA!*3Ye(v&wVFq#^7fK-h3`mHR;KS>o0auv
z_q>s3y7KCU*_ODI6J+IW*=v!hp&aNkC~@B;F{`@wufgMIJ{Em)%}J(mRd82~uKPNE
zu!45VT#b~I5H)6^M@|hh?PQ`$a((5ZmR_kKRwzf4qZ=wC=HgJvLU}~a#5@JmHKeM~
zcQ+dhueyjH6-vS(Hi{zy4lKXvX09`YYnog=urAe8uFQH2W~4-u2I{*$(n5sIJAG7C
T@Rc+s5Lgrh10CRyRonjp5+F85

literal 0
HcmV?d00001

diff --git a/_static/locales/id/LC_MESSAGES/booktheme.po b/_static/locales/id/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..9ffb56f
--- /dev/null
+++ b/_static/locales/id/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: id\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema oleh"
+
+msgid "Open an issue"
+msgstr "Buka masalah"
+
+msgid "Contents"
+msgstr "Isi"
+
+msgid "Download notebook file"
+msgstr "Unduh file notebook"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema Buku Sphinx"
+
+msgid "Fullscreen mode"
+msgstr "Mode layar penuh"
+
+msgid "Edit this page"
+msgstr "Edit halaman ini"
+
+msgid "By"
+msgstr "Oleh"
+
+msgid "Copyright"
+msgstr "hak cipta"
+
+msgid "Source repository"
+msgstr "Repositori sumber"
+
+msgid "previous page"
+msgstr "halaman sebelumnya"
+
+msgid "next page"
+msgstr "halaman selanjutnya"
+
+msgid "Toggle navigation"
+msgstr "Alihkan navigasi"
+
+msgid "repository"
+msgstr "gudang"
+
+msgid "suggest edit"
+msgstr "menyarankan edit"
+
+msgid "open issue"
+msgstr "masalah terbuka"
+
+msgid "Launch"
+msgstr "Meluncurkan"
+
+msgid "Print to PDF"
+msgstr "Cetak ke PDF"
+
+msgid "By the"
+msgstr "Oleh"
+
+msgid "Last updated on"
+msgstr "Terakhir diperbarui saat"
+
+msgid "Download source file"
+msgstr "Unduh file sumber"
+
+msgid "Download this page"
+msgstr "Unduh halaman ini"
diff --git a/_static/locales/it/LC_MESSAGES/booktheme.mo b/_static/locales/it/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..53ba476edd2df2a802917e9df402257ceca1a130
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/it/LC_MESSAGES/booktheme.po b/_static/locales/it/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..04308dd
--- /dev/null
+++ b/_static/locales/it/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: it\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema di"
+
+msgid "Open an issue"
+msgstr "Apri un problema"
+
+msgid "Contents"
+msgstr "Contenuti"
+
+msgid "Download notebook file"
+msgstr "Scarica il file del taccuino"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema del libro della Sfinge"
+
+msgid "Fullscreen mode"
+msgstr "Modalità schermo intero"
+
+msgid "Edit this page"
+msgstr "Modifica questa pagina"
+
+msgid "By"
+msgstr "Di"
+
+msgid "Copyright"
+msgstr "Diritto d'autore"
+
+msgid "Source repository"
+msgstr "Repository di origine"
+
+msgid "previous page"
+msgstr "pagina precedente"
+
+msgid "next page"
+msgstr "pagina successiva"
+
+msgid "Toggle navigation"
+msgstr "Attiva / disattiva la navigazione"
+
+msgid "repository"
+msgstr "repository"
+
+msgid "suggest edit"
+msgstr "suggerisci modifica"
+
+msgid "open issue"
+msgstr "questione aperta"
+
+msgid "Launch"
+msgstr "Lanciare"
+
+msgid "Print to PDF"
+msgstr "Stampa in PDF"
+
+msgid "By the"
+msgstr "Dal"
+
+msgid "Last updated on"
+msgstr "Ultimo aggiornamento il"
+
+msgid "Download source file"
+msgstr "Scarica il file sorgente"
+
+msgid "Download this page"
+msgstr "Scarica questa pagina"
diff --git a/_static/locales/iw/LC_MESSAGES/booktheme.mo b/_static/locales/iw/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..a45c6575e469914582f8223ac54793afc2f26575
GIT binary patch
literal 1445
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F;x7>$;pPAU

literal 0
HcmV?d00001

diff --git a/_static/locales/iw/LC_MESSAGES/booktheme.po b/_static/locales/iw/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..4ea190d
--- /dev/null
+++ b/_static/locales/iw/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: iw\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "נושא מאת"
+
+msgid "Open an issue"
+msgstr "פתח גיליון"
+
+msgid "Contents"
+msgstr "תוכן"
+
+msgid "Download notebook file"
+msgstr "הורד קובץ מחברת"
+
+msgid "Sphinx Book Theme"
+msgstr "נושא ספר ספינקס"
+
+msgid "Fullscreen mode"
+msgstr "מצב מסך מלא"
+
+msgid "Edit this page"
+msgstr "ערוך דף זה"
+
+msgid "By"
+msgstr "על ידי"
+
+msgid "Copyright"
+msgstr "זכויות יוצרים"
+
+msgid "Source repository"
+msgstr "מאגר המקורות"
+
+msgid "previous page"
+msgstr "עמוד קודם"
+
+msgid "next page"
+msgstr "עמוד הבא"
+
+msgid "Toggle navigation"
+msgstr "החלף ניווט"
+
+msgid "repository"
+msgstr "מאגר"
+
+msgid "suggest edit"
+msgstr "מציע לערוך"
+
+msgid "open issue"
+msgstr "בעיה פתוחה"
+
+msgid "Launch"
+msgstr "לְהַשִׁיק"
+
+msgid "Print to PDF"
+msgstr "הדפס לקובץ PDF"
+
+msgid "By the"
+msgstr "דרך"
+
+msgid "Last updated on"
+msgstr "עודכן לאחרונה ב"
+
+msgid "Download source file"
+msgstr "הורד את קובץ המקור"
+
+msgid "Download this page"
+msgstr "הורד דף זה"
diff --git a/_static/locales/ja/LC_MESSAGES/booktheme.mo b/_static/locales/ja/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..1cefd29ce3cc08792667a82dc7ff47e9843107be
GIT binary patch
literal 1471
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literal 0
HcmV?d00001

diff --git a/_static/locales/ja/LC_MESSAGES/booktheme.po b/_static/locales/ja/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..77d5a09
--- /dev/null
+++ b/_static/locales/ja/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ja\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "のテーマ"
+
+msgid "Open an issue"
+msgstr "問題を報告"
+
+msgid "Contents"
+msgstr "目次"
+
+msgid "Download notebook file"
+msgstr "ノートブックファイルをダウンロード"
+
+msgid "Sphinx Book Theme"
+msgstr "スフィンクスの本のテーマ"
+
+msgid "Fullscreen mode"
+msgstr "全画面モード"
+
+msgid "Edit this page"
+msgstr "このページを編集"
+
+msgid "By"
+msgstr "著者"
+
+msgid "Copyright"
+msgstr "Copyright"
+
+msgid "Source repository"
+msgstr "ソースリポジトリ"
+
+msgid "previous page"
+msgstr "前のページ"
+
+msgid "next page"
+msgstr "次のページ"
+
+msgid "Toggle navigation"
+msgstr "ナビゲーションを切り替え"
+
+msgid "repository"
+msgstr "リポジトリ"
+
+msgid "suggest edit"
+msgstr "編集を提案する"
+
+msgid "open issue"
+msgstr "未解決の問題"
+
+msgid "Launch"
+msgstr "起動"
+
+msgid "Print to PDF"
+msgstr "PDFに印刷"
+
+msgid "By the"
+msgstr "によって"
+
+msgid "Last updated on"
+msgstr "最終更新日"
+
+msgid "Download source file"
+msgstr "ソースファイルをダウンロード"
+
+msgid "Download this page"
+msgstr "このページをダウンロード"
diff --git a/_static/locales/ko/LC_MESSAGES/booktheme.mo b/_static/locales/ko/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..06c7ec938b4975c721caff60b956e343eef11570
GIT binary patch
literal 1375
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literal 0
HcmV?d00001

diff --git a/_static/locales/ko/LC_MESSAGES/booktheme.po b/_static/locales/ko/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..6ee3d78
--- /dev/null
+++ b/_static/locales/ko/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ko\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "테마별"
+
+msgid "Open an issue"
+msgstr "이슈 열기"
+
+msgid "Contents"
+msgstr "내용"
+
+msgid "Download notebook file"
+msgstr "노트북 파일 다운로드"
+
+msgid "Sphinx Book Theme"
+msgstr "스핑크스 도서 테마"
+
+msgid "Fullscreen mode"
+msgstr "전체 화면으로보기"
+
+msgid "Edit this page"
+msgstr "이 페이지 편집"
+
+msgid "By"
+msgstr "으로"
+
+msgid "Copyright"
+msgstr "저작권"
+
+msgid "Source repository"
+msgstr "소스 저장소"
+
+msgid "previous page"
+msgstr "이전 페이지"
+
+msgid "next page"
+msgstr "다음 페이지"
+
+msgid "Toggle navigation"
+msgstr "탐색 전환"
+
+msgid "repository"
+msgstr "저장소"
+
+msgid "suggest edit"
+msgstr "편집 제안"
+
+msgid "open issue"
+msgstr "열린 문제"
+
+msgid "Launch"
+msgstr "시작하다"
+
+msgid "Print to PDF"
+msgstr "PDF로 인쇄"
+
+msgid "By the"
+msgstr "에 의해"
+
+msgid "Last updated on"
+msgstr "마지막 업데이트"
+
+msgid "Download source file"
+msgstr "소스 파일 다운로드"
+
+msgid "Download this page"
+msgstr "이 페이지 다운로드"
diff --git a/_static/locales/lt/LC_MESSAGES/booktheme.mo b/_static/locales/lt/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..4468ba04bc134a84fea5e3c973461cf02c9c2da3
GIT binary patch
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zZOLY+Fx##<<Ci)qd?52?bQCIW>3{(8<Tx*Q1-TMM%b)wstrt>W!QLNCjg(=>2Jsvw
ClWZvf

literal 0
HcmV?d00001

diff --git a/_static/locales/lt/LC_MESSAGES/booktheme.po b/_static/locales/lt/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..01be267
--- /dev/null
+++ b/_static/locales/lt/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: lt\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema"
+
+msgid "Open an issue"
+msgstr "Atidarykite problemą"
+
+msgid "Contents"
+msgstr "Turinys"
+
+msgid "Download notebook file"
+msgstr "Atsisiųsti nešiojamojo kompiuterio failą"
+
+msgid "Sphinx Book Theme"
+msgstr "Sfinkso knygos tema"
+
+msgid "Fullscreen mode"
+msgstr "Pilno ekrano režimas"
+
+msgid "Edit this page"
+msgstr "Redaguoti šį puslapį"
+
+msgid "By"
+msgstr "Iki"
+
+msgid "Copyright"
+msgstr "Autorių teisės"
+
+msgid "Source repository"
+msgstr "Šaltinio saugykla"
+
+msgid "previous page"
+msgstr "Ankstesnis puslapis"
+
+msgid "next page"
+msgstr "Kitas puslapis"
+
+msgid "Toggle navigation"
+msgstr "Perjungti naršymą"
+
+msgid "repository"
+msgstr "saugykla"
+
+msgid "suggest edit"
+msgstr "pasiūlyti redaguoti"
+
+msgid "open issue"
+msgstr "atviras klausimas"
+
+msgid "Launch"
+msgstr "Paleiskite"
+
+msgid "Print to PDF"
+msgstr "Spausdinti į PDF"
+
+msgid "By the"
+msgstr "Prie"
+
+msgid "Last updated on"
+msgstr "Paskutinį kartą atnaujinta"
+
+msgid "Download source file"
+msgstr "Atsisiųsti šaltinio failą"
+
+msgid "Download this page"
+msgstr "Atsisiųskite šį puslapį"
diff --git a/_static/locales/lv/LC_MESSAGES/booktheme.mo b/_static/locales/lv/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..74aa4d8985d96a07c4c9be96f006f3b58d884342
GIT binary patch
literal 1404
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z$hD`+d1p{2ugmVX^Rv)XwpuMi|K_@C9{X=v^;%!ucx$~w8wptj+VHfeW0EJ?h=xP`
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A2mk;8

literal 0
HcmV?d00001

diff --git a/_static/locales/lv/LC_MESSAGES/booktheme.po b/_static/locales/lv/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..993a1e4
--- /dev/null
+++ b/_static/locales/lv/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: lv\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Autora tēma"
+
+msgid "Open an issue"
+msgstr "Atveriet problēmu"
+
+msgid "Contents"
+msgstr "Saturs"
+
+msgid "Download notebook file"
+msgstr "Lejupielādēt piezīmju grāmatiņu"
+
+msgid "Sphinx Book Theme"
+msgstr "Sfinksa grāmatas tēma"
+
+msgid "Fullscreen mode"
+msgstr "Pilnekrāna režīms"
+
+msgid "Edit this page"
+msgstr "Rediģēt šo lapu"
+
+msgid "By"
+msgstr "Autors"
+
+msgid "Copyright"
+msgstr "Autortiesības"
+
+msgid "Source repository"
+msgstr "Avota krātuve"
+
+msgid "previous page"
+msgstr "iepriekšējā lapa"
+
+msgid "next page"
+msgstr "nākamā lapaspuse"
+
+msgid "Toggle navigation"
+msgstr "Pārslēgt navigāciju"
+
+msgid "repository"
+msgstr "krātuve"
+
+msgid "suggest edit"
+msgstr "ieteikt rediģēt"
+
+msgid "open issue"
+msgstr "atklāts jautājums"
+
+msgid "Launch"
+msgstr "Uzsākt"
+
+msgid "Print to PDF"
+msgstr "Drukāt PDF formātā"
+
+msgid "By the"
+msgstr "Ar"
+
+msgid "Last updated on"
+msgstr "Pēdējoreiz atjaunināts"
+
+msgid "Download source file"
+msgstr "Lejupielādēt avota failu"
+
+msgid "Download this page"
+msgstr "Lejupielādējiet šo lapu"
diff --git a/_static/locales/ml/LC_MESSAGES/booktheme.mo b/_static/locales/ml/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..2736e8fcf6f9e923c2403307f0b366086d37b335
GIT binary patch
literal 1883
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zC_?O6<R^=s5)(<fn8n>*AzH~{-A|&9)JdV{ljJRVAnvQR<vbZ=ZMAN(=*78AqplK@
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literal 0
HcmV?d00001

diff --git a/_static/locales/ml/LC_MESSAGES/booktheme.po b/_static/locales/ml/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..81daf7c
--- /dev/null
+++ b/_static/locales/ml/LC_MESSAGES/booktheme.po
@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ml\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "പ്രമേയം"
+
+msgid "Open an issue"
+msgstr "ഒരു പ്രശ്നം തുറക്കുക"
+
+msgid "Download notebook file"
+msgstr "നോട്ട്ബുക്ക് ഫയൽ ഡൺലോഡ് ചെയ്യുക"
+
+msgid "Sphinx Book Theme"
+msgstr "സ്ഫിങ്ക്സ് പുസ്തക തീം"
+
+msgid "Edit this page"
+msgstr "ഈ പേജ് എഡിറ്റുചെയ്യുക"
+
+msgid "By"
+msgstr "എഴുതിയത്"
+
+msgid "Copyright"
+msgstr "പകർപ്പവകാശം"
+
+msgid "Source repository"
+msgstr "ഉറവിട ശേഖരം"
+
+msgid "previous page"
+msgstr "മുൻപത്തെ താൾ"
+
+msgid "next page"
+msgstr "അടുത്ത പേജ്"
+
+msgid "Toggle navigation"
+msgstr "നാവിഗേഷൻ ടോഗിൾ ചെയ്യുക"
+
+msgid "suggest edit"
+msgstr "എഡിറ്റുചെയ്യാൻ നിർദ്ദേശിക്കുക"
+
+msgid "open issue"
+msgstr "തുറന്ന പ്രശ്നം"
+
+msgid "Launch"
+msgstr "സമാരംഭിക്കുക"
+
+msgid "Print to PDF"
+msgstr "PDF- ലേക്ക് പ്രിന്റുചെയ്യുക"
+
+msgid "By the"
+msgstr "എഴുതിയത്"
+
+msgid "Last updated on"
+msgstr "അവസാനം അപ്‌ഡേറ്റുചെയ്‌തത്"
+
+msgid "Download source file"
+msgstr "ഉറവിട ഫയൽ ഡൗൺലോഡുചെയ്യുക"
+
+msgid "Download this page"
+msgstr "ഈ പേജ് ഡൗൺലോഡുചെയ്യുക"
diff --git a/_static/locales/mr/LC_MESSAGES/booktheme.mo b/_static/locales/mr/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..fe530100d7715cdc19a6f9db33a971665835f3c4
GIT binary patch
literal 1674
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A6951J

literal 0
HcmV?d00001

diff --git a/_static/locales/mr/LC_MESSAGES/booktheme.po b/_static/locales/mr/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..fd857bf
--- /dev/null
+++ b/_static/locales/mr/LC_MESSAGES/booktheme.po
@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: mr\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "द्वारा थीम"
+
+msgid "Open an issue"
+msgstr "एक मुद्दा उघडा"
+
+msgid "Download notebook file"
+msgstr "नोटबुक फाईल डाउनलोड करा"
+
+msgid "Sphinx Book Theme"
+msgstr "स्फिंक्स बुक थीम"
+
+msgid "Edit this page"
+msgstr "हे पृष्ठ संपादित करा"
+
+msgid "By"
+msgstr "द्वारा"
+
+msgid "Copyright"
+msgstr "कॉपीराइट"
+
+msgid "Source repository"
+msgstr "स्त्रोत भांडार"
+
+msgid "previous page"
+msgstr "मागील पान"
+
+msgid "next page"
+msgstr "पुढील पृष्ठ"
+
+msgid "Toggle navigation"
+msgstr "नेव्हिगेशन टॉगल करा"
+
+msgid "suggest edit"
+msgstr "संपादन सुचवा"
+
+msgid "open issue"
+msgstr "खुला मुद्दा"
+
+msgid "Launch"
+msgstr "लाँच करा"
+
+msgid "Print to PDF"
+msgstr "पीडीएफवर मुद्रित करा"
+
+msgid "By the"
+msgstr "द्वारा"
+
+msgid "Last updated on"
+msgstr "अखेरचे अद्यतनित"
+
+msgid "Download source file"
+msgstr "स्त्रोत फाइल डाउनलोड करा"
+
+msgid "Download this page"
+msgstr "हे पृष्ठ डाउनलोड करा"
diff --git a/_static/locales/ms/LC_MESSAGES/booktheme.mo b/_static/locales/ms/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..f02603fa2522a40060bd3f1b5d65052c77530de6
GIT binary patch
literal 1213
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zic<%vtlUs0G-<k!rV^=1q>K1wUB*6INTU1FI=E=_I%q^eqhYw#(!$c*-uvW@iB{KW
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z303fZ$OFyt{}&g^zO;WEWTFryjYX?^kbhtFq!oFlEKgJ}OW}A9HMBVqn5vG2&4p$&
zAr~BvaFnsG^hhh0!@1tw9jM|>;2yki7=)(TY<OX)9L&@d%}AYMC3$t|i|6R7w880t
eV9EtF-J(E&`s>V{?8_pQ^c*8Iog%4v$iD&q$RjNP

literal 0
HcmV?d00001

diff --git a/_static/locales/ms/LC_MESSAGES/booktheme.po b/_static/locales/ms/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..b616d70
--- /dev/null
+++ b/_static/locales/ms/LC_MESSAGES/booktheme.po
@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ms\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema oleh"
+
+msgid "Open an issue"
+msgstr "Buka masalah"
+
+msgid "Download notebook file"
+msgstr "Muat turun fail buku nota"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema Buku Sphinx"
+
+msgid "Edit this page"
+msgstr "Edit halaman ini"
+
+msgid "By"
+msgstr "Oleh"
+
+msgid "Copyright"
+msgstr "hak cipta"
+
+msgid "Source repository"
+msgstr "Repositori sumber"
+
+msgid "previous page"
+msgstr "halaman sebelumnya"
+
+msgid "next page"
+msgstr "muka surat seterusnya"
+
+msgid "Toggle navigation"
+msgstr "Togol navigasi"
+
+msgid "suggest edit"
+msgstr "cadangkan edit"
+
+msgid "open issue"
+msgstr "isu terbuka"
+
+msgid "Launch"
+msgstr "Lancarkan"
+
+msgid "Print to PDF"
+msgstr "Cetak ke PDF"
+
+msgid "By the"
+msgstr "Oleh"
+
+msgid "Last updated on"
+msgstr "Terakhir dikemas kini pada"
+
+msgid "Download source file"
+msgstr "Muat turun fail sumber"
+
+msgid "Download this page"
+msgstr "Muat turun halaman ini"
diff --git a/_static/locales/nl/LC_MESSAGES/booktheme.mo b/_static/locales/nl/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..e59e7ecb308a7648cd23aa6342a9ad98a61d0009
GIT binary patch
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HcmV?d00001

diff --git a/_static/locales/nl/LC_MESSAGES/booktheme.po b/_static/locales/nl/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..f16f4bc
--- /dev/null
+++ b/_static/locales/nl/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: nl\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Thema door de"
+
+msgid "Open an issue"
+msgstr "Open een probleem"
+
+msgid "Contents"
+msgstr "Inhoud"
+
+msgid "Download notebook file"
+msgstr "Download notebookbestand"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx-boekthema"
+
+msgid "Fullscreen mode"
+msgstr "Volledig scherm"
+
+msgid "Edit this page"
+msgstr "bewerk deze pagina"
+
+msgid "By"
+msgstr "Door"
+
+msgid "Copyright"
+msgstr "auteursrechten"
+
+msgid "Source repository"
+msgstr "Bronopslagplaats"
+
+msgid "previous page"
+msgstr "vorige pagina"
+
+msgid "next page"
+msgstr "volgende bladzijde"
+
+msgid "Toggle navigation"
+msgstr "Schakel navigatie"
+
+msgid "repository"
+msgstr "repository"
+
+msgid "suggest edit"
+msgstr "suggereren bewerken"
+
+msgid "open issue"
+msgstr "open probleem"
+
+msgid "Launch"
+msgstr "Lancering"
+
+msgid "Print to PDF"
+msgstr "Afdrukken naar pdf"
+
+msgid "By the"
+msgstr "Door de"
+
+msgid "Last updated on"
+msgstr "Laatst geupdate op"
+
+msgid "Download source file"
+msgstr "Download het bronbestand"
+
+msgid "Download this page"
+msgstr "Download deze pagina"
diff --git a/_static/locales/no/LC_MESSAGES/booktheme.mo b/_static/locales/no/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..6cd15c88de675226c00ca4d0430171075e5559ff
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/no/LC_MESSAGES/booktheme.po b/_static/locales/no/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..b1d304e
--- /dev/null
+++ b/_static/locales/no/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: no\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema av"
+
+msgid "Open an issue"
+msgstr "Åpne et problem"
+
+msgid "Contents"
+msgstr "Innhold"
+
+msgid "Download notebook file"
+msgstr "Last ned notatbokfilen"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx boktema"
+
+msgid "Fullscreen mode"
+msgstr "Fullskjerm-modus"
+
+msgid "Edit this page"
+msgstr "Rediger denne siden"
+
+msgid "By"
+msgstr "Av"
+
+msgid "Copyright"
+msgstr "opphavsrett"
+
+msgid "Source repository"
+msgstr "Kildedepot"
+
+msgid "previous page"
+msgstr "forrige side"
+
+msgid "next page"
+msgstr "neste side"
+
+msgid "Toggle navigation"
+msgstr "Bytt navigasjon"
+
+msgid "repository"
+msgstr "oppbevaringssted"
+
+msgid "suggest edit"
+msgstr "foreslå redigering"
+
+msgid "open issue"
+msgstr "åpent nummer"
+
+msgid "Launch"
+msgstr "Start"
+
+msgid "Print to PDF"
+msgstr "Skriv ut til PDF"
+
+msgid "By the"
+msgstr "Ved"
+
+msgid "Last updated on"
+msgstr "Sist oppdatert den"
+
+msgid "Download source file"
+msgstr "Last ned kildefilen"
+
+msgid "Download this page"
+msgstr "Last ned denne siden"
diff --git a/_static/locales/pl/LC_MESSAGES/booktheme.mo b/_static/locales/pl/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..9ebb584f77091f5666db4194ecd4f707396cbbca
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/pl/LC_MESSAGES/booktheme.po b/_static/locales/pl/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..80d2c89
--- /dev/null
+++ b/_static/locales/pl/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: pl\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Motyw autorstwa"
+
+msgid "Open an issue"
+msgstr "Otwórz problem"
+
+msgid "Contents"
+msgstr "Zawartość"
+
+msgid "Download notebook file"
+msgstr "Pobierz plik notatnika"
+
+msgid "Sphinx Book Theme"
+msgstr "Motyw książki Sphinx"
+
+msgid "Fullscreen mode"
+msgstr "Pełny ekran"
+
+msgid "Edit this page"
+msgstr "Edytuj tę strone"
+
+msgid "By"
+msgstr "Przez"
+
+msgid "Copyright"
+msgstr "prawa autorskie"
+
+msgid "Source repository"
+msgstr "Repozytorium źródłowe"
+
+msgid "previous page"
+msgstr "Poprzednia strona"
+
+msgid "next page"
+msgstr "Następna strona"
+
+msgid "Toggle navigation"
+msgstr "Przełącz nawigację"
+
+msgid "repository"
+msgstr "magazyn"
+
+msgid "suggest edit"
+msgstr "zaproponuj edycję"
+
+msgid "open issue"
+msgstr "otwarty problem"
+
+msgid "Launch"
+msgstr "Uruchomić"
+
+msgid "Print to PDF"
+msgstr "Drukuj do PDF"
+
+msgid "By the"
+msgstr "Przez"
+
+msgid "Last updated on"
+msgstr "Ostatnia aktualizacja"
+
+msgid "Download source file"
+msgstr "Pobierz plik źródłowy"
+
+msgid "Download this page"
+msgstr "Pobierz tę stronę"
diff --git a/_static/locales/pt/LC_MESSAGES/booktheme.mo b/_static/locales/pt/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..d0ddb8728e1d5ef72dddc1537f66aa32251a83c8
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/pt/LC_MESSAGES/booktheme.po b/_static/locales/pt/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..45ac847
--- /dev/null
+++ b/_static/locales/pt/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: pt\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema por"
+
+msgid "Open an issue"
+msgstr "Abra um problema"
+
+msgid "Contents"
+msgstr "Conteúdo"
+
+msgid "Download notebook file"
+msgstr "Baixar arquivo de notebook"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema do livro Sphinx"
+
+msgid "Fullscreen mode"
+msgstr "Modo tela cheia"
+
+msgid "Edit this page"
+msgstr "Edite essa página"
+
+msgid "By"
+msgstr "De"
+
+msgid "Copyright"
+msgstr "direito autoral"
+
+msgid "Source repository"
+msgstr "Repositório fonte"
+
+msgid "previous page"
+msgstr "página anterior"
+
+msgid "next page"
+msgstr "próxima página"
+
+msgid "Toggle navigation"
+msgstr "Alternar de navegação"
+
+msgid "repository"
+msgstr "repositório"
+
+msgid "suggest edit"
+msgstr "sugerir edição"
+
+msgid "open issue"
+msgstr "questão aberta"
+
+msgid "Launch"
+msgstr "Lançamento"
+
+msgid "Print to PDF"
+msgstr "Imprimir em PDF"
+
+msgid "By the"
+msgstr "Pelo"
+
+msgid "Last updated on"
+msgstr "Última atualização em"
+
+msgid "Download source file"
+msgstr "Baixar arquivo fonte"
+
+msgid "Download this page"
+msgstr "Baixe esta página"
diff --git a/_static/locales/ro/LC_MESSAGES/booktheme.mo b/_static/locales/ro/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..3c36ab1df7c589ad82614599b8c91f072a25d4a6
GIT binary patch
literal 1390
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literal 0
HcmV?d00001

diff --git a/_static/locales/ro/LC_MESSAGES/booktheme.po b/_static/locales/ro/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..532b3b8
--- /dev/null
+++ b/_static/locales/ro/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ro\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema de"
+
+msgid "Open an issue"
+msgstr "Deschideți o problemă"
+
+msgid "Contents"
+msgstr "Cuprins"
+
+msgid "Download notebook file"
+msgstr "Descărcați fișierul notebook"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema Sphinx Book"
+
+msgid "Fullscreen mode"
+msgstr "Modul ecran întreg"
+
+msgid "Edit this page"
+msgstr "Editați această pagină"
+
+msgid "By"
+msgstr "De"
+
+msgid "Copyright"
+msgstr "Drepturi de autor"
+
+msgid "Source repository"
+msgstr "Depozit sursă"
+
+msgid "previous page"
+msgstr "pagina anterioară"
+
+msgid "next page"
+msgstr "pagina următoare"
+
+msgid "Toggle navigation"
+msgstr "Comutare navigare"
+
+msgid "repository"
+msgstr "repertoriu"
+
+msgid "suggest edit"
+msgstr "sugerează editare"
+
+msgid "open issue"
+msgstr "problema deschisă"
+
+msgid "Launch"
+msgstr "Lansa"
+
+msgid "Print to PDF"
+msgstr "Imprimați în PDF"
+
+msgid "By the"
+msgstr "Langa"
+
+msgid "Last updated on"
+msgstr "Ultima actualizare la"
+
+msgid "Download source file"
+msgstr "Descărcați fișierul sursă"
+
+msgid "Download this page"
+msgstr "Descarcă această pagină"
diff --git a/_static/locales/ru/LC_MESSAGES/booktheme.mo b/_static/locales/ru/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..6b8ca41f36ebf869818399a9584cdb15619bea78
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/ru/LC_MESSAGES/booktheme.po b/_static/locales/ru/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..b718b48
--- /dev/null
+++ b/_static/locales/ru/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ru\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Тема от"
+
+msgid "Open an issue"
+msgstr "Открыть вопрос"
+
+msgid "Contents"
+msgstr "Содержание"
+
+msgid "Download notebook file"
+msgstr "Скачать файл записной книжки"
+
+msgid "Sphinx Book Theme"
+msgstr "Тема книги Сфинкс"
+
+msgid "Fullscreen mode"
+msgstr "Полноэкранный режим"
+
+msgid "Edit this page"
+msgstr "Редактировать эту страницу"
+
+msgid "By"
+msgstr "По"
+
+msgid "Copyright"
+msgstr "авторское право"
+
+msgid "Source repository"
+msgstr "Исходный репозиторий"
+
+msgid "previous page"
+msgstr "Предыдущая страница"
+
+msgid "next page"
+msgstr "Следующая страница"
+
+msgid "Toggle navigation"
+msgstr "Переключить навигацию"
+
+msgid "repository"
+msgstr "хранилище"
+
+msgid "suggest edit"
+msgstr "предложить редактировать"
+
+msgid "open issue"
+msgstr "открытый вопрос"
+
+msgid "Launch"
+msgstr "Запуск"
+
+msgid "Print to PDF"
+msgstr "Распечатать в PDF"
+
+msgid "By the"
+msgstr "Посредством"
+
+msgid "Last updated on"
+msgstr "Последнее обновление"
+
+msgid "Download source file"
+msgstr "Скачать исходный файл"
+
+msgid "Download this page"
+msgstr "Загрузите эту страницу"
diff --git a/_static/locales/sk/LC_MESSAGES/booktheme.mo b/_static/locales/sk/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..59bd0ddfa341477cf5ccfdc88f4c3e6127046f7a
GIT binary patch
literal 1393
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Di}h+h

literal 0
HcmV?d00001

diff --git a/_static/locales/sk/LC_MESSAGES/booktheme.po b/_static/locales/sk/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..f6c423b
--- /dev/null
+++ b/_static/locales/sk/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: sk\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Téma od"
+
+msgid "Open an issue"
+msgstr "Otvorte problém"
+
+msgid "Contents"
+msgstr "Obsah"
+
+msgid "Download notebook file"
+msgstr "Stiahnite si zošit"
+
+msgid "Sphinx Book Theme"
+msgstr "Téma knihy Sfinga"
+
+msgid "Fullscreen mode"
+msgstr "Režim celej obrazovky"
+
+msgid "Edit this page"
+msgstr "Upraviť túto stránku"
+
+msgid "By"
+msgstr "Autor:"
+
+msgid "Copyright"
+msgstr "Autorské práva"
+
+msgid "Source repository"
+msgstr "Zdrojové úložisko"
+
+msgid "previous page"
+msgstr "predchádzajúca strana"
+
+msgid "next page"
+msgstr "ďalšia strana"
+
+msgid "Toggle navigation"
+msgstr "Prepnúť navigáciu"
+
+msgid "repository"
+msgstr "Úložisko"
+
+msgid "suggest edit"
+msgstr "navrhnúť úpravu"
+
+msgid "open issue"
+msgstr "otvorené vydanie"
+
+msgid "Launch"
+msgstr "Spustiť"
+
+msgid "Print to PDF"
+msgstr "Tlač do PDF"
+
+msgid "By the"
+msgstr "Podľa"
+
+msgid "Last updated on"
+msgstr "Posledná aktualizácia dňa"
+
+msgid "Download source file"
+msgstr "Stiahnite si zdrojový súbor"
+
+msgid "Download this page"
+msgstr "Stiahnite si túto stránku"
diff --git a/_static/locales/sl/LC_MESSAGES/booktheme.mo b/_static/locales/sl/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..87bf26de683cb18c73bd23c2b4c57ef6a02545ec
GIT binary patch
literal 1374
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L??Y>WljW5^x#&@4

literal 0
HcmV?d00001

diff --git a/_static/locales/sl/LC_MESSAGES/booktheme.po b/_static/locales/sl/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..9822dc5
--- /dev/null
+++ b/_static/locales/sl/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: sl\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema avtorja"
+
+msgid "Open an issue"
+msgstr "Odprite številko"
+
+msgid "Contents"
+msgstr "Vsebina"
+
+msgid "Download notebook file"
+msgstr "Prenesite datoteko zvezka"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema knjige Sphinx"
+
+msgid "Fullscreen mode"
+msgstr "Celozaslonski način"
+
+msgid "Edit this page"
+msgstr "Uredite to stran"
+
+msgid "By"
+msgstr "Avtor"
+
+msgid "Copyright"
+msgstr "avtorske pravice"
+
+msgid "Source repository"
+msgstr "Izvorno skladišče"
+
+msgid "previous page"
+msgstr "Prejšnja stran"
+
+msgid "next page"
+msgstr "Naslednja stran"
+
+msgid "Toggle navigation"
+msgstr "Preklopi navigacijo"
+
+msgid "repository"
+msgstr "odlagališče"
+
+msgid "suggest edit"
+msgstr "predlagajte urejanje"
+
+msgid "open issue"
+msgstr "odprto vprašanje"
+
+msgid "Launch"
+msgstr "Kosilo"
+
+msgid "Print to PDF"
+msgstr "Natisni v PDF"
+
+msgid "By the"
+msgstr "Avtor"
+
+msgid "Last updated on"
+msgstr "Nazadnje posodobljeno dne"
+
+msgid "Download source file"
+msgstr "Prenesite izvorno datoteko"
+
+msgid "Download this page"
+msgstr "Prenesite to stran"
diff --git a/_static/locales/sr/LC_MESSAGES/booktheme.mo b/_static/locales/sr/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..ec740f4852f3973fa72ed0c7f7cf59273b8dba41
GIT binary patch
literal 1679
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zI<H@r`sJ*0>D-xfGsC|hn|!@gG`2jy9GHrZ5ik|B9M_xHwWbqBCa%6aKU+RIj0+tv
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HD*E*gL}ZXP

literal 0
HcmV?d00001

diff --git a/_static/locales/sr/LC_MESSAGES/booktheme.po b/_static/locales/sr/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..e809230
--- /dev/null
+++ b/_static/locales/sr/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: sr\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Тхеме би"
+
+msgid "Open an issue"
+msgstr "Отворите издање"
+
+msgid "Contents"
+msgstr "Садржај"
+
+msgid "Download notebook file"
+msgstr "Преузмите датотеку бележнице"
+
+msgid "Sphinx Book Theme"
+msgstr "Тема књиге Спхинк"
+
+msgid "Fullscreen mode"
+msgstr "Режим целог екрана"
+
+msgid "Edit this page"
+msgstr "Уредите ову страницу"
+
+msgid "By"
+msgstr "Од стране"
+
+msgid "Copyright"
+msgstr "Ауторско право"
+
+msgid "Source repository"
+msgstr "Изворно спремиште"
+
+msgid "previous page"
+msgstr "Претходна страница"
+
+msgid "next page"
+msgstr "Следећа страна"
+
+msgid "Toggle navigation"
+msgstr "Укључи / искључи навигацију"
+
+msgid "repository"
+msgstr "спремиште"
+
+msgid "suggest edit"
+msgstr "предложи уређивање"
+
+msgid "open issue"
+msgstr "отворено издање"
+
+msgid "Launch"
+msgstr "Лансирање"
+
+msgid "Print to PDF"
+msgstr "Испис у ПДФ"
+
+msgid "By the"
+msgstr "Од"
+
+msgid "Last updated on"
+msgstr "Последње ажурирање"
+
+msgid "Download source file"
+msgstr "Преузми изворну датотеку"
+
+msgid "Download this page"
+msgstr "Преузмите ову страницу"
diff --git a/_static/locales/sv/LC_MESSAGES/booktheme.mo b/_static/locales/sv/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..b07dc76ff21128244172d2e415cc899555d8b49d
GIT binary patch
literal 1365
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literal 0
HcmV?d00001

diff --git a/_static/locales/sv/LC_MESSAGES/booktheme.po b/_static/locales/sv/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..2421b00
--- /dev/null
+++ b/_static/locales/sv/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: sv\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema av"
+
+msgid "Open an issue"
+msgstr "Öppna en problemrapport"
+
+msgid "Contents"
+msgstr "Innehåll"
+
+msgid "Download notebook file"
+msgstr "Ladda ner notebook-fil"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx Boktema"
+
+msgid "Fullscreen mode"
+msgstr "Fullskärmsläge"
+
+msgid "Edit this page"
+msgstr "Redigera den här sidan"
+
+msgid "By"
+msgstr "Av"
+
+msgid "Copyright"
+msgstr "Upphovsrätt"
+
+msgid "Source repository"
+msgstr "Källkodsrepositorium"
+
+msgid "previous page"
+msgstr "föregående sida"
+
+msgid "next page"
+msgstr "nästa sida"
+
+msgid "Toggle navigation"
+msgstr "Växla navigering"
+
+msgid "repository"
+msgstr "repositorium"
+
+msgid "suggest edit"
+msgstr "föreslå ändring"
+
+msgid "open issue"
+msgstr "öppna problemrapport"
+
+msgid "Launch"
+msgstr "Öppna"
+
+msgid "Print to PDF"
+msgstr "Skriv ut till PDF"
+
+msgid "By the"
+msgstr "Av den"
+
+msgid "Last updated on"
+msgstr "Senast uppdaterad den"
+
+msgid "Download source file"
+msgstr "Ladda ner källfil"
+
+msgid "Download this page"
+msgstr "Ladda ner den här sidan"
diff --git a/_static/locales/ta/LC_MESSAGES/booktheme.mo b/_static/locales/ta/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..29f52e1f6f1ec96aceb0f883d8ccc82c23eb35c2
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/ta/LC_MESSAGES/booktheme.po b/_static/locales/ta/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..500042f
--- /dev/null
+++ b/_static/locales/ta/LC_MESSAGES/booktheme.po
@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ta\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "வழங்கிய தீம்"
+
+msgid "Open an issue"
+msgstr "சிக்கலைத் திறக்கவும்"
+
+msgid "Download notebook file"
+msgstr "நோட்புக் கோப்பைப் பதிவிறக்கவும்"
+
+msgid "Sphinx Book Theme"
+msgstr "ஸ்பிங்க்ஸ் புத்தக தீம்"
+
+msgid "Edit this page"
+msgstr "இந்தப் பக்கத்தைத் திருத்தவும்"
+
+msgid "By"
+msgstr "வழங்கியவர்"
+
+msgid "Copyright"
+msgstr "பதிப்புரிமை"
+
+msgid "Source repository"
+msgstr "மூல களஞ்சியம்"
+
+msgid "previous page"
+msgstr "முந்தைய பக்கம்"
+
+msgid "next page"
+msgstr "அடுத்த பக்கம்"
+
+msgid "Toggle navigation"
+msgstr "வழிசெலுத்தலை நிலைமாற்று"
+
+msgid "suggest edit"
+msgstr "திருத்த பரிந்துரைக்கவும்"
+
+msgid "open issue"
+msgstr "திறந்த பிரச்சினை"
+
+msgid "Launch"
+msgstr "தொடங்க"
+
+msgid "Print to PDF"
+msgstr "PDF இல் அச்சிடுக"
+
+msgid "By the"
+msgstr "மூலம்"
+
+msgid "Last updated on"
+msgstr "கடைசியாக புதுப்பிக்கப்பட்டது"
+
+msgid "Download source file"
+msgstr "மூல கோப்பைப் பதிவிறக்குக"
+
+msgid "Download this page"
+msgstr "இந்தப் பக்கத்தைப் பதிவிறக்கவும்"
diff --git a/_static/locales/te/LC_MESSAGES/booktheme.mo b/_static/locales/te/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..0a5f4b46adfda1551ae6791c3c3782525b61be04
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/te/LC_MESSAGES/booktheme.po b/_static/locales/te/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..b1afebb
--- /dev/null
+++ b/_static/locales/te/LC_MESSAGES/booktheme.po
@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: te\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "ద్వారా థీమ్"
+
+msgid "Open an issue"
+msgstr "సమస్యను తెరవండి"
+
+msgid "Download notebook file"
+msgstr "నోట్బుక్ ఫైల్ను డౌన్లోడ్ చేయండి"
+
+msgid "Sphinx Book Theme"
+msgstr "సింహిక పుస్తక థీమ్"
+
+msgid "Edit this page"
+msgstr "ఈ పేజీని సవరించండి"
+
+msgid "By"
+msgstr "ద్వారా"
+
+msgid "Copyright"
+msgstr "కాపీరైట్"
+
+msgid "Source repository"
+msgstr "మూల రిపోజిటరీ"
+
+msgid "previous page"
+msgstr "ముందు పేజి"
+
+msgid "next page"
+msgstr "తరువాతి పేజీ"
+
+msgid "Toggle navigation"
+msgstr "నావిగేషన్‌ను టోగుల్ చేయండి"
+
+msgid "suggest edit"
+msgstr "సవరించమని సూచించండి"
+
+msgid "open issue"
+msgstr "ఓపెన్ ఇష్యూ"
+
+msgid "Launch"
+msgstr "ప్రారంభించండి"
+
+msgid "Print to PDF"
+msgstr "PDF కి ముద్రించండి"
+
+msgid "By the"
+msgstr "ద్వారా"
+
+msgid "Last updated on"
+msgstr "చివరిగా నవీకరించబడింది"
+
+msgid "Download source file"
+msgstr "మూల ఫైల్‌ను డౌన్‌లోడ్ చేయండి"
+
+msgid "Download this page"
+msgstr "ఈ పేజీని డౌన్‌లోడ్ చేయండి"
diff --git a/_static/locales/tg/LC_MESSAGES/booktheme.mo b/_static/locales/tg/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..b21c6c6340194fdf35f7e5660deb42479c8dbff9
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/tg/LC_MESSAGES/booktheme.po b/_static/locales/tg/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..29b8237
--- /dev/null
+++ b/_static/locales/tg/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: tg\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Мавзӯъи аз"
+
+msgid "Open an issue"
+msgstr "Масъаларо кушоед"
+
+msgid "Contents"
+msgstr "Мундариҷа"
+
+msgid "Download notebook file"
+msgstr "Файли дафтарро зеркашӣ кунед"
+
+msgid "Sphinx Book Theme"
+msgstr "Сфинкс Мавзӯи китоб"
+
+msgid "Fullscreen mode"
+msgstr "Ҳолати экрани пурра"
+
+msgid "Edit this page"
+msgstr "Ин саҳифаро таҳрир кунед"
+
+msgid "By"
+msgstr "Бо"
+
+msgid "Copyright"
+msgstr "Ҳуқуқи муаллиф"
+
+msgid "Source repository"
+msgstr "Анбори манбаъ"
+
+msgid "previous page"
+msgstr "саҳифаи қаблӣ"
+
+msgid "next page"
+msgstr "саҳифаи оянда"
+
+msgid "Toggle navigation"
+msgstr "Гузаришро иваз кунед"
+
+msgid "repository"
+msgstr "анбор"
+
+msgid "suggest edit"
+msgstr "пешниҳод вироиш"
+
+msgid "open issue"
+msgstr "барориши кушод"
+
+msgid "Launch"
+msgstr "Оғоз"
+
+msgid "Print to PDF"
+msgstr "Чоп ба PDF"
+
+msgid "By the"
+msgstr "Бо"
+
+msgid "Last updated on"
+msgstr "Last навсозӣ дар"
+
+msgid "Download source file"
+msgstr "Файли манбаъро зеркашӣ кунед"
+
+msgid "Download this page"
+msgstr "Ин саҳифаро зеркашӣ кунед"
diff --git a/_static/locales/th/LC_MESSAGES/booktheme.mo b/_static/locales/th/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..abede98aa11b163e580a26b545980ace31e61ccf
GIT binary patch
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zjT&US*r9DL+Oc6=XyNi4J`IP)4~3RpiSp}N5WkMWZ=`O(hjnrBo?i;ppCMASYj{fI
qV*6MBqwc03(drtRAFXAoSBd=B?a4S*sk|OB^ZqtY{YJQZ;_45RC*i9A

literal 0
HcmV?d00001

diff --git a/_static/locales/th/LC_MESSAGES/booktheme.po b/_static/locales/th/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..ac65ee0
--- /dev/null
+++ b/_static/locales/th/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: th\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "ธีมโดย"
+
+msgid "Open an issue"
+msgstr "เปิดปัญหา"
+
+msgid "Contents"
+msgstr "สารบัญ"
+
+msgid "Download notebook file"
+msgstr "ดาวน์โหลดไฟล์สมุดบันทึก"
+
+msgid "Sphinx Book Theme"
+msgstr "ธีมหนังสือสฟิงซ์"
+
+msgid "Fullscreen mode"
+msgstr "โหมดเต็มหน้าจอ"
+
+msgid "Edit this page"
+msgstr "แก้ไขหน้านี้"
+
+msgid "By"
+msgstr "โดย"
+
+msgid "Copyright"
+msgstr "ลิขสิทธิ์"
+
+msgid "Source repository"
+msgstr "ที่เก็บซอร์ส"
+
+msgid "previous page"
+msgstr "หน้าที่แล้ว"
+
+msgid "next page"
+msgstr "หน้าต่อไป"
+
+msgid "Toggle navigation"
+msgstr "ไม่ต้องสลับช่องทาง"
+
+msgid "repository"
+msgstr "ที่เก็บ"
+
+msgid "suggest edit"
+msgstr "แนะนำแก้ไข"
+
+msgid "open issue"
+msgstr "เปิดปัญหา"
+
+msgid "Launch"
+msgstr "เปิด"
+
+msgid "Print to PDF"
+msgstr "พิมพ์เป็น PDF"
+
+msgid "By the"
+msgstr "โดย"
+
+msgid "Last updated on"
+msgstr "ปรับปรุงล่าสุดเมื่อ"
+
+msgid "Download source file"
+msgstr "ดาวน์โหลดไฟล์ต้นฉบับ"
+
+msgid "Download this page"
+msgstr "ดาวน์โหลดหน้านี้"
diff --git a/_static/locales/tl/LC_MESSAGES/booktheme.mo b/_static/locales/tl/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..8df1b73310e0c606251d1abff7e6033d1f6b273f
GIT binary patch
literal 1273
zcmZ{iJ#P~+7{?8ixA4}MHz7bWh@lJz6qYJggw!_(YD=U9)PcpxxsJ)jKAr8h8TbH<
zl>mt^fEW=h3@|dWP{DwN#01}fk%9knmnKyup2YV%`|Ricw;%r;A9>CYr_e5-eL%a2
z_Gk|th%ew?a0@&DeghAKKfp8KZ;;mh1;@cLOg;`?0Z)LpKw38o9s}=zN5K_v43vGY
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zo5YHk8|!7$+74gUi5w0)8?u(%HR#*g@l+_u=40)Val5-HoaZ5pg_kk6hAoO<T5Wbe
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zYF}CuMg<%mawMf%5;BoQ3pVSzGB;`7b(Ndbym+ll7=Ee3C$CPI*s^AIft_~oQ`+M|
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literal 0
HcmV?d00001

diff --git a/_static/locales/tl/LC_MESSAGES/booktheme.po b/_static/locales/tl/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..662d66c
--- /dev/null
+++ b/_static/locales/tl/LC_MESSAGES/booktheme.po
@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: tl\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tema ng"
+
+msgid "Open an issue"
+msgstr "Magbukas ng isyu"
+
+msgid "Download notebook file"
+msgstr "Mag-download ng file ng notebook"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema ng Sphinx Book"
+
+msgid "Edit this page"
+msgstr "I-edit ang pahinang ito"
+
+msgid "By"
+msgstr "Ni"
+
+msgid "Copyright"
+msgstr "Copyright"
+
+msgid "Source repository"
+msgstr "Pinagmulan ng imbakan"
+
+msgid "previous page"
+msgstr "Nakaraang pahina"
+
+msgid "next page"
+msgstr "Susunod na pahina"
+
+msgid "Toggle navigation"
+msgstr "I-toggle ang pag-navigate"
+
+msgid "suggest edit"
+msgstr "iminumungkahi i-edit"
+
+msgid "open issue"
+msgstr "bukas na isyu"
+
+msgid "Launch"
+msgstr "Ilunsad"
+
+msgid "Print to PDF"
+msgstr "I-print sa PDF"
+
+msgid "By the"
+msgstr "Sa pamamagitan ng"
+
+msgid "Last updated on"
+msgstr "Huling na-update noong"
+
+msgid "Download source file"
+msgstr "Mag-download ng file ng pinagmulan"
+
+msgid "Download this page"
+msgstr "I-download ang pahinang ito"
diff --git a/_static/locales/tr/LC_MESSAGES/booktheme.mo b/_static/locales/tr/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..029ae18afb5360a8c238a052e8d3971761759d3d
GIT binary patch
literal 1373
zcmZ{izi%8x6vqdWKynFz!~~?sQXUOIiX{o62)3@sVLOWA2n!$d<J)(;liizH&CG_Z
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zo6h$Ap{&BCl*;`;;xXGI&@B^nMMIv5kwyPFiiuV?c-PnoHwMdQd*;PnG+qT~k=xL=
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literal 0
HcmV?d00001

diff --git a/_static/locales/tr/LC_MESSAGES/booktheme.po b/_static/locales/tr/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..d1ae723
--- /dev/null
+++ b/_static/locales/tr/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: tr\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Tarafından tema"
+
+msgid "Open an issue"
+msgstr "Bir sorunu açın"
+
+msgid "Contents"
+msgstr "İçindekiler"
+
+msgid "Download notebook file"
+msgstr "Defter dosyasını indirin"
+
+msgid "Sphinx Book Theme"
+msgstr "Sfenks Kitap Teması"
+
+msgid "Fullscreen mode"
+msgstr "Tam ekran modu"
+
+msgid "Edit this page"
+msgstr "Bu sayfayı düzenle"
+
+msgid "By"
+msgstr "Tarafından"
+
+msgid "Copyright"
+msgstr "Telif hakkı"
+
+msgid "Source repository"
+msgstr "Kaynak kod deposu"
+
+msgid "previous page"
+msgstr "önceki sayfa"
+
+msgid "next page"
+msgstr "sonraki Sayfa"
+
+msgid "Toggle navigation"
+msgstr "Gezinmeyi değiştir"
+
+msgid "repository"
+msgstr "depo"
+
+msgid "suggest edit"
+msgstr "düzenleme öner"
+
+msgid "open issue"
+msgstr "Açık konu"
+
+msgid "Launch"
+msgstr "Başlatmak"
+
+msgid "Print to PDF"
+msgstr "PDF olarak yazdır"
+
+msgid "By the"
+msgstr "Tarafından"
+
+msgid "Last updated on"
+msgstr "Son güncelleme tarihi"
+
+msgid "Download source file"
+msgstr "Kaynak dosyayı indirin"
+
+msgid "Download this page"
+msgstr "Bu sayfayı indirin"
diff --git a/_static/locales/uk/LC_MESSAGES/booktheme.mo b/_static/locales/uk/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..16ab78909cfbaba7fa199f47fdfc2934426ac699
GIT binary patch
literal 1681
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zPJ@uD1fdWPh|e20*TKPc;zZ)a@r}d@A+B8DUJjM|f4dvvq>McK+j;xuef*#QJbLI0
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zJRRRqQE^OHOf}GcNnV%^Y~hNh{RFy}WOB1GQBNYTUK}^kOk9#WOpkH-{HV-c%WrFW
zye!Y19xVv^j9TsvZMiu?-_n+#FKN@Qx_Nh}?-P#qs7q~0+is4U)XE(BrAa+pZ_+xR
zZRr;9`hYeh-KP!O!kr#M<2%RQ<4zrzI}#B(?yg&<pWxY{2meKQ;zAaG(Je_Xjtj=E
z9(7$q(09~EfF`ZE2A7mZcK`2+9^rzjaHX3z)7!~B2h%!=*c9|lnghL|yA=s%zR*HT
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z<NofZ={oLHR_+Jb;Vx4(JG2JbhUt5^koP}7+~?BbLU@u{xGrtDCHKjW*gc*BJl2qW
z5mR0g^fg|gC#u^<Yt4P)a{4r6s#Q8N%xG_Ktmt;04^wo@PsZ5OQCrZ@sDuAWd=c9A
LPmM*`H%jps*u#;t

literal 0
HcmV?d00001

diff --git a/_static/locales/uk/LC_MESSAGES/booktheme.po b/_static/locales/uk/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..be49ab8
--- /dev/null
+++ b/_static/locales/uk/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: uk\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Тема від"
+
+msgid "Open an issue"
+msgstr "Відкрийте випуск"
+
+msgid "Contents"
+msgstr "Зміст"
+
+msgid "Download notebook file"
+msgstr "Завантажте файл блокнота"
+
+msgid "Sphinx Book Theme"
+msgstr "Тема книги \"Сфінкс\""
+
+msgid "Fullscreen mode"
+msgstr "Повноекранний режим"
+
+msgid "Edit this page"
+msgstr "Редагувати цю сторінку"
+
+msgid "By"
+msgstr "Автор"
+
+msgid "Copyright"
+msgstr "Авторське право"
+
+msgid "Source repository"
+msgstr "Джерело сховища"
+
+msgid "previous page"
+msgstr "Попередня сторінка"
+
+msgid "next page"
+msgstr "Наступна сторінка"
+
+msgid "Toggle navigation"
+msgstr "Переключити навігацію"
+
+msgid "repository"
+msgstr "сховище"
+
+msgid "suggest edit"
+msgstr "запропонувати редагувати"
+
+msgid "open issue"
+msgstr "відкритий випуск"
+
+msgid "Launch"
+msgstr "Запуск"
+
+msgid "Print to PDF"
+msgstr "Друк у форматі PDF"
+
+msgid "By the"
+msgstr "По"
+
+msgid "Last updated on"
+msgstr "Останнє оновлення:"
+
+msgid "Download source file"
+msgstr "Завантажити вихідний файл"
+
+msgid "Download this page"
+msgstr "Завантажте цю сторінку"
diff --git a/_static/locales/ur/LC_MESSAGES/booktheme.mo b/_static/locales/ur/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..de8c84b935ed5c3db23e304015d45b638a3d2db3
GIT binary patch
literal 1462
zcma)(&2Jk;7{&)0pqP)6LL-m>O`(TSv<;z`$dL~;A5u^%qBgBK^s=!h>rLI6)qdpT
zRwLUoA{Qc+BL{@CNd#$~fM}{TM=rgzQV%n0sfS7&;BP2WpLe~9L#0ZLy!)G(eLtS}
z@uTBCHyGACc;3gei{}G8S6;vi>pu7*_yBwvd<eb@w!uE|FOYJdfXBgJ1iuNM0*`@b
zLCPBe-vGY^UkASidqI(LA-n%JJO2PupEWQCZh@447o_}q;B8Q6=kJd&_8QJVf>d_{
zw7^~PH24qrDR`oXv3~FiknZO|ioXGV2*%(?;Gf{z;NRf8;J+FBUg~@w04eVRNO2|b
zJ#Z2H7+e8i$-yFT-pWp-6LJ_r(sdMXnvv>}ceKb;S{N^_PkZu%7R~=ky6bpCK9k3g
z$k@3h{CHRvY(#lWzU!1jHmVk6McE}TRVZeZy2@wWis)VkD)Nisnai;32Hdk9!Ny8%
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z*MdBkUV01)pAYlSw$Ly6$pRnzWH`t4n!cr5?Pa~wuCipkz0CC=x@BmuW3xx+mX7tR
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z$~?F1e_~CYdU3r0$=I6uq5ePVO_Bn=P}riFSZ}qf6oE57w5w3K+FoX+hEW?y<4|&p
zx|p)Aw=sGx%}Vw#el49X^(ARiaRizwH+vA!fH?=_BQ=JATO9Uo!rm6_g(Z9Fvrf~J
ziFzY}!KTjO`w9hS|3mkKY2Z8hBsWpwH*$FgF5fip{lMp#&N|*Vkp4MHrJJsNw1%8D
c^9?3>eEmE8GP@z_uy-`khW>?G>aA{%rxd0lq5uE@

literal 0
HcmV?d00001

diff --git a/_static/locales/ur/LC_MESSAGES/booktheme.po b/_static/locales/ur/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..94bcab3
--- /dev/null
+++ b/_static/locales/ur/LC_MESSAGES/booktheme.po
@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ur\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "کے ذریعہ تھیم"
+
+msgid "Open an issue"
+msgstr "ایک مسئلہ کھولیں"
+
+msgid "Download notebook file"
+msgstr "نوٹ بک فائل ڈاؤن لوڈ کریں"
+
+msgid "Sphinx Book Theme"
+msgstr "سپنکس بک تھیم"
+
+msgid "Edit this page"
+msgstr "اس صفحے میں ترمیم کریں"
+
+msgid "By"
+msgstr "بذریعہ"
+
+msgid "Copyright"
+msgstr "کاپی رائٹ"
+
+msgid "Source repository"
+msgstr "ماخذ ذخیرہ"
+
+msgid "previous page"
+msgstr "سابقہ ​​صفحہ"
+
+msgid "next page"
+msgstr "اگلا صفحہ"
+
+msgid "Toggle navigation"
+msgstr "نیویگیشن ٹوگل کریں"
+
+msgid "suggest edit"
+msgstr "ترمیم کی تجویز کریں"
+
+msgid "open issue"
+msgstr "کھلا مسئلہ"
+
+msgid "Launch"
+msgstr "لانچ کریں"
+
+msgid "Print to PDF"
+msgstr "پی ڈی ایف پرنٹ کریں"
+
+msgid "By the"
+msgstr "کی طرف"
+
+msgid "Last updated on"
+msgstr "آخری بار تازہ کاری ہوئی"
+
+msgid "Download source file"
+msgstr "سورس فائل ڈاؤن لوڈ کریں"
+
+msgid "Download this page"
+msgstr "اس صفحے کو ڈاؤن لوڈ کریں"
diff --git a/_static/locales/vi/LC_MESSAGES/booktheme.mo b/_static/locales/vi/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..2bb32555c3ea0dab08ed37b71cb863fbe75698c6
GIT binary patch
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literal 0
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diff --git a/_static/locales/vi/LC_MESSAGES/booktheme.po b/_static/locales/vi/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..116236d
--- /dev/null
+++ b/_static/locales/vi/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: vi\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "Chủ đề của"
+
+msgid "Open an issue"
+msgstr "Mở một vấn đề"
+
+msgid "Contents"
+msgstr "Nội dung"
+
+msgid "Download notebook file"
+msgstr "Tải xuống tệp sổ tay"
+
+msgid "Sphinx Book Theme"
+msgstr "Chủ đề sách nhân sư"
+
+msgid "Fullscreen mode"
+msgstr "Chế độ toàn màn hình"
+
+msgid "Edit this page"
+msgstr "chỉnh sửa trang này"
+
+msgid "By"
+msgstr "Bởi"
+
+msgid "Copyright"
+msgstr "Bản quyền"
+
+msgid "Source repository"
+msgstr "Kho nguồn"
+
+msgid "previous page"
+msgstr "trang trước"
+
+msgid "next page"
+msgstr "Trang tiếp theo"
+
+msgid "Toggle navigation"
+msgstr "Chuyển đổi điều hướng thành"
+
+msgid "repository"
+msgstr "kho"
+
+msgid "suggest edit"
+msgstr "đề nghị chỉnh sửa"
+
+msgid "open issue"
+msgstr "vấn đề mở"
+
+msgid "Launch"
+msgstr "Phóng"
+
+msgid "Print to PDF"
+msgstr "In sang PDF"
+
+msgid "By the"
+msgstr "Bằng"
+
+msgid "Last updated on"
+msgstr "Cập nhật lần cuối vào"
+
+msgid "Download source file"
+msgstr "Tải xuống tệp nguồn"
+
+msgid "Download this page"
+msgstr "Tải xuống trang này"
diff --git a/_static/locales/zh_CN/LC_MESSAGES/booktheme.mo b/_static/locales/zh_CN/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..0e3235d090c2a05c0e278d38520f0437847dc79f
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/zh_CN/LC_MESSAGES/booktheme.po b/_static/locales/zh_CN/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..4f4ab57
--- /dev/null
+++ b/_static/locales/zh_CN/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: zh_CN\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "主题作者："
+
+msgid "Open an issue"
+msgstr "创建议题"
+
+msgid "Contents"
+msgstr "目录"
+
+msgid "Download notebook file"
+msgstr "下载笔记本文件"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx Book 主题"
+
+msgid "Fullscreen mode"
+msgstr "全屏模式"
+
+msgid "Edit this page"
+msgstr "编辑此页面"
+
+msgid "By"
+msgstr "作者："
+
+msgid "Copyright"
+msgstr "版权"
+
+msgid "Source repository"
+msgstr "源码库"
+
+msgid "previous page"
+msgstr "上一页"
+
+msgid "next page"
+msgstr "下一页"
+
+msgid "Toggle navigation"
+msgstr "显示或隐藏导航栏"
+
+msgid "repository"
+msgstr "仓库"
+
+msgid "suggest edit"
+msgstr "提出修改建议"
+
+msgid "open issue"
+msgstr "创建议题"
+
+msgid "Launch"
+msgstr "启动"
+
+msgid "Print to PDF"
+msgstr "列印成 PDF"
+
+msgid "By the"
+msgstr "作者："
+
+msgid "Last updated on"
+msgstr "上次更新时间："
+
+msgid "Download source file"
+msgstr "下载源文件"
+
+msgid "Download this page"
+msgstr "下载此页面"
diff --git a/_static/locales/zh_TW/LC_MESSAGES/booktheme.mo b/_static/locales/zh_TW/LC_MESSAGES/booktheme.mo
new file mode 100644
index 0000000000000000000000000000000000000000..9116fa95d0a752665e0f1d59857a32abfc0c6bce
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/_static/locales/zh_TW/LC_MESSAGES/booktheme.po b/_static/locales/zh_TW/LC_MESSAGES/booktheme.po
new file mode 100644
index 0000000..42b43b8
--- /dev/null
+++ b/_static/locales/zh_TW/LC_MESSAGES/booktheme.po
@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: zh_TW\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Theme by the"
+msgstr "佈景主題作者："
+
+msgid "Open an issue"
+msgstr "開啟議題"
+
+msgid "Contents"
+msgstr "目錄"
+
+msgid "Download notebook file"
+msgstr "下載 Notebook 檔案"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx Book 佈景主題"
+
+msgid "Fullscreen mode"
+msgstr "全螢幕模式"
+
+msgid "Edit this page"
+msgstr "編輯此頁面"
+
+msgid "By"
+msgstr "作者："
+
+msgid "Copyright"
+msgstr "Copyright"
+
+msgid "Source repository"
+msgstr "來源儲存庫"
+
+msgid "previous page"
+msgstr "上一頁"
+
+msgid "next page"
+msgstr "下一頁"
+
+msgid "Toggle navigation"
+msgstr "顯示或隱藏導覽列"
+
+msgid "repository"
+msgstr "儲存庫"
+
+msgid "suggest edit"
+msgstr "提出修改建議"
+
+msgid "open issue"
+msgstr "公開的問題"
+
+msgid "Launch"
+msgstr "啟動"
+
+msgid "Print to PDF"
+msgstr "列印成 PDF"
+
+msgid "By the"
+msgstr "作者："
+
+msgid "Last updated on"
+msgstr "最後更新時間："
+
+msgid "Download source file"
+msgstr "下載原始檔"
+
+msgid "Download this page"
+msgstr "下載此頁面"
diff --git a/_static/minus.png b/_static/minus.png
new file mode 100644
index 0000000000000000000000000000000000000000..d96755fdaf8bb2214971e0db9c1fd3077d7c419d
GIT binary patch
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literal 0
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diff --git a/_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css b/_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css
new file mode 100644
index 0000000..3356631
--- /dev/null
+++ b/_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css
@@ -0,0 +1,2342 @@
+/* Variables */
+:root {
+  --mystnb-source-bg-color: #f7f7f7;
+  --mystnb-stdout-bg-color: #fcfcfc;
+  --mystnb-stderr-bg-color: #fdd;
+  --mystnb-traceback-bg-color: #fcfcfc;
+  --mystnb-source-border-color: #ccc;
+  --mystnb-source-margin-color: green;
+  --mystnb-stdout-border-color: #f7f7f7;
+  --mystnb-stderr-border-color: #f7f7f7;
+  --mystnb-traceback-border-color: #ffd6d6;
+  --mystnb-hide-prompt-opacity: 70%;
+  --mystnb-source-border-radius: .4em;
+  --mystnb-source-border-width: 1px;
+}
+
+/* Whole cell */
+div.container.cell {
+  padding-left: 0;
+  margin-bottom: 1em;
+}
+
+/* Removing all background formatting so we can control at the div level */
+.cell_input div.highlight,
+.cell_output pre,
+.cell_input pre,
+.cell_output .output {
+  border: none;
+  box-shadow: none;
+}
+
+.cell_output .output pre,
+.cell_input pre {
+  margin: 0px;
+}
+
+/* Input cells */
+div.cell div.cell_input,
+div.cell details.above-input>summary {
+  padding-left: 0em;
+  padding-right: 0em;
+  border: var(--mystnb-source-border-width) var(--mystnb-source-border-color) solid;
+  background-color: var(--mystnb-source-bg-color);
+  border-left-color: var(--mystnb-source-margin-color);
+  border-left-width: medium;
+  border-radius: var(--mystnb-source-border-radius);
+}
+
+div.cell_input>div,
+div.cell_output div.output>div.highlight {
+  margin: 0em !important;
+  border: none !important;
+}
+
+/* All cell outputs */
+.cell_output {
+  padding-left: 1em;
+  padding-right: 0em;
+  margin-top: 1em;
+}
+
+/* Text outputs from cells */
+.cell_output .output.text_plain,
+.cell_output .output.traceback,
+.cell_output .output.stream,
+.cell_output .output.stderr {
+  margin-top: 1em;
+  margin-bottom: 0em;
+  box-shadow: none;
+}
+
+.cell_output .output.text_plain,
+.cell_output .output.stream {
+  background: var(--mystnb-stdout-bg-color);
+  border: 1px solid var(--mystnb-stdout-border-color);
+}
+
+.cell_output .output.stderr {
+  background: var(--mystnb-stderr-bg-color);
+  border: 1px solid var(--mystnb-stderr-border-color);
+}
+
+.cell_output .output.traceback {
+  background: var(--mystnb-traceback-bg-color);
+  border: 1px solid var(--mystnb-traceback-border-color);
+}
+
+/* Collapsible cell content */
+div.cell details.above-input div.cell_input {
+  border-top-left-radius: 0;
+  border-top-right-radius: 0;
+  border-top: var(--mystnb-source-border-width) var(--mystnb-source-border-color) dashed;
+}
+
+div.cell div.cell_input.above-output-prompt {
+  border-bottom-left-radius: 0;
+  border-bottom-right-radius: 0;
+}
+
+div.cell details.above-input>summary {
+  border-bottom-left-radius: 0;
+  border-bottom-right-radius: 0;
+  border-bottom: var(--mystnb-source-border-width) var(--mystnb-source-border-color) dashed;
+  padding-left: 1em;
+  margin-bottom: 0;
+}
+
+div.cell details.above-output>summary {
+  background-color: var(--mystnb-source-bg-color);
+  padding-left: 1em;
+  padding-right: 0em;
+  border: var(--mystnb-source-border-width) var(--mystnb-source-border-color) solid;
+  border-radius: var(--mystnb-source-border-radius);
+  border-left-color: var(--mystnb-source-margin-color);
+  border-left-width: medium;
+}
+
+div.cell details.below-input>summary {
+  background-color: var(--mystnb-source-bg-color);
+  padding-left: 1em;
+  padding-right: 0em;
+  border: var(--mystnb-source-border-width) var(--mystnb-source-border-color) solid;
+  border-top: none;
+  border-bottom-left-radius: var(--mystnb-source-border-radius);
+  border-bottom-right-radius: var(--mystnb-source-border-radius);
+  border-left-color: var(--mystnb-source-margin-color);
+  border-left-width: medium;
+}
+
+div.cell details.hide>summary>span {
+  opacity: var(--mystnb-hide-prompt-opacity);
+}
+
+div.cell details.hide[open]>summary>span.collapsed {
+  display: none;
+}
+
+div.cell details.hide:not([open])>summary>span.expanded {
+  display: none;
+}
+
+@keyframes collapsed-fade-in {
+  0% {
+    opacity: 0;
+  }
+
+  100% {
+    opacity: 1;
+  }
+}
+div.cell details.hide[open]>summary~* {
+  -moz-animation: collapsed-fade-in 0.3s ease-in-out;
+  -webkit-animation: collapsed-fade-in 0.3s ease-in-out;
+  animation: collapsed-fade-in 0.3s ease-in-out;
+}
+
+/* Math align to the left */
+.cell_output .MathJax_Display {
+  text-align: left !important;
+}
+
+/* Pandas tables. Pulled from the Jupyter / nbsphinx CSS */
+div.cell_output table {
+  border: none;
+  border-collapse: collapse;
+  border-spacing: 0;
+  color: black;
+  font-size: 1em;
+  table-layout: fixed;
+}
+
+div.cell_output thead {
+  border-bottom: 1px solid black;
+  vertical-align: bottom;
+}
+
+div.cell_output tr,
+div.cell_output th,
+div.cell_output td {
+  text-align: right;
+  vertical-align: middle;
+  padding: 0.5em 0.5em;
+  line-height: normal;
+  white-space: normal;
+  max-width: none;
+  border: none;
+}
+
+div.cell_output th {
+  font-weight: bold;
+}
+
+div.cell_output tbody tr:nth-child(odd) {
+  background: #f5f5f5;
+}
+
+div.cell_output tbody tr:hover {
+  background: rgba(66, 165, 245, 0.2);
+}
+
+/** source code line numbers **/
+span.linenos {
+  opacity: 0.5;
+}
+
+/* Inline text from `paste` operation */
+
+span.pasted-text {
+  font-weight: bold;
+}
+
+span.pasted-inline img {
+  max-height: 2em;
+}
+
+tbody span.pasted-inline img {
+  max-height: none;
+}
+
+/* Font colors for translated ANSI escape sequences
+Color values are copied from Jupyter Notebook
+https://github.com/jupyter/notebook/blob/52581f8eda9b319eb0390ac77fe5903c38f81e3e/notebook/static/notebook/less/ansicolors.less#L14-L21
+Background colors from
+https://nbsphinx.readthedocs.io/en/latest/code-cells.html#ANSI-Colors
+*/
+div.highlight .-Color-Bold {
+  font-weight: bold;
+}
+
+div.highlight .-Color[class*=-Black] {
+  color: #3E424D
+}
+
+div.highlight .-Color[class*=-Red] {
+  color: #E75C58
+}
+
+div.highlight .-Color[class*=-Green] {
+  color: #00A250
+}
+
+div.highlight .-Color[class*=-Yellow] {
+  color: #DDB62B
+}
+
+div.highlight .-Color[class*=-Blue] {
+  color: #208FFB
+}
+
+div.highlight .-Color[class*=-Magenta] {
+  color: #D160C4
+}
+
+div.highlight .-Color[class*=-Cyan] {
+  color: #60C6C8
+}
+
+div.highlight .-Color[class*=-White] {
+  color: #C5C1B4
+}
+
+div.highlight .-Color[class*=-BGBlack] {
+  background-color: #3E424D
+}
+
+div.highlight .-Color[class*=-BGRed] {
+  background-color: #E75C58
+}
+
+div.highlight .-Color[class*=-BGGreen] {
+  background-color: #00A250
+}
+
+div.highlight .-Color[class*=-BGYellow] {
+  background-color: #DDB62B
+}
+
+div.highlight .-Color[class*=-BGBlue] {
+  background-color: #208FFB
+}
+
+div.highlight .-Color[class*=-BGMagenta] {
+  background-color: #D160C4
+}
+
+div.highlight .-Color[class*=-BGCyan] {
+  background-color: #60C6C8
+}
+
+div.highlight .-Color[class*=-BGWhite] {
+  background-color: #C5C1B4
+}
+
+/* Font colors for 8-bit ANSI */
+
+div.highlight .-Color[class*=-C0] {
+  color: #000000
+}
+
+div.highlight .-Color[class*=-BGC0] {
+  background-color: #000000
+}
+
+div.highlight .-Color[class*=-C1] {
+  color: #800000
+}
+
+div.highlight .-Color[class*=-BGC1] {
+  background-color: #800000
+}
+
+div.highlight .-Color[class*=-C2] {
+  color: #008000
+}
+
+div.highlight .-Color[class*=-BGC2] {
+  background-color: #008000
+}
+
+div.highlight .-Color[class*=-C3] {
+  color: #808000
+}
+
+div.highlight .-Color[class*=-BGC3] {
+  background-color: #808000
+}
+
+div.highlight .-Color[class*=-C4] {
+  color: #000080
+}
+
+div.highlight .-Color[class*=-BGC4] {
+  background-color: #000080
+}
+
+div.highlight .-Color[class*=-C5] {
+  color: #800080
+}
+
+div.highlight .-Color[class*=-BGC5] {
+  background-color: #800080
+}
+
+div.highlight .-Color[class*=-C6] {
+  color: #008080
+}
+
+div.highlight .-Color[class*=-BGC6] {
+  background-color: #008080
+}
+
+div.highlight .-Color[class*=-C7] {
+  color: #C0C0C0
+}
+
+div.highlight .-Color[class*=-BGC7] {
+  background-color: #C0C0C0
+}
+
+div.highlight .-Color[class*=-C8] {
+  color: #808080
+}
+
+div.highlight .-Color[class*=-BGC8] {
+  background-color: #808080
+}
+
+div.highlight .-Color[class*=-C9] {
+  color: #FF0000
+}
+
+div.highlight .-Color[class*=-BGC9] {
+  background-color: #FF0000
+}
+
+div.highlight .-Color[class*=-C10] {
+  color: #00FF00
+}
+
+div.highlight .-Color[class*=-BGC10] {
+  background-color: #00FF00
+}
+
+div.highlight .-Color[class*=-C11] {
+  color: #FFFF00
+}
+
+div.highlight .-Color[class*=-BGC11] {
+  background-color: #FFFF00
+}
+
+div.highlight .-Color[class*=-C12] {
+  color: #0000FF
+}
+
+div.highlight .-Color[class*=-BGC12] {
+  background-color: #0000FF
+}
+
+div.highlight .-Color[class*=-C13] {
+  color: #FF00FF
+}
+
+div.highlight .-Color[class*=-BGC13] {
+  background-color: #FF00FF
+}
+
+div.highlight .-Color[class*=-C14] {
+  color: #00FFFF
+}
+
+div.highlight .-Color[class*=-BGC14] {
+  background-color: #00FFFF
+}
+
+div.highlight .-Color[class*=-C15] {
+  color: #FFFFFF
+}
+
+div.highlight .-Color[class*=-BGC15] {
+  background-color: #FFFFFF
+}
+
+div.highlight .-Color[class*=-C16] {
+  color: #000000
+}
+
+div.highlight .-Color[class*=-BGC16] {
+  background-color: #000000
+}
+
+div.highlight .-Color[class*=-C17] {
+  color: #00005F
+}
+
+div.highlight .-Color[class*=-BGC17] {
+  background-color: #00005F
+}
+
+div.highlight .-Color[class*=-C18] {
+  color: #000087
+}
+
+div.highlight .-Color[class*=-BGC18] {
+  background-color: #000087
+}
+
+div.highlight .-Color[class*=-C19] {
+  color: #0000AF
+}
+
+div.highlight .-Color[class*=-BGC19] {
+  background-color: #0000AF
+}
+
+div.highlight .-Color[class*=-C20] {
+  color: #0000D7
+}
+
+div.highlight .-Color[class*=-BGC20] {
+  background-color: #0000D7
+}
+
+div.highlight .-Color[class*=-C21] {
+  color: #0000FF
+}
+
+div.highlight .-Color[class*=-BGC21] {
+  background-color: #0000FF
+}
+
+div.highlight .-Color[class*=-C22] {
+  color: #005F00
+}
+
+div.highlight .-Color[class*=-BGC22] {
+  background-color: #005F00
+}
+
+div.highlight .-Color[class*=-C23] {
+  color: #005F5F
+}
+
+div.highlight .-Color[class*=-BGC23] {
+  background-color: #005F5F
+}
+
+div.highlight .-Color[class*=-C24] {
+  color: #005F87
+}
+
+div.highlight .-Color[class*=-BGC24] {
+  background-color: #005F87
+}
+
+div.highlight .-Color[class*=-C25] {
+  color: #005FAF
+}
+
+div.highlight .-Color[class*=-BGC25] {
+  background-color: #005FAF
+}
+
+div.highlight .-Color[class*=-C26] {
+  color: #005FD7
+}
+
+div.highlight .-Color[class*=-BGC26] {
+  background-color: #005FD7
+}
+
+div.highlight .-Color[class*=-C27] {
+  color: #005FFF
+}
+
+div.highlight .-Color[class*=-BGC27] {
+  background-color: #005FFF
+}
+
+div.highlight .-Color[class*=-C28] {
+  color: #008700
+}
+
+div.highlight .-Color[class*=-BGC28] {
+  background-color: #008700
+}
+
+div.highlight .-Color[class*=-C29] {
+  color: #00875F
+}
+
+div.highlight .-Color[class*=-BGC29] {
+  background-color: #00875F
+}
+
+div.highlight .-Color[class*=-C30] {
+  color: #008787
+}
+
+div.highlight .-Color[class*=-BGC30] {
+  background-color: #008787
+}
+
+div.highlight .-Color[class*=-C31] {
+  color: #0087AF
+}
+
+div.highlight .-Color[class*=-BGC31] {
+  background-color: #0087AF
+}
+
+div.highlight .-Color[class*=-C32] {
+  color: #0087D7
+}
+
+div.highlight .-Color[class*=-BGC32] {
+  background-color: #0087D7
+}
+
+div.highlight .-Color[class*=-C33] {
+  color: #0087FF
+}
+
+div.highlight .-Color[class*=-BGC33] {
+  background-color: #0087FF
+}
+
+div.highlight .-Color[class*=-C34] {
+  color: #00AF00
+}
+
+div.highlight .-Color[class*=-BGC34] {
+  background-color: #00AF00
+}
+
+div.highlight .-Color[class*=-C35] {
+  color: #00AF5F
+}
+
+div.highlight .-Color[class*=-BGC35] {
+  background-color: #00AF5F
+}
+
+div.highlight .-Color[class*=-C36] {
+  color: #00AF87
+}
+
+div.highlight .-Color[class*=-BGC36] {
+  background-color: #00AF87
+}
+
+div.highlight .-Color[class*=-C37] {
+  color: #00AFAF
+}
+
+div.highlight .-Color[class*=-BGC37] {
+  background-color: #00AFAF
+}
+
+div.highlight .-Color[class*=-C38] {
+  color: #00AFD7
+}
+
+div.highlight .-Color[class*=-BGC38] {
+  background-color: #00AFD7
+}
+
+div.highlight .-Color[class*=-C39] {
+  color: #00AFFF
+}
+
+div.highlight .-Color[class*=-BGC39] {
+  background-color: #00AFFF
+}
+
+div.highlight .-Color[class*=-C40] {
+  color: #00D700
+}
+
+div.highlight .-Color[class*=-BGC40] {
+  background-color: #00D700
+}
+
+div.highlight .-Color[class*=-C41] {
+  color: #00D75F
+}
+
+div.highlight .-Color[class*=-BGC41] {
+  background-color: #00D75F
+}
+
+div.highlight .-Color[class*=-C42] {
+  color: #00D787
+}
+
+div.highlight .-Color[class*=-BGC42] {
+  background-color: #00D787
+}
+
+div.highlight .-Color[class*=-C43] {
+  color: #00D7AF
+}
+
+div.highlight .-Color[class*=-BGC43] {
+  background-color: #00D7AF
+}
+
+div.highlight .-Color[class*=-C44] {
+  color: #00D7D7
+}
+
+div.highlight .-Color[class*=-BGC44] {
+  background-color: #00D7D7
+}
+
+div.highlight .-Color[class*=-C45] {
+  color: #00D7FF
+}
+
+div.highlight .-Color[class*=-BGC45] {
+  background-color: #00D7FF
+}
+
+div.highlight .-Color[class*=-C46] {
+  color: #00FF00
+}
+
+div.highlight .-Color[class*=-BGC46] {
+  background-color: #00FF00
+}
+
+div.highlight .-Color[class*=-C47] {
+  color: #00FF5F
+}
+
+div.highlight .-Color[class*=-BGC47] {
+  background-color: #00FF5F
+}
+
+div.highlight .-Color[class*=-C48] {
+  color: #00FF87
+}
+
+div.highlight .-Color[class*=-BGC48] {
+  background-color: #00FF87
+}
+
+div.highlight .-Color[class*=-C49] {
+  color: #00FFAF
+}
+
+div.highlight .-Color[class*=-BGC49] {
+  background-color: #00FFAF
+}
+
+div.highlight .-Color[class*=-C50] {
+  color: #00FFD7
+}
+
+div.highlight .-Color[class*=-BGC50] {
+  background-color: #00FFD7
+}
+
+div.highlight .-Color[class*=-C51] {
+  color: #00FFFF
+}
+
+div.highlight .-Color[class*=-BGC51] {
+  background-color: #00FFFF
+}
+
+div.highlight .-Color[class*=-C52] {
+  color: #5F0000
+}
+
+div.highlight .-Color[class*=-BGC52] {
+  background-color: #5F0000
+}
+
+div.highlight .-Color[class*=-C53] {
+  color: #5F005F
+}
+
+div.highlight .-Color[class*=-BGC53] {
+  background-color: #5F005F
+}
+
+div.highlight .-Color[class*=-C54] {
+  color: #5F0087
+}
+
+div.highlight .-Color[class*=-BGC54] {
+  background-color: #5F0087
+}
+
+div.highlight .-Color[class*=-C55] {
+  color: #5F00AF
+}
+
+div.highlight .-Color[class*=-BGC55] {
+  background-color: #5F00AF
+}
+
+div.highlight .-Color[class*=-C56] {
+  color: #5F00D7
+}
+
+div.highlight .-Color[class*=-BGC56] {
+  background-color: #5F00D7
+}
+
+div.highlight .-Color[class*=-C57] {
+  color: #5F00FF
+}
+
+div.highlight .-Color[class*=-BGC57] {
+  background-color: #5F00FF
+}
+
+div.highlight .-Color[class*=-C58] {
+  color: #5F5F00
+}
+
+div.highlight .-Color[class*=-BGC58] {
+  background-color: #5F5F00
+}
+
+div.highlight .-Color[class*=-C59] {
+  color: #5F5F5F
+}
+
+div.highlight .-Color[class*=-BGC59] {
+  background-color: #5F5F5F
+}
+
+div.highlight .-Color[class*=-C60] {
+  color: #5F5F87
+}
+
+div.highlight .-Color[class*=-BGC60] {
+  background-color: #5F5F87
+}
+
+div.highlight .-Color[class*=-C61] {
+  color: #5F5FAF
+}
+
+div.highlight .-Color[class*=-BGC61] {
+  background-color: #5F5FAF
+}
+
+div.highlight .-Color[class*=-C62] {
+  color: #5F5FD7
+}
+
+div.highlight .-Color[class*=-BGC62] {
+  background-color: #5F5FD7
+}
+
+div.highlight .-Color[class*=-C63] {
+  color: #5F5FFF
+}
+
+div.highlight .-Color[class*=-BGC63] {
+  background-color: #5F5FFF
+}
+
+div.highlight .-Color[class*=-C64] {
+  color: #5F8700
+}
+
+div.highlight .-Color[class*=-BGC64] {
+  background-color: #5F8700
+}
+
+div.highlight .-Color[class*=-C65] {
+  color: #5F875F
+}
+
+div.highlight .-Color[class*=-BGC65] {
+  background-color: #5F875F
+}
+
+div.highlight .-Color[class*=-C66] {
+  color: #5F8787
+}
+
+div.highlight .-Color[class*=-BGC66] {
+  background-color: #5F8787
+}
+
+div.highlight .-Color[class*=-C67] {
+  color: #5F87AF
+}
+
+div.highlight .-Color[class*=-BGC67] {
+  background-color: #5F87AF
+}
+
+div.highlight .-Color[class*=-C68] {
+  color: #5F87D7
+}
+
+div.highlight .-Color[class*=-BGC68] {
+  background-color: #5F87D7
+}
+
+div.highlight .-Color[class*=-C69] {
+  color: #5F87FF
+}
+
+div.highlight .-Color[class*=-BGC69] {
+  background-color: #5F87FF
+}
+
+div.highlight .-Color[class*=-C70] {
+  color: #5FAF00
+}
+
+div.highlight .-Color[class*=-BGC70] {
+  background-color: #5FAF00
+}
+
+div.highlight .-Color[class*=-C71] {
+  color: #5FAF5F
+}
+
+div.highlight .-Color[class*=-BGC71] {
+  background-color: #5FAF5F
+}
+
+div.highlight .-Color[class*=-C72] {
+  color: #5FAF87
+}
+
+div.highlight .-Color[class*=-BGC72] {
+  background-color: #5FAF87
+}
+
+div.highlight .-Color[class*=-C73] {
+  color: #5FAFAF
+}
+
+div.highlight .-Color[class*=-BGC73] {
+  background-color: #5FAFAF
+}
+
+div.highlight .-Color[class*=-C74] {
+  color: #5FAFD7
+}
+
+div.highlight .-Color[class*=-BGC74] {
+  background-color: #5FAFD7
+}
+
+div.highlight .-Color[class*=-C75] {
+  color: #5FAFFF
+}
+
+div.highlight .-Color[class*=-BGC75] {
+  background-color: #5FAFFF
+}
+
+div.highlight .-Color[class*=-C76] {
+  color: #5FD700
+}
+
+div.highlight .-Color[class*=-BGC76] {
+  background-color: #5FD700
+}
+
+div.highlight .-Color[class*=-C77] {
+  color: #5FD75F
+}
+
+div.highlight .-Color[class*=-BGC77] {
+  background-color: #5FD75F
+}
+
+div.highlight .-Color[class*=-C78] {
+  color: #5FD787
+}
+
+div.highlight .-Color[class*=-BGC78] {
+  background-color: #5FD787
+}
+
+div.highlight .-Color[class*=-C79] {
+  color: #5FD7AF
+}
+
+div.highlight .-Color[class*=-BGC79] {
+  background-color: #5FD7AF
+}
+
+div.highlight .-Color[class*=-C80] {
+  color: #5FD7D7
+}
+
+div.highlight .-Color[class*=-BGC80] {
+  background-color: #5FD7D7
+}
+
+div.highlight .-Color[class*=-C81] {
+  color: #5FD7FF
+}
+
+div.highlight .-Color[class*=-BGC81] {
+  background-color: #5FD7FF
+}
+
+div.highlight .-Color[class*=-C82] {
+  color: #5FFF00
+}
+
+div.highlight .-Color[class*=-BGC82] {
+  background-color: #5FFF00
+}
+
+div.highlight .-Color[class*=-C83] {
+  color: #5FFF5F
+}
+
+div.highlight .-Color[class*=-BGC83] {
+  background-color: #5FFF5F
+}
+
+div.highlight .-Color[class*=-C84] {
+  color: #5FFF87
+}
+
+div.highlight .-Color[class*=-BGC84] {
+  background-color: #5FFF87
+}
+
+div.highlight .-Color[class*=-C85] {
+  color: #5FFFAF
+}
+
+div.highlight .-Color[class*=-BGC85] {
+  background-color: #5FFFAF
+}
+
+div.highlight .-Color[class*=-C86] {
+  color: #5FFFD7
+}
+
+div.highlight .-Color[class*=-BGC86] {
+  background-color: #5FFFD7
+}
+
+div.highlight .-Color[class*=-C87] {
+  color: #5FFFFF
+}
+
+div.highlight .-Color[class*=-BGC87] {
+  background-color: #5FFFFF
+}
+
+div.highlight .-Color[class*=-C88] {
+  color: #870000
+}
+
+div.highlight .-Color[class*=-BGC88] {
+  background-color: #870000
+}
+
+div.highlight .-Color[class*=-C89] {
+  color: #87005F
+}
+
+div.highlight .-Color[class*=-BGC89] {
+  background-color: #87005F
+}
+
+div.highlight .-Color[class*=-C90] {
+  color: #870087
+}
+
+div.highlight .-Color[class*=-BGC90] {
+  background-color: #870087
+}
+
+div.highlight .-Color[class*=-C91] {
+  color: #8700AF
+}
+
+div.highlight .-Color[class*=-BGC91] {
+  background-color: #8700AF
+}
+
+div.highlight .-Color[class*=-C92] {
+  color: #8700D7
+}
+
+div.highlight .-Color[class*=-BGC92] {
+  background-color: #8700D7
+}
+
+div.highlight .-Color[class*=-C93] {
+  color: #8700FF
+}
+
+div.highlight .-Color[class*=-BGC93] {
+  background-color: #8700FF
+}
+
+div.highlight .-Color[class*=-C94] {
+  color: #875F00
+}
+
+div.highlight .-Color[class*=-BGC94] {
+  background-color: #875F00
+}
+
+div.highlight .-Color[class*=-C95] {
+  color: #875F5F
+}
+
+div.highlight .-Color[class*=-BGC95] {
+  background-color: #875F5F
+}
+
+div.highlight .-Color[class*=-C96] {
+  color: #875F87
+}
+
+div.highlight .-Color[class*=-BGC96] {
+  background-color: #875F87
+}
+
+div.highlight .-Color[class*=-C97] {
+  color: #875FAF
+}
+
+div.highlight .-Color[class*=-BGC97] {
+  background-color: #875FAF
+}
+
+div.highlight .-Color[class*=-C98] {
+  color: #875FD7
+}
+
+div.highlight .-Color[class*=-BGC98] {
+  background-color: #875FD7
+}
+
+div.highlight .-Color[class*=-C99] {
+  color: #875FFF
+}
+
+div.highlight .-Color[class*=-BGC99] {
+  background-color: #875FFF
+}
+
+div.highlight .-Color[class*=-C100] {
+  color: #878700
+}
+
+div.highlight .-Color[class*=-BGC100] {
+  background-color: #878700
+}
+
+div.highlight .-Color[class*=-C101] {
+  color: #87875F
+}
+
+div.highlight .-Color[class*=-BGC101] {
+  background-color: #87875F
+}
+
+div.highlight .-Color[class*=-C102] {
+  color: #878787
+}
+
+div.highlight .-Color[class*=-BGC102] {
+  background-color: #878787
+}
+
+div.highlight .-Color[class*=-C103] {
+  color: #8787AF
+}
+
+div.highlight .-Color[class*=-BGC103] {
+  background-color: #8787AF
+}
+
+div.highlight .-Color[class*=-C104] {
+  color: #8787D7
+}
+
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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new file mode 100644
index 0000000..997797f
--- /dev/null
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+html[data-theme="light"] .highlight pre { line-height: 125%; }
+html[data-theme="light"] .highlight td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }
+html[data-theme="light"] .highlight span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }
+html[data-theme="light"] .highlight td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }
+html[data-theme="light"] .highlight span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }
+html[data-theme="light"] .highlight .hll { background-color: #7971292e }
+html[data-theme="light"] .highlight { background: #fefefe; color: #545454 }
+html[data-theme="light"] .highlight .c { color: #797129 } /* Comment */
+html[data-theme="light"] .highlight .err { color: #d91e18 } /* Error */
+html[data-theme="light"] .highlight .k { color: #7928a1 } /* Keyword */
+html[data-theme="light"] .highlight .l { color: #797129 } /* Literal */
+html[data-theme="light"] .highlight .n { color: #545454 } /* Name */
+html[data-theme="light"] .highlight .o { color: #008000 } /* Operator */
+html[data-theme="light"] .highlight .p { color: #545454 } /* Punctuation */
+html[data-theme="light"] .highlight .ch { color: #797129 } /* Comment.Hashbang */
+html[data-theme="light"] .highlight .cm { color: #797129 } /* Comment.Multiline */
+html[data-theme="light"] .highlight .cp { color: #797129 } /* Comment.Preproc */
+html[data-theme="light"] .highlight .cpf { color: #797129 } /* Comment.PreprocFile */
+html[data-theme="light"] .highlight .c1 { color: #797129 } /* Comment.Single */
+html[data-theme="light"] .highlight .cs { color: #797129 } /* Comment.Special */
+html[data-theme="light"] .highlight .gd { color: #007faa } /* Generic.Deleted */
+html[data-theme="light"] .highlight .ge { font-style: italic } /* Generic.Emph */
+html[data-theme="light"] .highlight .gh { color: #007faa } /* Generic.Heading */
+html[data-theme="light"] .highlight .gs { font-weight: bold } /* Generic.Strong */
+html[data-theme="light"] .highlight .gu { color: #007faa } /* Generic.Subheading */
+html[data-theme="light"] .highlight .kc { color: #7928a1 } /* Keyword.Constant */
+html[data-theme="light"] .highlight .kd { color: #7928a1 } /* Keyword.Declaration */
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+html[data-theme="dark"] .highlight { background: #2b2b2b; color: #f8f8f2 }
+html[data-theme="dark"] .highlight .c { color: #ffd900 } /* Comment */
+html[data-theme="dark"] .highlight .err { color: #ffa07a } /* Error */
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+html[data-theme="dark"] .highlight .l { color: #ffd900 } /* Literal */
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+html[data-theme="dark"] .highlight .o { color: #abe338 } /* Operator */
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+html[data-theme="dark"] .highlight .cpf { color: #ffd900 } /* Comment.PreprocFile */
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+html[data-theme="dark"] .highlight .sh { color: #abe338 } /* Literal.String.Heredoc */
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+html[data-theme="dark"] .highlight .il { color: #ffd900 } /* Literal.Number.Integer.Long */
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diff --git a/_static/sbt-webpack-macros.html b/_static/sbt-webpack-macros.html
new file mode 100644
index 0000000..6cbf559
--- /dev/null
+++ b/_static/sbt-webpack-macros.html
@@ -0,0 +1,11 @@
+<!--
+  All these macros are auto-generated and must **NOT** be edited by hand.
+  See the webpack.config.js file, to learn more about how this is generated.
+-->
+{% macro head_pre_bootstrap() %}
+  <link href="{{ pathto('_static/styles/sphinx-book-theme.css', 1) }}" rel="stylesheet">
+{% endmacro %}
+
+{% macro body_post() %}
+  <script src="{{ pathto('_static/scripts/sphinx-book-theme.js', 1) }}"></script>
+{% endmacro %}
diff --git a/_static/scripts/bootstrap.js b/_static/scripts/bootstrap.js
new file mode 100644
index 0000000..4e209b0
--- /dev/null
+++ b/_static/scripts/bootstrap.js
@@ -0,0 +1,3 @@
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t.defaultInterval=t.interval,t}_addEventListeners(){this._config.keyboard&&fe.on(this._element,Ye,(t=>this._keydown(t))),"hover"===this._config.pause&&(fe.on(this._element,Ke,(()=>this.pause())),fe.on(this._element,Qe,(()=>this._maybeEnableCycle()))),this._config.touch&&je.isSupported()&&this._addTouchEventListeners()}_addTouchEventListeners(){for(const t of we.find(".carousel-item img",this._element))fe.on(t,Xe,(t=>t.preventDefault()));const t={leftCallback:()=>this._slide(this._directionToOrder(ze)),rightCallback:()=>this._slide(this._directionToOrder(Re)),endCallback:()=>{"hover"===this._config.pause&&(this.pause(),this.touchTimeout&&clearTimeout(this.touchTimeout),this.touchTimeout=setTimeout((()=>this._maybeEnableCycle()),500+this._config.interval))}};this._swipeHelper=new je(this._element,t)}_keydown(t){if(/input|textarea/i.test(t.target.tagName))return;const e=ni[t.key];e&&(t.preventDefault(),this._slide(this._directionToOrder(e)))}_getItemIndex(t){return this._getItems().indexOf(t)}_setActiveIndicatorElement(t){if(!this._indicatorsElement)return;const e=we.findOne(ti,this._indicatorsElement);e.classList.remove(Ze),e.removeAttribute("aria-current");const i=we.findOne(`[data-bs-slide-to="${t}"]`,this._indicatorsElement);i&&(i.classList.add(Ze),i.setAttribute("aria-current","true"))}_updateInterval(){const t=this._activeElement||this._getActive();if(!t)return;const e=Number.parseInt(t.getAttribute("data-bs-interval"),10);this._config.interval=e||this._config.defaultInterval}_slide(t,e=null){if(this._isSliding)return;const i=this._getActive(),n=t===Be,s=e||Gt(this._getItems(),i,n,this._config.wrap);if(s===i)return;const o=this._getItemIndex(s),r=e=>fe.trigger(this._element,e,{relatedTarget:s,direction:this._orderToDirection(t),from:this._getItemIndex(i),to:o});if(r(qe).defaultPrevented)return;if(!i||!s)return;const a=Boolean(this._interval);this.pause(),this._isSliding=!0,this._setActiveIndicatorElement(o),this._activeElement=s;const l=n?"carousel-item-start":"carousel-item-end",c=n?"carousel-item-next":"carousel-item-prev";s.classList.add(c),qt(s),i.classList.add(l),s.classList.add(l),this._queueCallback((()=>{s.classList.remove(l,c),s.classList.add(Ze),i.classList.remove(Ze,c,l),this._isSliding=!1,r(Ve)}),i,this._isAnimated()),a&&this.cycle()}_isAnimated(){return this._element.classList.contains("slide")}_getActive(){return we.findOne(ii,this._element)}_getItems(){return we.find(ei,this._element)}_clearInterval(){this._interval&&(clearInterval(this._interval),this._interval=null)}_directionToOrder(t){return Kt()?t===ze?We:Be:t===ze?Be:We}_orderToDirection(t){return Kt()?t===We?ze:Re:t===We?Re:ze}static jQueryInterface(t){return this.each((function(){const e=ri.getOrCreateInstance(this,t);if("number"!=typeof t){if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}else e.to(t)}))}}fe.on(document,Ge,"[data-bs-slide], [data-bs-slide-to]",(function(t){const e=we.getElementFromSelector(this);if(!e||!e.classList.contains(Je))return;t.preventDefault();const i=ri.getOrCreateInstance(e),n=this.getAttribute("data-bs-slide-to");return n?(i.to(n),void i._maybeEnableCycle()):"next"===_e.getDataAttribute(this,"slide")?(i.next(),void i._maybeEnableCycle()):(i.prev(),void i._maybeEnableCycle())})),fe.on(window,Ue,(()=>{const t=we.find('[data-bs-ride="carousel"]');for(const e of t)ri.getOrCreateInstance(e)})),Qt(ri);const ai=".bs.collapse",li=`show${ai}`,ci=`shown${ai}`,hi=`hide${ai}`,di=`hidden${ai}`,ui=`click${ai}.data-api`,fi="show",pi="collapse",mi="collapsing",gi=`:scope .${pi} .${pi}`,_i='[data-bs-toggle="collapse"]',bi={parent:null,toggle:!0},vi={parent:"(null|element)",toggle:"boolean"};class yi extends ve{constructor(t,e){super(t,e),this._isTransitioning=!1,this._triggerArray=[];const i=we.find(_i);for(const t of i){const e=we.getSelectorFromElement(t),i=we.find(e).filter((t=>t===this._element));null!==e&&i.length&&this._triggerArray.push(t)}this._initializeChildren(),this._config.parent||this._addAriaAndCollapsedClass(this._triggerArray,this._isShown()),this._config.toggle&&this.toggle()}static get Default(){return bi}static get DefaultType(){return vi}static get NAME(){return"collapse"}toggle(){this._isShown()?this.hide():this.show()}show(){if(this._isTransitioning||this._isShown())return;let t=[];if(this._config.parent&&(t=this._getFirstLevelChildren(".collapse.show, .collapse.collapsing").filter((t=>t!==this._element)).map((t=>yi.getOrCreateInstance(t,{toggle:!1})))),t.length&&t[0]._isTransitioning)return;if(fe.trigger(this._element,li).defaultPrevented)return;for(const e of t)e.hide();const e=this._getDimension();this._element.classList.remove(pi),this._element.classList.add(mi),this._element.style[e]=0,this._addAriaAndCollapsedClass(this._triggerArray,!0),this._isTransitioning=!0;const i=`scroll${e[0].toUpperCase()+e.slice(1)}`;this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(mi),this._element.classList.add(pi,fi),this._element.style[e]="",fe.trigger(this._element,ci)}),this._element,!0),this._element.style[e]=`${this._element[i]}px`}hide(){if(this._isTransitioning||!this._isShown())return;if(fe.trigger(this._element,hi).defaultPrevented)return;const t=this._getDimension();this._element.style[t]=`${this._element.getBoundingClientRect()[t]}px`,qt(this._element),this._element.classList.add(mi),this._element.classList.remove(pi,fi);for(const t of this._triggerArray){const e=we.getElementFromSelector(t);e&&!this._isShown(e)&&this._addAriaAndCollapsedClass([t],!1)}this._isTransitioning=!0,this._element.style[t]="",this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(mi),this._element.classList.add(pi),fe.trigger(this._element,di)}),this._element,!0)}_isShown(t=this._element){return t.classList.contains(fi)}_configAfterMerge(t){return t.toggle=Boolean(t.toggle),t.parent=Ht(t.parent),t}_getDimension(){return this._element.classList.contains("collapse-horizontal")?"width":"height"}_initializeChildren(){if(!this._config.parent)return;const t=this._getFirstLevelChildren(_i);for(const e of t){const t=we.getElementFromSelector(e);t&&this._addAriaAndCollapsedClass([e],this._isShown(t))}}_getFirstLevelChildren(t){const e=we.find(gi,this._config.parent);return we.find(t,this._config.parent).filter((t=>!e.includes(t)))}_addAriaAndCollapsedClass(t,e){if(t.length)for(const i of t)i.classList.toggle("collapsed",!e),i.setAttribute("aria-expanded",e)}static jQueryInterface(t){const e={};return"string"==typeof t&&/show|hide/.test(t)&&(e.toggle=!1),this.each((function(){const i=yi.getOrCreateInstance(this,e);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t]()}}))}}fe.on(document,ui,_i,(function(t){("A"===t.target.tagName||t.delegateTarget&&"A"===t.delegateTarget.tagName)&&t.preventDefault();for(const t of we.getMultipleElementsFromSelector(this))yi.getOrCreateInstance(t,{toggle:!1}).toggle()})),Qt(yi);const wi="dropdown",Ei=".bs.dropdown",Ai=".data-api",Ti="ArrowUp",Ci="ArrowDown",Oi=`hide${Ei}`,xi=`hidden${Ei}`,ki=`show${Ei}`,Li=`shown${Ei}`,Si=`click${Ei}${Ai}`,Di=`keydown${Ei}${Ai}`,$i=`keyup${Ei}${Ai}`,Ii="show",Ni='[data-bs-toggle="dropdown"]:not(.disabled):not(:disabled)',Pi=`${Ni}.${Ii}`,Mi=".dropdown-menu",ji=Kt()?"top-end":"top-start",Fi=Kt()?"top-start":"top-end",Hi=Kt()?"bottom-end":"bottom-start",Bi=Kt()?"bottom-start":"bottom-end",Wi=Kt()?"left-start":"right-start",zi=Kt()?"right-start":"left-start",Ri={autoClose:!0,boundary:"clippingParents",display:"dynamic",offset:[0,2],popperConfig:null,reference:"toggle"},qi={autoClose:"(boolean|string)",boundary:"(string|element)",display:"string",offset:"(array|string|function)",popperConfig:"(null|object|function)",reference:"(string|element|object)"};class Vi extends ve{constructor(t,e){super(t,e),this._popper=null,this._parent=this._element.parentNode,this._menu=we.next(this._element,Mi)[0]||we.prev(this._element,Mi)[0]||we.findOne(Mi,this._parent),this._inNavbar=this._detectNavbar()}static get Default(){return Ri}static get DefaultType(){return qi}static get NAME(){return wi}toggle(){return this._isShown()?this.hide():this.show()}show(){if(Wt(this._element)||this._isShown())return;const t={relatedTarget:this._element};if(!fe.trigger(this._element,ki,t).defaultPrevented){if(this._createPopper(),"ontouchstart"in document.documentElement&&!this._parent.closest(".navbar-nav"))for(const t of[].concat(...document.body.children))fe.on(t,"mouseover",Rt);this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add(Ii),this._element.classList.add(Ii),fe.trigger(this._element,Li,t)}}hide(){if(Wt(this._element)||!this._isShown())return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){if(!fe.trigger(this._element,Oi,t).defaultPrevented){if("ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.off(t,"mouseover",Rt);this._popper&&this._popper.destroy(),this._menu.classList.remove(Ii),this._element.classList.remove(Ii),this._element.setAttribute("aria-expanded","false"),_e.removeDataAttribute(this._menu,"popper"),fe.trigger(this._element,xi,t)}}_getConfig(t){if("object"==typeof(t=super._getConfig(t)).reference&&!Ft(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${wi.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(){if(void 0===e)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let t=this._element;"parent"===this._config.reference?t=this._parent:Ft(this._config.reference)?t=Ht(this._config.reference):"object"==typeof this._config.reference&&(t=this._config.reference);const i=this._getPopperConfig();this._popper=Dt(t,this._menu,i)}_isShown(){return this._menu.classList.contains(Ii)}_getPlacement(){const t=this._parent;if(t.classList.contains("dropend"))return Wi;if(t.classList.contains("dropstart"))return zi;if(t.classList.contains("dropup-center"))return"top";if(t.classList.contains("dropdown-center"))return"bottom";const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?Fi:ji:e?Bi:Hi}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(_e.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...Xt(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=we.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter((t=>Bt(t)));i.length&&Gt(i,e,t===Ci,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=Vi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(2===t.button||"keyup"===t.type&&"Tab"!==t.key)return;const e=we.find(Pi);for(const i of e){const e=Vi.getInstance(i);if(!e||!1===e._config.autoClose)continue;const n=t.composedPath(),s=n.includes(e._menu);if(n.includes(e._element)||"inside"===e._config.autoClose&&!s||"outside"===e._config.autoClose&&s)continue;if(e._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;const o={relatedTarget:e._element};"click"===t.type&&(o.clickEvent=t),e._completeHide(o)}}static dataApiKeydownHandler(t){const e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ti,Ci].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ni)?this:we.prev(this,Ni)[0]||we.next(this,Ni)[0]||we.findOne(Ni,t.delegateTarget.parentNode),o=Vi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}fe.on(document,Di,Ni,Vi.dataApiKeydownHandler),fe.on(document,Di,Mi,Vi.dataApiKeydownHandler),fe.on(document,Si,Vi.clearMenus),fe.on(document,$i,Vi.clearMenus),fe.on(document,Si,Ni,(function(t){t.preventDefault(),Vi.getOrCreateInstance(this).toggle()})),Qt(Vi);const Yi="backdrop",Ki="show",Qi=`mousedown.bs.${Yi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Ui={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Gi extends be{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Ui}static get NAME(){return Yi}show(t){if(!this._config.isVisible)return void Xt(t);this._append();const e=this._getElement();this._config.isAnimated&&qt(e),e.classList.add(Ki),this._emulateAnimation((()=>{Xt(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),Xt(t)}))):Xt(t)}dispose(){this._isAppended&&(fe.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=Ht(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),fe.on(t,Qi,(()=>{Xt(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){Ut(t,this._getElement(),this._config.isAnimated)}}const Ji=".bs.focustrap",Zi=`focusin${Ji}`,tn=`keydown.tab${Ji}`,en="backward",nn={autofocus:!0,trapElement:null},sn={autofocus:"boolean",trapElement:"element"};class on extends be{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return nn}static get DefaultType(){return sn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),fe.off(document,Ji),fe.on(document,Zi,(t=>this._handleFocusin(t))),fe.on(document,tn,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,fe.off(document,Ji))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=we.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===en?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?en:"forward")}}const rn=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",an=".sticky-top",ln="padding-right",cn="margin-right";class hn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,ln,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e+t)),this._setElementAttributes(an,cn,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,ln),this._resetElementAttributes(rn,ln),this._resetElementAttributes(an,cn)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&_e.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=_e.getDataAttribute(t,e);null!==i?(_e.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(Ft(t))e(t);else for(const i of we.find(t,this._element))e(i)}}const dn=".bs.modal",un=`hide${dn}`,fn=`hidePrevented${dn}`,pn=`hidden${dn}`,mn=`show${dn}`,gn=`shown${dn}`,_n=`resize${dn}`,bn=`click.dismiss${dn}`,vn=`mousedown.dismiss${dn}`,yn=`keydown.dismiss${dn}`,wn=`click${dn}.data-api`,En="modal-open",An="show",Tn="modal-static",Cn={backdrop:!0,focus:!0,keyboard:!0},On={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class xn extends ve{constructor(t,e){super(t,e),this._dialog=we.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new hn,this._addEventListeners()}static get Default(){return Cn}static get DefaultType(){return On}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||fe.trigger(this._element,mn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(En),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(fe.trigger(this._element,un).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){fe.off(window,dn),fe.off(this._dialog,dn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Gi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new on({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=we.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),qt(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,fe.trigger(this._element,gn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){fe.on(this._element,yn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),fe.on(window,_n,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),fe.on(this._element,vn,(t=>{fe.one(this._element,bn,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(En),this._resetAdjustments(),this._scrollBar.reset(),fe.trigger(this._element,pn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(fe.trigger(this._element,fn).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(Tn)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(Tn),this._queueCallback((()=>{this._element.classList.remove(Tn),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=Kt()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=Kt()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=xn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}fe.on(document,wn,'[data-bs-toggle="modal"]',(function(t){const e=we.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),fe.one(e,mn,(t=>{t.defaultPrevented||fe.one(e,pn,(()=>{Bt(this)&&this.focus()}))}));const i=we.findOne(".modal.show");i&&xn.getInstance(i).hide(),xn.getOrCreateInstance(e).toggle(this)})),Ee(xn),Qt(xn);const kn=".bs.offcanvas",Ln=".data-api",Sn=`load${kn}${Ln}`,Dn="show",$n="showing",In="hiding",Nn=".offcanvas.show",Pn=`show${kn}`,Mn=`shown${kn}`,jn=`hide${kn}`,Fn=`hidePrevented${kn}`,Hn=`hidden${kn}`,Bn=`resize${kn}`,Wn=`click${kn}${Ln}`,zn=`keydown.dismiss${kn}`,Rn={backdrop:!0,keyboard:!0,scroll:!1},qn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class Vn extends ve{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return Rn}static get DefaultType(){return qn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||fe.trigger(this._element,Pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new hn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add($n),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Dn),this._element.classList.remove($n),fe.trigger(this._element,Mn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(fe.trigger(this._element,jn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add(In),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Dn,In),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new hn).reset(),fe.trigger(this._element,Hn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Gi({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():fe.trigger(this._element,Fn)}:null})}_initializeFocusTrap(){return new on({trapElement:this._element})}_addEventListeners(){fe.on(this._element,zn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():fe.trigger(this._element,Fn))}))}static jQueryInterface(t){return this.each((function(){const e=Vn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}fe.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=we.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),Wt(this))return;fe.one(e,Hn,(()=>{Bt(this)&&this.focus()}));const i=we.findOne(Nn);i&&i!==e&&Vn.getInstance(i).hide(),Vn.getOrCreateInstance(e).toggle(this)})),fe.on(window,Sn,(()=>{for(const t of we.find(Nn))Vn.getOrCreateInstance(t).show()})),fe.on(window,Bn,(()=>{for(const t of we.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&Vn.getOrCreateInstance(t).hide()})),Ee(Vn),Qt(Vn);const Yn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Un={allowList:Yn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"<div></div>"},Gn={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},Jn={entry:"(string|element|function|null)",selector:"(string|element)"};class Zn extends be{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Un}static get DefaultType(){return Gn}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Jn)}_setContent(t,e,i){const n=we.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?Ft(e)?this._putElementInTemplate(Ht(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return Xt(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const ts=new Set(["sanitize","allowList","sanitizeFn"]),es="fade",is="show",ns=".modal",ss="hide.bs.modal",os="hover",rs="focus",as={AUTO:"auto",TOP:"top",RIGHT:Kt()?"left":"right",BOTTOM:"bottom",LEFT:Kt()?"right":"left"},ls={allowList:Yn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'<div class="tooltip" role="tooltip"><div class="tooltip-arrow"></div><div class="tooltip-inner"></div></div>',title:"",trigger:"hover focus"},cs={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class hs extends ve{constructor(t,i){if(void 0===e)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,i),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return ls}static get DefaultType(){return cs}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),fe.off(this._element.closest(ns),ss,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=fe.trigger(this._element,this.constructor.eventName("show")),e=(zt(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),fe.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(is),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.on(t,"mouseover",Rt);this._queueCallback((()=>{fe.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!fe.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(is),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.off(t,"mouseover",Rt);this._activeTrigger.click=!1,this._activeTrigger[rs]=!1,this._activeTrigger[os]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),fe.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(es,is),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(es),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Zn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(es)}_isShown(){return this.tip&&this.tip.classList.contains(is)}_createPopper(t){const e=Xt(this._config.placement,[this,t,this._element]),i=as[e.toUpperCase()];return Dt(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return Xt(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...Xt(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)fe.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===os?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===os?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");fe.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?rs:os]=!0,e._enter()})),fe.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?rs:os]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},fe.on(this._element.closest(ns),ss,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=_e.getDataAttributes(this._element);for(const t of Object.keys(e))ts.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:Ht(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=hs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}Qt(hs);const ds={...hs.Default,content:"",offset:[0,8],placement:"right",template:'<div class="popover" role="tooltip"><div class="popover-arrow"></div><h3 class="popover-header"></h3><div class="popover-body"></div></div>',trigger:"click"},us={...hs.DefaultType,content:"(null|string|element|function)"};class fs extends hs{static get Default(){return ds}static get DefaultType(){return us}static get NAME(){return"popover"}_isWithContent(){return this._getTitle()||this._getContent()}_getContentForTemplate(){return{".popover-header":this._getTitle(),".popover-body":this._getContent()}}_getContent(){return this._resolvePossibleFunction(this._config.content)}static jQueryInterface(t){return this.each((function(){const e=fs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}Qt(fs);const ps=".bs.scrollspy",ms=`activate${ps}`,gs=`click${ps}`,_s=`load${ps}.data-api`,bs="active",vs="[href]",ys=".nav-link",ws=`${ys}, .nav-item > ${ys}, .list-group-item`,Es={offset:null,rootMargin:"0px 0px -25%",smoothScroll:!1,target:null,threshold:[.1,.5,1]},As={offset:"(number|null)",rootMargin:"string",smoothScroll:"boolean",target:"element",threshold:"array"};class Ts extends ve{constructor(t,e){super(t,e),this._targetLinks=new Map,this._observableSections=new Map,this._rootElement="visible"===getComputedStyle(this._element).overflowY?null:this._element,this._activeTarget=null,this._observer=null,this._previousScrollData={visibleEntryTop:0,parentScrollTop:0},this.refresh()}static get Default(){return Es}static get DefaultType(){return As}static get NAME(){return"scrollspy"}refresh(){this._initializeTargetsAndObservables(),this._maybeEnableSmoothScroll(),this._observer?this._observer.disconnect():this._observer=this._getNewObserver();for(const t of this._observableSections.values())this._observer.observe(t)}dispose(){this._observer.disconnect(),super.dispose()}_configAfterMerge(t){return t.target=Ht(t.target)||document.body,t.rootMargin=t.offset?`${t.offset}px 0px -30%`:t.rootMargin,"string"==typeof t.threshold&&(t.threshold=t.threshold.split(",").map((t=>Number.parseFloat(t)))),t}_maybeEnableSmoothScroll(){this._config.smoothScroll&&(fe.off(this._config.target,gs),fe.on(this._config.target,gs,vs,(t=>{const e=this._observableSections.get(t.target.hash);if(e){t.preventDefault();const i=this._rootElement||window,n=e.offsetTop-this._element.offsetTop;if(i.scrollTo)return void i.scrollTo({top:n,behavior:"smooth"});i.scrollTop=n}})))}_getNewObserver(){const t={root:this._rootElement,threshold:this._config.threshold,rootMargin:this._config.rootMargin};return new IntersectionObserver((t=>this._observerCallback(t)),t)}_observerCallback(t){const e=t=>this._targetLinks.get(`#${t.target.id}`),i=t=>{this._previousScrollData.visibleEntryTop=t.target.offsetTop,this._process(e(t))},n=(this._rootElement||document.documentElement).scrollTop,s=n>=this._previousScrollData.parentScrollTop;this._previousScrollData.parentScrollTop=n;for(const o of t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new Map,this._observableSections=new Map;const t=we.find(vs,this._config.target);for(const e of t){if(!e.hash||Wt(e))continue;const t=we.findOne(decodeURI(e.hash),this._element);Bt(t)&&(this._targetLinks.set(decodeURI(e.hash),e),this._observableSections.set(e.hash,t))}}_process(t){this._activeTarget!==t&&(this._clearActiveClass(this._config.target),this._activeTarget=t,t.classList.add(bs),this._activateParents(t),fe.trigger(this._element,ms,{relatedTarget:t}))}_activateParents(t){if(t.classList.contains("dropdown-item"))we.findOne(".dropdown-toggle",t.closest(".dropdown")).classList.add(bs);else for(const e of we.parents(t,".nav, .list-group"))for(const t of we.prev(e,ws))t.classList.add(bs)}_clearActiveClass(t){t.classList.remove(bs);const e=we.find(`${vs}.${bs}`,t);for(const t of e)t.classList.remove(bs)}static jQueryInterface(t){return this.each((function(){const e=Ts.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}fe.on(window,_s,(()=>{for(const t of we.find('[data-bs-spy="scroll"]'))Ts.getOrCreateInstance(t)})),Qt(Ts);const Cs=".bs.tab",Os=`hide${Cs}`,xs=`hidden${Cs}`,ks=`show${Cs}`,Ls=`shown${Cs}`,Ss=`click${Cs}`,Ds=`keydown${Cs}`,$s=`load${Cs}`,Is="ArrowLeft",Ns="ArrowRight",Ps="ArrowUp",Ms="ArrowDown",js="Home",Fs="End",Hs="active",Bs="fade",Ws="show",zs=".dropdown-toggle",Rs=`:not(${zs})`,qs='[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',Vs=`.nav-link${Rs}, .list-group-item${Rs}, [role="tab"]${Rs}, ${qs}`,Ys=`.${Hs}[data-bs-toggle="tab"], .${Hs}[data-bs-toggle="pill"], .${Hs}[data-bs-toggle="list"]`;class Ks extends ve{constructor(t){super(t),this._parent=this._element.closest('.list-group, .nav, [role="tablist"]'),this._parent&&(this._setInitialAttributes(this._parent,this._getChildren()),fe.on(this._element,Ds,(t=>this._keydown(t))))}static get NAME(){return"tab"}show(){const t=this._element;if(this._elemIsActive(t))return;const e=this._getActiveElem(),i=e?fe.trigger(e,Os,{relatedTarget:t}):null;fe.trigger(t,ks,{relatedTarget:e}).defaultPrevented||i&&i.defaultPrevented||(this._deactivate(e,t),this._activate(t,e))}_activate(t,e){t&&(t.classList.add(Hs),this._activate(we.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.removeAttribute("tabindex"),t.setAttribute("aria-selected",!0),this._toggleDropDown(t,!0),fe.trigger(t,Ls,{relatedTarget:e})):t.classList.add(Ws)}),t,t.classList.contains(Bs)))}_deactivate(t,e){t&&(t.classList.remove(Hs),t.blur(),this._deactivate(we.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.setAttribute("aria-selected",!1),t.setAttribute("tabindex","-1"),this._toggleDropDown(t,!1),fe.trigger(t,xs,{relatedTarget:e})):t.classList.remove(Ws)}),t,t.classList.contains(Bs)))}_keydown(t){if(![Is,Ns,Ps,Ms,js,Fs].includes(t.key))return;t.stopPropagation(),t.preventDefault();const e=this._getChildren().filter((t=>!Wt(t)));let i;if([js,Fs].includes(t.key))i=e[t.key===js?0:e.length-1];else{const n=[Ns,Ms].includes(t.key);i=Gt(e,t.target,n,!0)}i&&(i.focus({preventScroll:!0}),Ks.getOrCreateInstance(i).show())}_getChildren(){return we.find(Vs,this._parent)}_getActiveElem(){return this._getChildren().find((t=>this._elemIsActive(t)))||null}_setInitialAttributes(t,e){this._setAttributeIfNotExists(t,"role","tablist");for(const t of e)this._setInitialAttributesOnChild(t)}_setInitialAttributesOnChild(t){t=this._getInnerElement(t);const e=this._elemIsActive(t),i=this._getOuterElement(t);t.setAttribute("aria-selected",e),i!==t&&this._setAttributeIfNotExists(i,"role","presentation"),e||t.setAttribute("tabindex","-1"),this._setAttributeIfNotExists(t,"role","tab"),this._setInitialAttributesOnTargetPanel(t)}_setInitialAttributesOnTargetPanel(t){const e=we.getElementFromSelector(t);e&&(this._setAttributeIfNotExists(e,"role","tabpanel"),t.id&&this._setAttributeIfNotExists(e,"aria-labelledby",`${t.id}`))}_toggleDropDown(t,e){const i=this._getOuterElement(t);if(!i.classList.contains("dropdown"))return;const n=(t,n)=>{const s=we.findOne(t,i);s&&s.classList.toggle(n,e)};n(zs,Hs),n(".dropdown-menu",Ws),i.setAttribute("aria-expanded",e)}_setAttributeIfNotExists(t,e,i){t.hasAttribute(e)||t.setAttribute(e,i)}_elemIsActive(t){return t.classList.contains(Hs)}_getInnerElement(t){return t.matches(Vs)?t:we.findOne(Vs,t)}_getOuterElement(t){return t.closest(".nav-item, .list-group-item")||t}static jQueryInterface(t){return this.each((function(){const e=Ks.getOrCreateInstance(this);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}fe.on(document,Ss,qs,(function(t){["A","AREA"].includes(this.tagName)&&t.preventDefault(),Wt(this)||Ks.getOrCreateInstance(this).show()})),fe.on(window,$s,(()=>{for(const t of we.find(Ys))Ks.getOrCreateInstance(t)})),Qt(Ks);const Qs=".bs.toast",Xs=`mouseover${Qs}`,Us=`mouseout${Qs}`,Gs=`focusin${Qs}`,Js=`focusout${Qs}`,Zs=`hide${Qs}`,to=`hidden${Qs}`,eo=`show${Qs}`,io=`shown${Qs}`,no="hide",so="show",oo="showing",ro={animation:"boolean",autohide:"boolean",delay:"number"},ao={animation:!0,autohide:!0,delay:5e3};class lo extends ve{constructor(t,e){super(t,e),this._timeout=null,this._hasMouseInteraction=!1,this._hasKeyboardInteraction=!1,this._setListeners()}static get Default(){return ao}static get DefaultType(){return ro}static get NAME(){return"toast"}show(){fe.trigger(this._element,eo).defaultPrevented||(this._clearTimeout(),this._config.animation&&this._element.classList.add("fade"),this._element.classList.remove(no),qt(this._element),this._element.classList.add(so,oo),this._queueCallback((()=>{this._element.classList.remove(oo),fe.trigger(this._element,io),this._maybeScheduleHide()}),this._element,this._config.animation))}hide(){this.isShown()&&(fe.trigger(this._element,Zs).defaultPrevented||(this._element.classList.add(oo),this._queueCallback((()=>{this._element.classList.add(no),this._element.classList.remove(oo,so),fe.trigger(this._element,to)}),this._element,this._config.animation)))}dispose(){this._clearTimeout(),this.isShown()&&this._element.classList.remove(so),super.dispose()}isShown(){return 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"${t}"`);e[t](this)}}))}}function co(t){"loading"!=document.readyState?t():document.addEventListener("DOMContentLoaded",t)}Ee(lo),Qt(lo),co((function(){[].slice.call(document.querySelectorAll('[data-bs-toggle="tooltip"]')).map((function(t){return new hs(t,{delay:{show:500,hide:100}})}))})),co((function(){document.getElementById("pst-back-to-top").addEventListener("click",(function(){document.body.scrollTop=0,document.documentElement.scrollTop=0}))})),co((function(){var t=document.getElementById("pst-back-to-top"),e=document.getElementsByClassName("bd-header")[0].getBoundingClientRect();window.addEventListener("scroll",(function(){this.oldScroll>this.scrollY&&this.scrollY>e.bottom?t.style.display="block":t.style.display="none",this.oldScroll=this.scrollY}))})),window.bootstrap=i})();
+//# sourceMappingURL=bootstrap.js.map
\ No newline at end of file
diff --git a/_static/scripts/bootstrap.js.LICENSE.txt b/_static/scripts/bootstrap.js.LICENSE.txt
new file mode 100644
index 0000000..10f979d
--- /dev/null
+++ b/_static/scripts/bootstrap.js.LICENSE.txt
@@ -0,0 +1,5 @@
+/*!
+  * Bootstrap v5.3.2 (https://getbootstrap.com/)
+  * Copyright 2011-2023 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)
+  * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)
+  */
diff --git a/_static/scripts/bootstrap.js.map b/_static/scripts/bootstrap.js.map
new file mode 100644
index 0000000..64e212b
--- /dev/null
+++ b/_static/scripts/bootstrap.js.map
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(element.nodeName || '').toLowerCase() : null;\n}","export default function getWindow(node) {\n  if (node == null) {\n    return window;\n  }\n\n  if (node.toString() !== '[object Window]') {\n    var ownerDocument = node.ownerDocument;\n    return ownerDocument ? ownerDocument.defaultView || window : window;\n  }\n\n  return node;\n}","import getWindow from \"./getWindow.js\";\n\nfunction isElement(node) {\n  var OwnElement = getWindow(node).Element;\n  return node instanceof OwnElement || node instanceof Element;\n}\n\nfunction isHTMLElement(node) {\n  var OwnElement = getWindow(node).HTMLElement;\n  return node instanceof OwnElement || node instanceof HTMLElement;\n}\n\nfunction isShadowRoot(node) {\n  // IE 11 has no ShadowRoot\n  if (typeof ShadowRoot === 'undefined') {\n    return false;\n  }\n\n  var OwnElement = getWindow(node).ShadowRoot;\n  return node instanceof OwnElement || node instanceof ShadowRoot;\n}\n\nexport { isElement, isHTMLElement, isShadowRoot };","import getNodeName from \"../dom-utils/getNodeName.js\";\nimport { isHTMLElement } from \"../dom-utils/instanceOf.js\"; // This modifier takes the styles prepared by the `computeStyles` modifier\n// and applies them to the HTMLElements such as popper and arrow\n\nfunction applyStyles(_ref) {\n  var state = _ref.state;\n  Object.keys(state.elements).forEach(function (name) {\n    var style = state.styles[name] || {};\n    var attributes = state.attributes[name] || {};\n    var element = state.elements[name]; // arrow is optional + virtual elements\n\n    if (!isHTMLElement(element) || !getNodeName(element)) {\n      return;\n    } // Flow doesn't support to extend this property, but it's the most\n    // effective way to apply styles to an HTMLElement\n    // $FlowFixMe[cannot-write]\n\n\n    Object.assign(element.style, style);\n    Object.keys(attributes).forEach(function (name) {\n      var value = attributes[name];\n\n      if (value === false) {\n        element.removeAttribute(name);\n      } else {\n        element.setAttribute(name, value === true ? '' : value);\n      }\n    });\n  });\n}\n\nfunction effect(_ref2) {\n  var state = _ref2.state;\n  var initialStyles = {\n    popper: {\n      position: state.options.strategy,\n      left: '0',\n      top: '0',\n      margin: '0'\n    },\n    arrow: {\n      position: 'absolute'\n    },\n    reference: {}\n  };\n  Object.assign(state.elements.popper.style, initialStyles.popper);\n  state.styles = initialStyles;\n\n  if (state.elements.arrow) {\n    Object.assign(state.elements.arrow.style, initialStyles.arrow);\n  }\n\n  return function () {\n    Object.keys(state.elements).forEach(function (name) {\n      var element = state.elements[name];\n      var attributes = state.attributes[name] || {};\n      var styleProperties = Object.keys(state.styles.hasOwnProperty(name) ? state.styles[name] : initialStyles[name]); // Set all values to an empty string to unset them\n\n      var style = styleProperties.reduce(function (style, property) {\n        style[property] = '';\n        return style;\n      }, {}); // arrow is optional + virtual elements\n\n      if (!isHTMLElement(element) || !getNodeName(element)) {\n        return;\n      }\n\n      Object.assign(element.style, style);\n      Object.keys(attributes).forEach(function (attribute) {\n        element.removeAttribute(attribute);\n      });\n    });\n  };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n  name: 'applyStyles',\n  enabled: true,\n  phase: 'write',\n  fn: applyStyles,\n  effect: effect,\n  requires: ['computeStyles']\n};","import { auto } from \"../enums.js\";\nexport default function getBasePlacement(placement) {\n  return placement.split('-')[0];\n}","export var max = Math.max;\nexport var min = Math.min;\nexport var round = Math.round;","export default function getUAString() {\n  var uaData = navigator.userAgentData;\n\n  if (uaData != null && uaData.brands && Array.isArray(uaData.brands)) {\n    return uaData.brands.map(function (item) {\n      return item.brand + \"/\" + item.version;\n    }).join(' ');\n  }\n\n  return navigator.userAgent;\n}","import getUAString from \"../utils/userAgent.js\";\nexport default function isLayoutViewport() {\n  return !/^((?!chrome|android).)*safari/i.test(getUAString());\n}","import { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport { round } from \"../utils/math.js\";\nimport getWindow from \"./getWindow.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getBoundingClientRect(element, includeScale, isFixedStrategy) {\n  if (includeScale === void 0) {\n    includeScale = false;\n  }\n\n  if (isFixedStrategy === void 0) {\n    isFixedStrategy = false;\n  }\n\n  var clientRect = element.getBoundingClientRect();\n  var scaleX = 1;\n  var scaleY = 1;\n\n  if (includeScale && isHTMLElement(element)) {\n    scaleX = element.offsetWidth > 0 ? round(clientRect.width) / element.offsetWidth || 1 : 1;\n    scaleY = element.offsetHeight > 0 ? round(clientRect.height) / element.offsetHeight || 1 : 1;\n  }\n\n  var _ref = isElement(element) ? getWindow(element) : window,\n      visualViewport = _ref.visualViewport;\n\n  var addVisualOffsets = !isLayoutViewport() && isFixedStrategy;\n  var x = (clientRect.left + (addVisualOffsets && visualViewport ? visualViewport.offsetLeft : 0)) / scaleX;\n  var y = (clientRect.top + (addVisualOffsets && visualViewport ? visualViewport.offsetTop : 0)) / scaleY;\n  var width = clientRect.width / scaleX;\n  var height = clientRect.height / scaleY;\n  return {\n    width: width,\n    height: height,\n    top: y,\n    right: x + width,\n    bottom: y + height,\n    left: x,\n    x: x,\n    y: y\n  };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\"; // Returns the layout rect of an element relative to its offsetParent. Layout\n// means it doesn't take into account transforms.\n\nexport default function getLayoutRect(element) {\n  var clientRect = getBoundingClientRect(element); // Use the clientRect sizes if it's not been transformed.\n  // Fixes https://github.com/popperjs/popper-core/issues/1223\n\n  var width = element.offsetWidth;\n  var height = element.offsetHeight;\n\n  if (Math.abs(clientRect.width - width) <= 1) {\n    width = clientRect.width;\n  }\n\n  if (Math.abs(clientRect.height - height) <= 1) {\n    height = clientRect.height;\n  }\n\n  return {\n    x: element.offsetLeft,\n    y: element.offsetTop,\n    width: width,\n    height: height\n  };\n}","import { isShadowRoot } from \"./instanceOf.js\";\nexport default function contains(parent, child) {\n  var rootNode = child.getRootNode && child.getRootNode(); // First, attempt with faster native method\n\n  if (parent.contains(child)) {\n    return true;\n  } // then fallback to custom implementation with Shadow DOM support\n  else if (rootNode && isShadowRoot(rootNode)) {\n      var next = child;\n\n      do {\n        if (next && parent.isSameNode(next)) {\n          return true;\n        } // $FlowFixMe[prop-missing]: need a better way to handle this...\n\n\n        next = next.parentNode || next.host;\n      } while (next);\n    } // Give up, the result is false\n\n\n  return false;\n}","import getWindow from \"./getWindow.js\";\nexport default function getComputedStyle(element) {\n  return getWindow(element).getComputedStyle(element);\n}","import getNodeName from \"./getNodeName.js\";\nexport default function isTableElement(element) {\n  return ['table', 'td', 'th'].indexOf(getNodeName(element)) >= 0;\n}","import { isElement } from \"./instanceOf.js\";\nexport default function getDocumentElement(element) {\n  // $FlowFixMe[incompatible-return]: assume body is always available\n  return ((isElement(element) ? element.ownerDocument : // $FlowFixMe[prop-missing]\n  element.document) || window.document).documentElement;\n}","import getNodeName from \"./getNodeName.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport { isShadowRoot } from \"./instanceOf.js\";\nexport default function getParentNode(element) {\n  if (getNodeName(element) === 'html') {\n    return element;\n  }\n\n  return (// this is a quicker (but less type safe) way to save quite some bytes from the bundle\n    // $FlowFixMe[incompatible-return]\n    // $FlowFixMe[prop-missing]\n    element.assignedSlot || // step into the shadow DOM of the parent of a slotted node\n    element.parentNode || ( // DOM Element detected\n    isShadowRoot(element) ? element.host : null) || // ShadowRoot detected\n    // $FlowFixMe[incompatible-call]: HTMLElement is a Node\n    getDocumentElement(element) // fallback\n\n  );\n}","import getWindow from \"./getWindow.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isHTMLElement, isShadowRoot } from \"./instanceOf.js\";\nimport isTableElement from \"./isTableElement.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getUAString from \"../utils/userAgent.js\";\n\nfunction getTrueOffsetParent(element) {\n  if (!isHTMLElement(element) || // https://github.com/popperjs/popper-core/issues/837\n  getComputedStyle(element).position === 'fixed') {\n    return null;\n  }\n\n  return element.offsetParent;\n} // `.offsetParent` reports `null` for fixed elements, while absolute elements\n// return the containing block\n\n\nfunction getContainingBlock(element) {\n  var isFirefox = /firefox/i.test(getUAString());\n  var isIE = /Trident/i.test(getUAString());\n\n  if (isIE && isHTMLElement(element)) {\n    // In IE 9, 10 and 11 fixed elements containing block is always established by the viewport\n    var elementCss = getComputedStyle(element);\n\n    if (elementCss.position === 'fixed') {\n      return null;\n    }\n  }\n\n  var currentNode = getParentNode(element);\n\n  if (isShadowRoot(currentNode)) {\n    currentNode = currentNode.host;\n  }\n\n  while (isHTMLElement(currentNode) && ['html', 'body'].indexOf(getNodeName(currentNode)) < 0) {\n    var css = getComputedStyle(currentNode); // This is non-exhaustive but covers the most common CSS properties that\n    // create a containing block.\n    // https://developer.mozilla.org/en-US/docs/Web/CSS/Containing_block#identifying_the_containing_block\n\n    if (css.transform !== 'none' || css.perspective !== 'none' || css.contain === 'paint' || ['transform', 'perspective'].indexOf(css.willChange) !== -1 || isFirefox && css.willChange === 'filter' || isFirefox && css.filter && css.filter !== 'none') {\n      return currentNode;\n    } else {\n      currentNode = currentNode.parentNode;\n    }\n  }\n\n  return null;\n} // Gets the closest ancestor positioned element. Handles some edge cases,\n// such as table ancestors and cross browser bugs.\n\n\nexport default function getOffsetParent(element) {\n  var window = getWindow(element);\n  var offsetParent = getTrueOffsetParent(element);\n\n  while (offsetParent && isTableElement(offsetParent) && getComputedStyle(offsetParent).position === 'static') {\n    offsetParent = getTrueOffsetParent(offsetParent);\n  }\n\n  if (offsetParent && (getNodeName(offsetParent) === 'html' || getNodeName(offsetParent) === 'body' && getComputedStyle(offsetParent).position === 'static')) {\n    return window;\n  }\n\n  return offsetParent || getContainingBlock(element) || window;\n}","export default function getMainAxisFromPlacement(placement) {\n  return ['top', 'bottom'].indexOf(placement) >= 0 ? 'x' : 'y';\n}","import { max as mathMax, min as mathMin } from \"./math.js\";\nexport function within(min, value, max) {\n  return mathMax(min, mathMin(value, max));\n}\nexport function withinMaxClamp(min, value, max) {\n  var v = within(min, value, max);\n  return v > max ? max : v;\n}","import getFreshSideObject from \"./getFreshSideObject.js\";\nexport default function mergePaddingObject(paddingObject) {\n  return Object.assign({}, getFreshSideObject(), paddingObject);\n}","export default function getFreshSideObject() {\n  return {\n    top: 0,\n    right: 0,\n    bottom: 0,\n    left: 0\n  };\n}","export default function expandToHashMap(value, keys) {\n  return keys.reduce(function (hashMap, key) {\n    hashMap[key] = value;\n    return hashMap;\n  }, {});\n}","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport contains from \"../dom-utils/contains.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport { within } from \"../utils/within.js\";\nimport mergePaddingObject from \"../utils/mergePaddingObject.js\";\nimport expandToHashMap from \"../utils/expandToHashMap.js\";\nimport { left, right, basePlacements, top, bottom } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar toPaddingObject = function toPaddingObject(padding, state) {\n  padding = typeof padding === 'function' ? padding(Object.assign({}, state.rects, {\n    placement: state.placement\n  })) : padding;\n  return mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n};\n\nfunction arrow(_ref) {\n  var _state$modifiersData$;\n\n  var state = _ref.state,\n      name = _ref.name,\n      options = _ref.options;\n  var arrowElement = state.elements.arrow;\n  var popperOffsets = state.modifiersData.popperOffsets;\n  var basePlacement = getBasePlacement(state.placement);\n  var axis = getMainAxisFromPlacement(basePlacement);\n  var isVertical = [left, right].indexOf(basePlacement) >= 0;\n  var len = isVertical ? 'height' : 'width';\n\n  if (!arrowElement || !popperOffsets) {\n    return;\n  }\n\n  var paddingObject = toPaddingObject(options.padding, state);\n  var arrowRect = getLayoutRect(arrowElement);\n  var minProp = axis === 'y' ? top : left;\n  var maxProp = axis === 'y' ? bottom : right;\n  var endDiff = state.rects.reference[len] + state.rects.reference[axis] - popperOffsets[axis] - state.rects.popper[len];\n  var startDiff = popperOffsets[axis] - state.rects.reference[axis];\n  var arrowOffsetParent = getOffsetParent(arrowElement);\n  var clientSize = arrowOffsetParent ? axis === 'y' ? arrowOffsetParent.clientHeight || 0 : arrowOffsetParent.clientWidth || 0 : 0;\n  var centerToReference = endDiff / 2 - startDiff / 2; // Make sure the arrow doesn't overflow the popper if the center point is\n  // outside of the popper bounds\n\n  var min = paddingObject[minProp];\n  var max = clientSize - arrowRect[len] - paddingObject[maxProp];\n  var center = clientSize / 2 - arrowRect[len] / 2 + centerToReference;\n  var offset = within(min, center, max); // Prevents breaking syntax highlighting...\n\n  var axisProp = axis;\n  state.modifiersData[name] = (_state$modifiersData$ = {}, _state$modifiersData$[axisProp] = offset, _state$modifiersData$.centerOffset = offset - center, _state$modifiersData$);\n}\n\nfunction effect(_ref2) {\n  var state = _ref2.state,\n      options = _ref2.options;\n  var _options$element = options.element,\n      arrowElement = _options$element === void 0 ? '[data-popper-arrow]' : _options$element;\n\n  if (arrowElement == null) {\n    return;\n  } // CSS selector\n\n\n  if (typeof arrowElement === 'string') {\n    arrowElement = state.elements.popper.querySelector(arrowElement);\n\n    if (!arrowElement) {\n      return;\n    }\n  }\n\n  if (!contains(state.elements.popper, arrowElement)) {\n    return;\n  }\n\n  state.elements.arrow = arrowElement;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n  name: 'arrow',\n  enabled: true,\n  phase: 'main',\n  fn: arrow,\n  effect: effect,\n  requires: ['popperOffsets'],\n  requiresIfExists: ['preventOverflow']\n};","export default function getVariation(placement) {\n  return placement.split('-')[1];\n}","import { top, left, right, bottom, end } from \"../enums.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getWindow from \"../dom-utils/getWindow.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getComputedStyle from \"../dom-utils/getComputedStyle.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport { round } from \"../utils/math.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar unsetSides = {\n  top: 'auto',\n  right: 'auto',\n  bottom: 'auto',\n  left: 'auto'\n}; // Round the offsets to the nearest suitable subpixel based on the DPR.\n// Zooming can change the DPR, but it seems to report a value that will\n// cleanly divide the values into the appropriate subpixels.\n\nfunction roundOffsetsByDPR(_ref, win) {\n  var x = _ref.x,\n      y = _ref.y;\n  var dpr = win.devicePixelRatio || 1;\n  return {\n    x: round(x * dpr) / dpr || 0,\n    y: round(y * dpr) / dpr || 0\n  };\n}\n\nexport function mapToStyles(_ref2) {\n  var _Object$assign2;\n\n  var popper = _ref2.popper,\n      popperRect = _ref2.popperRect,\n      placement = _ref2.placement,\n      variation = _ref2.variation,\n      offsets = _ref2.offsets,\n      position = _ref2.position,\n      gpuAcceleration = _ref2.gpuAcceleration,\n      adaptive = _ref2.adaptive,\n      roundOffsets = _ref2.roundOffsets,\n      isFixed = _ref2.isFixed;\n  var _offsets$x = offsets.x,\n      x = _offsets$x === void 0 ? 0 : _offsets$x,\n      _offsets$y = offsets.y,\n      y = _offsets$y === void 0 ? 0 : _offsets$y;\n\n  var _ref3 = typeof roundOffsets === 'function' ? roundOffsets({\n    x: x,\n    y: y\n  }) : {\n    x: x,\n    y: y\n  };\n\n  x = _ref3.x;\n  y = _ref3.y;\n  var hasX = offsets.hasOwnProperty('x');\n  var hasY = offsets.hasOwnProperty('y');\n  var sideX = left;\n  var sideY = top;\n  var win = window;\n\n  if (adaptive) {\n    var offsetParent = getOffsetParent(popper);\n    var heightProp = 'clientHeight';\n    var widthProp = 'clientWidth';\n\n    if (offsetParent === getWindow(popper)) {\n      offsetParent = getDocumentElement(popper);\n\n      if (getComputedStyle(offsetParent).position !== 'static' && position === 'absolute') {\n        heightProp = 'scrollHeight';\n        widthProp = 'scrollWidth';\n      }\n    } // $FlowFixMe[incompatible-cast]: force type refinement, we compare offsetParent with window above, but Flow doesn't detect it\n\n\n    offsetParent = offsetParent;\n\n    if (placement === top || (placement === left || placement === right) && variation === end) {\n      sideY = bottom;\n      var offsetY = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.height : // $FlowFixMe[prop-missing]\n      offsetParent[heightProp];\n      y -= offsetY - popperRect.height;\n      y *= gpuAcceleration ? 1 : -1;\n    }\n\n    if (placement === left || (placement === top || placement === bottom) && variation === end) {\n      sideX = right;\n      var offsetX = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.width : // $FlowFixMe[prop-missing]\n      offsetParent[widthProp];\n      x -= offsetX - popperRect.width;\n      x *= gpuAcceleration ? 1 : -1;\n    }\n  }\n\n  var commonStyles = Object.assign({\n    position: position\n  }, adaptive && unsetSides);\n\n  var _ref4 = roundOffsets === true ? roundOffsetsByDPR({\n    x: x,\n    y: y\n  }, getWindow(popper)) : {\n    x: x,\n    y: y\n  };\n\n  x = _ref4.x;\n  y = _ref4.y;\n\n  if (gpuAcceleration) {\n    var _Object$assign;\n\n    return Object.assign({}, commonStyles, (_Object$assign = {}, _Object$assign[sideY] = hasY ? '0' : '', _Object$assign[sideX] = hasX ? '0' : '', _Object$assign.transform = (win.devicePixelRatio || 1) <= 1 ? \"translate(\" + x + \"px, \" + y + \"px)\" : \"translate3d(\" + x + \"px, \" + y + \"px, 0)\", _Object$assign));\n  }\n\n  return Object.assign({}, commonStyles, (_Object$assign2 = {}, _Object$assign2[sideY] = hasY ? y + \"px\" : '', _Object$assign2[sideX] = hasX ? x + \"px\" : '', _Object$assign2.transform = '', _Object$assign2));\n}\n\nfunction computeStyles(_ref5) {\n  var state = _ref5.state,\n      options = _ref5.options;\n  var _options$gpuAccelerat = options.gpuAcceleration,\n      gpuAcceleration = _options$gpuAccelerat === void 0 ? true : _options$gpuAccelerat,\n      _options$adaptive = options.adaptive,\n      adaptive = _options$adaptive === void 0 ? true : _options$adaptive,\n      _options$roundOffsets = options.roundOffsets,\n      roundOffsets = _options$roundOffsets === void 0 ? true : _options$roundOffsets;\n  var commonStyles = {\n    placement: getBasePlacement(state.placement),\n    variation: getVariation(state.placement),\n    popper: state.elements.popper,\n    popperRect: state.rects.popper,\n    gpuAcceleration: gpuAcceleration,\n    isFixed: state.options.strategy === 'fixed'\n  };\n\n  if (state.modifiersData.popperOffsets != null) {\n    state.styles.popper = Object.assign({}, state.styles.popper, mapToStyles(Object.assign({}, commonStyles, {\n      offsets: state.modifiersData.popperOffsets,\n      position: state.options.strategy,\n      adaptive: adaptive,\n      roundOffsets: roundOffsets\n    })));\n  }\n\n  if (state.modifiersData.arrow != null) {\n    state.styles.arrow = Object.assign({}, state.styles.arrow, mapToStyles(Object.assign({}, commonStyles, {\n      offsets: state.modifiersData.arrow,\n      position: 'absolute',\n      adaptive: false,\n      roundOffsets: roundOffsets\n    })));\n  }\n\n  state.attributes.popper = Object.assign({}, state.attributes.popper, {\n    'data-popper-placement': state.placement\n  });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n  name: 'computeStyles',\n  enabled: true,\n  phase: 'beforeWrite',\n  fn: computeStyles,\n  data: {}\n};","import getWindow from \"../dom-utils/getWindow.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar passive = {\n  passive: true\n};\n\nfunction effect(_ref) {\n  var state = _ref.state,\n      instance = _ref.instance,\n      options = _ref.options;\n  var _options$scroll = options.scroll,\n      scroll = _options$scroll === void 0 ? true : _options$scroll,\n      _options$resize = options.resize,\n      resize = _options$resize === void 0 ? true : _options$resize;\n  var window = getWindow(state.elements.popper);\n  var scrollParents = [].concat(state.scrollParents.reference, state.scrollParents.popper);\n\n  if (scroll) {\n    scrollParents.forEach(function (scrollParent) {\n      scrollParent.addEventListener('scroll', instance.update, passive);\n    });\n  }\n\n  if (resize) {\n    window.addEventListener('resize', instance.update, passive);\n  }\n\n  return function () {\n    if (scroll) {\n      scrollParents.forEach(function (scrollParent) {\n        scrollParent.removeEventListener('scroll', instance.update, passive);\n      });\n    }\n\n    if (resize) {\n      window.removeEventListener('resize', instance.update, passive);\n    }\n  };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n  name: 'eventListeners',\n  enabled: true,\n  phase: 'write',\n  fn: function fn() {},\n  effect: effect,\n  data: {}\n};","var hash = {\n  left: 'right',\n  right: 'left',\n  bottom: 'top',\n  top: 'bottom'\n};\nexport default function getOppositePlacement(placement) {\n  return placement.replace(/left|right|bottom|top/g, function (matched) {\n    return hash[matched];\n  });\n}","var hash = {\n  start: 'end',\n  end: 'start'\n};\nexport default function getOppositeVariationPlacement(placement) {\n  return placement.replace(/start|end/g, function (matched) {\n    return hash[matched];\n  });\n}","import getWindow from \"./getWindow.js\";\nexport default function getWindowScroll(node) {\n  var win = getWindow(node);\n  var scrollLeft = win.pageXOffset;\n  var scrollTop = win.pageYOffset;\n  return {\n    scrollLeft: scrollLeft,\n    scrollTop: scrollTop\n  };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nexport default function getWindowScrollBarX(element) {\n  // If <html> has a CSS width greater than the viewport, then this will be\n  // incorrect for RTL.\n  // Popper 1 is broken in this case and never had a bug report so let's assume\n  // it's not an issue. I don't think anyone ever specifies width on <html>\n  // anyway.\n  // Browsers where the left scrollbar doesn't cause an issue report `0` for\n  // this (e.g. Edge 2019, IE11, Safari)\n  return getBoundingClientRect(getDocumentElement(element)).left + getWindowScroll(element).scrollLeft;\n}","import getComputedStyle from \"./getComputedStyle.js\";\nexport default function isScrollParent(element) {\n  // Firefox wants us to check `-x` and `-y` variations as well\n  var _getComputedStyle = getComputedStyle(element),\n      overflow = _getComputedStyle.overflow,\n      overflowX = _getComputedStyle.overflowX,\n      overflowY = _getComputedStyle.overflowY;\n\n  return /auto|scroll|overlay|hidden/.test(overflow + overflowY + overflowX);\n}","import getParentNode from \"./getParentNode.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nexport default function getScrollParent(node) {\n  if (['html', 'body', '#document'].indexOf(getNodeName(node)) >= 0) {\n    // $FlowFixMe[incompatible-return]: assume body is always available\n    return node.ownerDocument.body;\n  }\n\n  if (isHTMLElement(node) && isScrollParent(node)) {\n    return node;\n  }\n\n  return getScrollParent(getParentNode(node));\n}","import getScrollParent from \"./getScrollParent.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getWindow from \"./getWindow.js\";\nimport isScrollParent from \"./isScrollParent.js\";\n/*\ngiven a DOM element, return the list of all scroll parents, up the list of ancesors\nuntil we get to the top window object. This list is what we attach scroll listeners\nto, because if any of these parent elements scroll, we'll need to re-calculate the\nreference element's position.\n*/\n\nexport default function listScrollParents(element, list) {\n  var _element$ownerDocumen;\n\n  if (list === void 0) {\n    list = [];\n  }\n\n  var scrollParent = getScrollParent(element);\n  var isBody = scrollParent === ((_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body);\n  var win = getWindow(scrollParent);\n  var target = isBody ? [win].concat(win.visualViewport || [], isScrollParent(scrollParent) ? scrollParent : []) : scrollParent;\n  var updatedList = list.concat(target);\n  return isBody ? updatedList : // $FlowFixMe[incompatible-call]: isBody tells us target will be an HTMLElement here\n  updatedList.concat(listScrollParents(getParentNode(target)));\n}","export default function rectToClientRect(rect) {\n  return Object.assign({}, rect, {\n    left: rect.x,\n    top: rect.y,\n    right: rect.x + rect.width,\n    bottom: rect.y + rect.height\n  });\n}","import { viewport } from \"../enums.js\";\nimport getViewportRect from \"./getViewportRect.js\";\nimport getDocumentRect from \"./getDocumentRect.js\";\nimport listScrollParents from \"./listScrollParents.js\";\nimport getOffsetParent from \"./getOffsetParent.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport contains from \"./contains.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport rectToClientRect from \"../utils/rectToClientRect.js\";\nimport { max, min } from \"../utils/math.js\";\n\nfunction getInnerBoundingClientRect(element, strategy) {\n  var rect = getBoundingClientRect(element, false, strategy === 'fixed');\n  rect.top = rect.top + element.clientTop;\n  rect.left = rect.left + element.clientLeft;\n  rect.bottom = rect.top + element.clientHeight;\n  rect.right = rect.left + element.clientWidth;\n  rect.width = element.clientWidth;\n  rect.height = element.clientHeight;\n  rect.x = rect.left;\n  rect.y = rect.top;\n  return rect;\n}\n\nfunction getClientRectFromMixedType(element, clippingParent, strategy) {\n  return clippingParent === viewport ? rectToClientRect(getViewportRect(element, strategy)) : isElement(clippingParent) ? getInnerBoundingClientRect(clippingParent, strategy) : rectToClientRect(getDocumentRect(getDocumentElement(element)));\n} // A \"clipping parent\" is an overflowable container with the characteristic of\n// clipping (or hiding) overflowing elements with a position different from\n// `initial`\n\n\nfunction getClippingParents(element) {\n  var clippingParents = listScrollParents(getParentNode(element));\n  var canEscapeClipping = ['absolute', 'fixed'].indexOf(getComputedStyle(element).position) >= 0;\n  var clipperElement = canEscapeClipping && isHTMLElement(element) ? getOffsetParent(element) : element;\n\n  if (!isElement(clipperElement)) {\n    return [];\n  } // $FlowFixMe[incompatible-return]: https://github.com/facebook/flow/issues/1414\n\n\n  return clippingParents.filter(function (clippingParent) {\n    return isElement(clippingParent) && contains(clippingParent, clipperElement) && getNodeName(clippingParent) !== 'body';\n  });\n} // Gets the maximum area that the element is visible in due to any number of\n// clipping parents\n\n\nexport default function getClippingRect(element, boundary, rootBoundary, strategy) {\n  var mainClippingParents = boundary === 'clippingParents' ? getClippingParents(element) : [].concat(boundary);\n  var clippingParents = [].concat(mainClippingParents, [rootBoundary]);\n  var firstClippingParent = clippingParents[0];\n  var clippingRect = clippingParents.reduce(function (accRect, clippingParent) {\n    var rect = getClientRectFromMixedType(element, clippingParent, strategy);\n    accRect.top = max(rect.top, accRect.top);\n    accRect.right = min(rect.right, accRect.right);\n    accRect.bottom = min(rect.bottom, accRect.bottom);\n    accRect.left = max(rect.left, accRect.left);\n    return accRect;\n  }, getClientRectFromMixedType(element, firstClippingParent, strategy));\n  clippingRect.width = clippingRect.right - clippingRect.left;\n  clippingRect.height = clippingRect.bottom - clippingRect.top;\n  clippingRect.x = clippingRect.left;\n  clippingRect.y = clippingRect.top;\n  return clippingRect;\n}","import getWindow from \"./getWindow.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getViewportRect(element, strategy) {\n  var win = getWindow(element);\n  var html = getDocumentElement(element);\n  var visualViewport = win.visualViewport;\n  var width = html.clientWidth;\n  var height = html.clientHeight;\n  var x = 0;\n  var y = 0;\n\n  if (visualViewport) {\n    width = visualViewport.width;\n    height = visualViewport.height;\n    var layoutViewport = isLayoutViewport();\n\n    if (layoutViewport || !layoutViewport && strategy === 'fixed') {\n      x = visualViewport.offsetLeft;\n      y = visualViewport.offsetTop;\n    }\n  }\n\n  return {\n    width: width,\n    height: height,\n    x: x + getWindowScrollBarX(element),\n    y: y\n  };\n}","import getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nimport { max } from \"../utils/math.js\"; // Gets the entire size of the scrollable document area, even extending outside\n// of the `<html>` and `<body>` rect bounds if horizontally scrollable\n\nexport default function getDocumentRect(element) {\n  var _element$ownerDocumen;\n\n  var html = getDocumentElement(element);\n  var winScroll = getWindowScroll(element);\n  var body = (_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body;\n  var width = max(html.scrollWidth, html.clientWidth, body ? body.scrollWidth : 0, body ? body.clientWidth : 0);\n  var height = max(html.scrollHeight, html.clientHeight, body ? body.scrollHeight : 0, body ? body.clientHeight : 0);\n  var x = -winScroll.scrollLeft + getWindowScrollBarX(element);\n  var y = -winScroll.scrollTop;\n\n  if (getComputedStyle(body || html).direction === 'rtl') {\n    x += max(html.clientWidth, body ? body.clientWidth : 0) - width;\n  }\n\n  return {\n    width: width,\n    height: height,\n    x: x,\n    y: y\n  };\n}","import getBasePlacement from \"./getBasePlacement.js\";\nimport getVariation from \"./getVariation.js\";\nimport getMainAxisFromPlacement from \"./getMainAxisFromPlacement.js\";\nimport { top, right, bottom, left, start, end } from \"../enums.js\";\nexport default function computeOffsets(_ref) {\n  var reference = _ref.reference,\n      element = _ref.element,\n      placement = _ref.placement;\n  var basePlacement = placement ? getBasePlacement(placement) : null;\n  var variation = placement ? getVariation(placement) : null;\n  var commonX = reference.x + reference.width / 2 - element.width / 2;\n  var commonY = reference.y + reference.height / 2 - element.height / 2;\n  var offsets;\n\n  switch (basePlacement) {\n    case top:\n      offsets = {\n        x: commonX,\n        y: reference.y - element.height\n      };\n      break;\n\n    case bottom:\n      offsets = {\n        x: commonX,\n        y: reference.y + reference.height\n      };\n      break;\n\n    case right:\n      offsets = {\n        x: reference.x + reference.width,\n        y: commonY\n      };\n      break;\n\n    case left:\n      offsets = {\n        x: reference.x - element.width,\n        y: commonY\n      };\n      break;\n\n    default:\n      offsets = {\n        x: reference.x,\n        y: reference.y\n      };\n  }\n\n  var mainAxis = basePlacement ? getMainAxisFromPlacement(basePlacement) : null;\n\n  if (mainAxis != null) {\n    var len = mainAxis === 'y' ? 'height' : 'width';\n\n    switch (variation) {\n      case start:\n        offsets[mainAxis] = offsets[mainAxis] - (reference[len] / 2 - element[len] / 2);\n        break;\n\n      case end:\n        offsets[mainAxis] = offsets[mainAxis] + (reference[len] / 2 - element[len] / 2);\n        break;\n\n      default:\n    }\n  }\n\n  return offsets;\n}","import getClippingRect from \"../dom-utils/getClippingRect.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getBoundingClientRect from \"../dom-utils/getBoundingClientRect.js\";\nimport computeOffsets from \"./computeOffsets.js\";\nimport rectToClientRect from \"./rectToClientRect.js\";\nimport { clippingParents, reference, popper, bottom, top, right, basePlacements, viewport } from \"../enums.js\";\nimport { isElement } from \"../dom-utils/instanceOf.js\";\nimport mergePaddingObject from \"./mergePaddingObject.js\";\nimport expandToHashMap from \"./expandToHashMap.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport default function detectOverflow(state, options) {\n  if (options === void 0) {\n    options = {};\n  }\n\n  var _options = options,\n      _options$placement = _options.placement,\n      placement = _options$placement === void 0 ? state.placement : _options$placement,\n      _options$strategy = _options.strategy,\n      strategy = _options$strategy === void 0 ? state.strategy : _options$strategy,\n      _options$boundary = _options.boundary,\n      boundary = _options$boundary === void 0 ? clippingParents : _options$boundary,\n      _options$rootBoundary = _options.rootBoundary,\n      rootBoundary = _options$rootBoundary === void 0 ? viewport : _options$rootBoundary,\n      _options$elementConte = _options.elementContext,\n      elementContext = _options$elementConte === void 0 ? popper : _options$elementConte,\n      _options$altBoundary = _options.altBoundary,\n      altBoundary = _options$altBoundary === void 0 ? false : _options$altBoundary,\n      _options$padding = _options.padding,\n      padding = _options$padding === void 0 ? 0 : _options$padding;\n  var paddingObject = mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n  var altContext = elementContext === popper ? reference : popper;\n  var popperRect = state.rects.popper;\n  var element = state.elements[altBoundary ? altContext : elementContext];\n  var clippingClientRect = getClippingRect(isElement(element) ? element : element.contextElement || getDocumentElement(state.elements.popper), boundary, rootBoundary, strategy);\n  var referenceClientRect = getBoundingClientRect(state.elements.reference);\n  var popperOffsets = computeOffsets({\n    reference: referenceClientRect,\n    element: popperRect,\n    strategy: 'absolute',\n    placement: placement\n  });\n  var popperClientRect = rectToClientRect(Object.assign({}, popperRect, popperOffsets));\n  var elementClientRect = elementContext === popper ? popperClientRect : referenceClientRect; // positive = overflowing the clipping rect\n  // 0 or negative = within the clipping rect\n\n  var overflowOffsets = {\n    top: clippingClientRect.top - elementClientRect.top + paddingObject.top,\n    bottom: elementClientRect.bottom - clippingClientRect.bottom + paddingObject.bottom,\n    left: clippingClientRect.left - elementClientRect.left + paddingObject.left,\n    right: elementClientRect.right - clippingClientRect.right + paddingObject.right\n  };\n  var offsetData = state.modifiersData.offset; // Offsets can be applied only to the popper element\n\n  if (elementContext === popper && offsetData) {\n    var offset = offsetData[placement];\n    Object.keys(overflowOffsets).forEach(function (key) {\n      var multiply = [right, bottom].indexOf(key) >= 0 ? 1 : -1;\n      var axis = [top, bottom].indexOf(key) >= 0 ? 'y' : 'x';\n      overflowOffsets[key] += offset[axis] * multiply;\n    });\n  }\n\n  return overflowOffsets;\n}","import getOppositePlacement from \"../utils/getOppositePlacement.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getOppositeVariationPlacement from \"../utils/getOppositeVariationPlacement.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport computeAutoPlacement from \"../utils/computeAutoPlacement.js\";\nimport { bottom, top, start, right, left, auto } from \"../enums.js\";\nimport getVariation from \"../utils/getVariation.js\"; // eslint-disable-next-line import/no-unused-modules\n\nfunction getExpandedFallbackPlacements(placement) {\n  if (getBasePlacement(placement) === auto) {\n    return [];\n  }\n\n  var oppositePlacement = getOppositePlacement(placement);\n  return [getOppositeVariationPlacement(placement), oppositePlacement, getOppositeVariationPlacement(oppositePlacement)];\n}\n\nfunction flip(_ref) {\n  var state = _ref.state,\n      options = _ref.options,\n      name = _ref.name;\n\n  if (state.modifiersData[name]._skip) {\n    return;\n  }\n\n  var _options$mainAxis = options.mainAxis,\n      checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n      _options$altAxis = options.altAxis,\n      checkAltAxis = _options$altAxis === void 0 ? true : _options$altAxis,\n      specifiedFallbackPlacements = options.fallbackPlacements,\n      padding = options.padding,\n      boundary = options.boundary,\n      rootBoundary = options.rootBoundary,\n      altBoundary = options.altBoundary,\n      _options$flipVariatio = options.flipVariations,\n      flipVariations = _options$flipVariatio === void 0 ? true : _options$flipVariatio,\n      allowedAutoPlacements = options.allowedAutoPlacements;\n  var preferredPlacement = state.options.placement;\n  var basePlacement = getBasePlacement(preferredPlacement);\n  var isBasePlacement = basePlacement === preferredPlacement;\n  var fallbackPlacements = specifiedFallbackPlacements || (isBasePlacement || !flipVariations ? [getOppositePlacement(preferredPlacement)] : getExpandedFallbackPlacements(preferredPlacement));\n  var placements = [preferredPlacement].concat(fallbackPlacements).reduce(function (acc, placement) {\n    return acc.concat(getBasePlacement(placement) === auto ? computeAutoPlacement(state, {\n      placement: placement,\n      boundary: boundary,\n      rootBoundary: rootBoundary,\n      padding: padding,\n      flipVariations: flipVariations,\n      allowedAutoPlacements: allowedAutoPlacements\n    }) : placement);\n  }, []);\n  var referenceRect = state.rects.reference;\n  var popperRect = state.rects.popper;\n  var checksMap = new Map();\n  var makeFallbackChecks = true;\n  var firstFittingPlacement = placements[0];\n\n  for (var i = 0; i < placements.length; i++) {\n    var placement = placements[i];\n\n    var _basePlacement = getBasePlacement(placement);\n\n    var isStartVariation = getVariation(placement) === start;\n    var isVertical = [top, bottom].indexOf(_basePlacement) >= 0;\n    var len = isVertical ? 'width' : 'height';\n    var overflow = detectOverflow(state, {\n      placement: placement,\n      boundary: boundary,\n      rootBoundary: rootBoundary,\n      altBoundary: altBoundary,\n      padding: padding\n    });\n    var mainVariationSide = isVertical ? isStartVariation ? right : left : isStartVariation ? bottom : top;\n\n    if (referenceRect[len] > popperRect[len]) {\n      mainVariationSide = getOppositePlacement(mainVariationSide);\n    }\n\n    var altVariationSide = getOppositePlacement(mainVariationSide);\n    var checks = [];\n\n    if (checkMainAxis) {\n      checks.push(overflow[_basePlacement] <= 0);\n    }\n\n    if (checkAltAxis) {\n      checks.push(overflow[mainVariationSide] <= 0, overflow[altVariationSide] <= 0);\n    }\n\n    if (checks.every(function (check) {\n      return check;\n    })) {\n      firstFittingPlacement = placement;\n      makeFallbackChecks = false;\n      break;\n    }\n\n    checksMap.set(placement, checks);\n  }\n\n  if (makeFallbackChecks) {\n    // `2` may be desired in some cases – research later\n    var numberOfChecks = flipVariations ? 3 : 1;\n\n    var _loop = function _loop(_i) {\n      var fittingPlacement = placements.find(function (placement) {\n        var checks = checksMap.get(placement);\n\n        if (checks) {\n          return checks.slice(0, _i).every(function (check) {\n            return check;\n          });\n        }\n      });\n\n      if (fittingPlacement) {\n        firstFittingPlacement = fittingPlacement;\n        return \"break\";\n      }\n    };\n\n    for (var _i = numberOfChecks; _i > 0; _i--) {\n      var _ret = _loop(_i);\n\n      if (_ret === \"break\") break;\n    }\n  }\n\n  if (state.placement !== firstFittingPlacement) {\n    state.modifiersData[name]._skip = true;\n    state.placement = firstFittingPlacement;\n    state.reset = true;\n  }\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n  name: 'flip',\n  enabled: true,\n  phase: 'main',\n  fn: flip,\n  requiresIfExists: ['offset'],\n  data: {\n    _skip: false\n  }\n};","import getVariation from \"./getVariation.js\";\nimport { variationPlacements, basePlacements, placements as allPlacements } from \"../enums.js\";\nimport detectOverflow from \"./detectOverflow.js\";\nimport getBasePlacement from \"./getBasePlacement.js\";\nexport default function computeAutoPlacement(state, options) {\n  if (options === void 0) {\n    options = {};\n  }\n\n  var _options = options,\n      placement = _options.placement,\n      boundary = _options.boundary,\n      rootBoundary = _options.rootBoundary,\n      padding = _options.padding,\n      flipVariations = _options.flipVariations,\n      _options$allowedAutoP = _options.allowedAutoPlacements,\n      allowedAutoPlacements = _options$allowedAutoP === void 0 ? allPlacements : _options$allowedAutoP;\n  var variation = getVariation(placement);\n  var placements = variation ? flipVariations ? variationPlacements : variationPlacements.filter(function (placement) {\n    return getVariation(placement) === variation;\n  }) : basePlacements;\n  var allowedPlacements = placements.filter(function (placement) {\n    return allowedAutoPlacements.indexOf(placement) >= 0;\n  });\n\n  if (allowedPlacements.length === 0) {\n    allowedPlacements = placements;\n  } // $FlowFixMe[incompatible-type]: Flow seems to have problems with two array unions...\n\n\n  var overflows = allowedPlacements.reduce(function (acc, placement) {\n    acc[placement] = detectOverflow(state, {\n      placement: placement,\n      boundary: boundary,\n      rootBoundary: rootBoundary,\n      padding: padding\n    })[getBasePlacement(placement)];\n    return acc;\n  }, {});\n  return Object.keys(overflows).sort(function (a, b) {\n    return overflows[a] - overflows[b];\n  });\n}","import { top, bottom, left, right } from \"../enums.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\n\nfunction getSideOffsets(overflow, rect, preventedOffsets) {\n  if (preventedOffsets === void 0) {\n    preventedOffsets = {\n      x: 0,\n      y: 0\n    };\n  }\n\n  return {\n    top: overflow.top - rect.height - preventedOffsets.y,\n    right: overflow.right - rect.width + preventedOffsets.x,\n    bottom: overflow.bottom - rect.height + preventedOffsets.y,\n    left: overflow.left - rect.width - preventedOffsets.x\n  };\n}\n\nfunction isAnySideFullyClipped(overflow) {\n  return [top, right, bottom, left].some(function (side) {\n    return overflow[side] >= 0;\n  });\n}\n\nfunction hide(_ref) {\n  var state = _ref.state,\n      name = _ref.name;\n  var referenceRect = state.rects.reference;\n  var popperRect = state.rects.popper;\n  var preventedOffsets = state.modifiersData.preventOverflow;\n  var referenceOverflow = detectOverflow(state, {\n    elementContext: 'reference'\n  });\n  var popperAltOverflow = detectOverflow(state, {\n    altBoundary: true\n  });\n  var referenceClippingOffsets = getSideOffsets(referenceOverflow, referenceRect);\n  var popperEscapeOffsets = getSideOffsets(popperAltOverflow, popperRect, preventedOffsets);\n  var isReferenceHidden = isAnySideFullyClipped(referenceClippingOffsets);\n  var hasPopperEscaped = isAnySideFullyClipped(popperEscapeOffsets);\n  state.modifiersData[name] = {\n    referenceClippingOffsets: referenceClippingOffsets,\n    popperEscapeOffsets: popperEscapeOffsets,\n    isReferenceHidden: isReferenceHidden,\n    hasPopperEscaped: hasPopperEscaped\n  };\n  state.attributes.popper = Object.assign({}, state.attributes.popper, {\n    'data-popper-reference-hidden': isReferenceHidden,\n    'data-popper-escaped': hasPopperEscaped\n  });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n  name: 'hide',\n  enabled: true,\n  phase: 'main',\n  requiresIfExists: ['preventOverflow'],\n  fn: hide\n};","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport { top, left, right, placements } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport function distanceAndSkiddingToXY(placement, rects, offset) {\n  var basePlacement = getBasePlacement(placement);\n  var invertDistance = [left, top].indexOf(basePlacement) >= 0 ? -1 : 1;\n\n  var _ref = typeof offset === 'function' ? offset(Object.assign({}, rects, {\n    placement: placement\n  })) : offset,\n      skidding = _ref[0],\n      distance = _ref[1];\n\n  skidding = skidding || 0;\n  distance = (distance || 0) * invertDistance;\n  return [left, right].indexOf(basePlacement) >= 0 ? {\n    x: distance,\n    y: skidding\n  } : {\n    x: skidding,\n    y: distance\n  };\n}\n\nfunction offset(_ref2) {\n  var state = _ref2.state,\n      options = _ref2.options,\n      name = _ref2.name;\n  var _options$offset = options.offset,\n      offset = _options$offset === void 0 ? [0, 0] : _options$offset;\n  var data = placements.reduce(function (acc, placement) {\n    acc[placement] = distanceAndSkiddingToXY(placement, state.rects, offset);\n    return acc;\n  }, {});\n  var _data$state$placement = data[state.placement],\n      x = _data$state$placement.x,\n      y = _data$state$placement.y;\n\n  if (state.modifiersData.popperOffsets != null) {\n    state.modifiersData.popperOffsets.x += x;\n    state.modifiersData.popperOffsets.y += y;\n  }\n\n  state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n  name: 'offset',\n  enabled: true,\n  phase: 'main',\n  requires: ['popperOffsets'],\n  fn: offset\n};","import computeOffsets from \"../utils/computeOffsets.js\";\n\nfunction popperOffsets(_ref) {\n  var state = _ref.state,\n      name = _ref.name;\n  // Offsets are the actual position the popper needs to have to be\n  // properly positioned near its reference element\n  // This is the most basic placement, and will be adjusted by\n  // the modifiers in the next step\n  state.modifiersData[name] = computeOffsets({\n    reference: state.rects.reference,\n    element: state.rects.popper,\n    strategy: 'absolute',\n    placement: state.placement\n  });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n  name: 'popperOffsets',\n  enabled: true,\n  phase: 'read',\n  fn: popperOffsets,\n  data: {}\n};","import { top, left, right, bottom, start } from \"../enums.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport getAltAxis from \"../utils/getAltAxis.js\";\nimport { within, withinMaxClamp } from \"../utils/within.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport getFreshSideObject from \"../utils/getFreshSideObject.js\";\nimport { min as mathMin, max as mathMax } from \"../utils/math.js\";\n\nfunction preventOverflow(_ref) {\n  var state = _ref.state,\n      options = _ref.options,\n      name = _ref.name;\n  var _options$mainAxis = options.mainAxis,\n      checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n      _options$altAxis = options.altAxis,\n      checkAltAxis = _options$altAxis === void 0 ? false : _options$altAxis,\n      boundary = options.boundary,\n      rootBoundary = options.rootBoundary,\n      altBoundary = options.altBoundary,\n      padding = options.padding,\n      _options$tether = options.tether,\n      tether = _options$tether === void 0 ? true : _options$tether,\n      _options$tetherOffset = options.tetherOffset,\n      tetherOffset = _options$tetherOffset === void 0 ? 0 : _options$tetherOffset;\n  var overflow = detectOverflow(state, {\n    boundary: boundary,\n    rootBoundary: rootBoundary,\n    padding: padding,\n    altBoundary: altBoundary\n  });\n  var basePlacement = getBasePlacement(state.placement);\n  var variation = getVariation(state.placement);\n  var isBasePlacement = !variation;\n  var mainAxis = getMainAxisFromPlacement(basePlacement);\n  var altAxis = getAltAxis(mainAxis);\n  var popperOffsets = state.modifiersData.popperOffsets;\n  var referenceRect = state.rects.reference;\n  var popperRect = state.rects.popper;\n  var tetherOffsetValue = typeof tetherOffset === 'function' ? tetherOffset(Object.assign({}, state.rects, {\n    placement: state.placement\n  })) : tetherOffset;\n  var normalizedTetherOffsetValue = typeof tetherOffsetValue === 'number' ? {\n    mainAxis: tetherOffsetValue,\n    altAxis: tetherOffsetValue\n  } : Object.assign({\n    mainAxis: 0,\n    altAxis: 0\n  }, tetherOffsetValue);\n  var offsetModifierState = state.modifiersData.offset ? state.modifiersData.offset[state.placement] : null;\n  var data = {\n    x: 0,\n    y: 0\n  };\n\n  if (!popperOffsets) {\n    return;\n  }\n\n  if (checkMainAxis) {\n    var _offsetModifierState$;\n\n    var mainSide = mainAxis === 'y' ? top : left;\n    var altSide = mainAxis === 'y' ? bottom : right;\n    var len = mainAxis === 'y' ? 'height' : 'width';\n    var offset = popperOffsets[mainAxis];\n    var min = offset + overflow[mainSide];\n    var max = offset - overflow[altSide];\n    var additive = tether ? -popperRect[len] / 2 : 0;\n    var minLen = variation === start ? referenceRect[len] : popperRect[len];\n    var maxLen = variation === start ? -popperRect[len] : -referenceRect[len]; // We need to include the arrow in the calculation so the arrow doesn't go\n    // outside the reference bounds\n\n    var arrowElement = state.elements.arrow;\n    var arrowRect = tether && arrowElement ? getLayoutRect(arrowElement) : {\n      width: 0,\n      height: 0\n    };\n    var arrowPaddingObject = state.modifiersData['arrow#persistent'] ? state.modifiersData['arrow#persistent'].padding : getFreshSideObject();\n    var arrowPaddingMin = arrowPaddingObject[mainSide];\n    var arrowPaddingMax = arrowPaddingObject[altSide]; // If the reference length is smaller than the arrow length, we don't want\n    // to include its full size in the calculation. If the reference is small\n    // and near the edge of a boundary, the popper can overflow even if the\n    // reference is not overflowing as well (e.g. virtual elements with no\n    // width or height)\n\n    var arrowLen = within(0, referenceRect[len], arrowRect[len]);\n    var minOffset = isBasePlacement ? referenceRect[len] / 2 - additive - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis : minLen - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis;\n    var maxOffset = isBasePlacement ? -referenceRect[len] / 2 + additive + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis : maxLen + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis;\n    var arrowOffsetParent = state.elements.arrow && getOffsetParent(state.elements.arrow);\n    var clientOffset = arrowOffsetParent ? mainAxis === 'y' ? arrowOffsetParent.clientTop || 0 : arrowOffsetParent.clientLeft || 0 : 0;\n    var offsetModifierValue = (_offsetModifierState$ = offsetModifierState == null ? void 0 : offsetModifierState[mainAxis]) != null ? _offsetModifierState$ : 0;\n    var tetherMin = offset + minOffset - offsetModifierValue - clientOffset;\n    var tetherMax = offset + maxOffset - offsetModifierValue;\n    var preventedOffset = within(tether ? mathMin(min, tetherMin) : min, offset, tether ? mathMax(max, tetherMax) : max);\n    popperOffsets[mainAxis] = preventedOffset;\n    data[mainAxis] = preventedOffset - offset;\n  }\n\n  if (checkAltAxis) {\n    var _offsetModifierState$2;\n\n    var _mainSide = mainAxis === 'x' ? top : left;\n\n    var _altSide = mainAxis === 'x' ? bottom : right;\n\n    var _offset = popperOffsets[altAxis];\n\n    var _len = altAxis === 'y' ? 'height' : 'width';\n\n    var _min = _offset + overflow[_mainSide];\n\n    var _max = _offset - overflow[_altSide];\n\n    var isOriginSide = [top, left].indexOf(basePlacement) !== -1;\n\n    var _offsetModifierValue = (_offsetModifierState$2 = offsetModifierState == null ? void 0 : offsetModifierState[altAxis]) != null ? _offsetModifierState$2 : 0;\n\n    var _tetherMin = isOriginSide ? _min : _offset - referenceRect[_len] - popperRect[_len] - _offsetModifierValue + normalizedTetherOffsetValue.altAxis;\n\n    var _tetherMax = isOriginSide ? _offset + referenceRect[_len] + popperRect[_len] - _offsetModifierValue - normalizedTetherOffsetValue.altAxis : _max;\n\n    var _preventedOffset = tether && isOriginSide ? withinMaxClamp(_tetherMin, _offset, _tetherMax) : within(tether ? _tetherMin : _min, _offset, tether ? _tetherMax : _max);\n\n    popperOffsets[altAxis] = _preventedOffset;\n    data[altAxis] = _preventedOffset - _offset;\n  }\n\n  state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n  name: 'preventOverflow',\n  enabled: true,\n  phase: 'main',\n  fn: preventOverflow,\n  requiresIfExists: ['offset']\n};","export default function getAltAxis(axis) {\n  return axis === 'x' ? 'y' : 'x';\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getNodeScroll from \"./getNodeScroll.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport { round } from \"../utils/math.js\";\n\nfunction isElementScaled(element) {\n  var rect = element.getBoundingClientRect();\n  var scaleX = round(rect.width) / element.offsetWidth || 1;\n  var scaleY = round(rect.height) / element.offsetHeight || 1;\n  return scaleX !== 1 || scaleY !== 1;\n} // Returns the composite rect of an element relative to its offsetParent.\n// Composite means it takes into account transforms as well as layout.\n\n\nexport default function getCompositeRect(elementOrVirtualElement, offsetParent, isFixed) {\n  if (isFixed === void 0) {\n    isFixed = false;\n  }\n\n  var isOffsetParentAnElement = isHTMLElement(offsetParent);\n  var offsetParentIsScaled = isHTMLElement(offsetParent) && isElementScaled(offsetParent);\n  var documentElement = getDocumentElement(offsetParent);\n  var rect = getBoundingClientRect(elementOrVirtualElement, offsetParentIsScaled, isFixed);\n  var scroll = {\n    scrollLeft: 0,\n    scrollTop: 0\n  };\n  var offsets = {\n    x: 0,\n    y: 0\n  };\n\n  if (isOffsetParentAnElement || !isOffsetParentAnElement && !isFixed) {\n    if (getNodeName(offsetParent) !== 'body' || // https://github.com/popperjs/popper-core/issues/1078\n    isScrollParent(documentElement)) {\n      scroll = getNodeScroll(offsetParent);\n    }\n\n    if (isHTMLElement(offsetParent)) {\n      offsets = getBoundingClientRect(offsetParent, true);\n      offsets.x += offsetParent.clientLeft;\n      offsets.y += offsetParent.clientTop;\n    } else if (documentElement) {\n      offsets.x = getWindowScrollBarX(documentElement);\n    }\n  }\n\n  return {\n    x: rect.left + scroll.scrollLeft - offsets.x,\n    y: rect.top + scroll.scrollTop - offsets.y,\n    width: rect.width,\n    height: rect.height\n  };\n}","import getWindowScroll from \"./getWindowScroll.js\";\nimport getWindow from \"./getWindow.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getHTMLElementScroll from \"./getHTMLElementScroll.js\";\nexport default function getNodeScroll(node) {\n  if (node === getWindow(node) || !isHTMLElement(node)) {\n    return getWindowScroll(node);\n  } else {\n    return getHTMLElementScroll(node);\n  }\n}","export default function getHTMLElementScroll(element) {\n  return {\n    scrollLeft: element.scrollLeft,\n    scrollTop: element.scrollTop\n  };\n}","import { modifierPhases } from \"../enums.js\"; // source: https://stackoverflow.com/questions/49875255\n\nfunction order(modifiers) {\n  var map = new Map();\n  var visited = new Set();\n  var result = [];\n  modifiers.forEach(function (modifier) {\n    map.set(modifier.name, modifier);\n  }); // On visiting object, check for its dependencies and visit them recursively\n\n  function sort(modifier) {\n    visited.add(modifier.name);\n    var requires = [].concat(modifier.requires || [], modifier.requiresIfExists || []);\n    requires.forEach(function (dep) {\n      if (!visited.has(dep)) {\n        var depModifier = map.get(dep);\n\n        if (depModifier) {\n          sort(depModifier);\n        }\n      }\n    });\n    result.push(modifier);\n  }\n\n  modifiers.forEach(function (modifier) {\n    if (!visited.has(modifier.name)) {\n      // check for visited object\n      sort(modifier);\n    }\n  });\n  return result;\n}\n\nexport default function orderModifiers(modifiers) {\n  // order based on dependencies\n  var orderedModifiers = order(modifiers); // order based on phase\n\n  return modifierPhases.reduce(function (acc, phase) {\n    return acc.concat(orderedModifiers.filter(function (modifier) {\n      return modifier.phase === phase;\n    }));\n  }, []);\n}","import getCompositeRect from \"./dom-utils/getCompositeRect.js\";\nimport getLayoutRect from \"./dom-utils/getLayoutRect.js\";\nimport listScrollParents from \"./dom-utils/listScrollParents.js\";\nimport getOffsetParent from \"./dom-utils/getOffsetParent.js\";\nimport orderModifiers from \"./utils/orderModifiers.js\";\nimport debounce from \"./utils/debounce.js\";\nimport mergeByName from \"./utils/mergeByName.js\";\nimport detectOverflow from \"./utils/detectOverflow.js\";\nimport { isElement } from \"./dom-utils/instanceOf.js\";\nvar DEFAULT_OPTIONS = {\n  placement: 'bottom',\n  modifiers: [],\n  strategy: 'absolute'\n};\n\nfunction areValidElements() {\n  for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {\n    args[_key] = arguments[_key];\n  }\n\n  return !args.some(function (element) {\n    return !(element && typeof element.getBoundingClientRect === 'function');\n  });\n}\n\nexport function popperGenerator(generatorOptions) {\n  if (generatorOptions === void 0) {\n    generatorOptions = {};\n  }\n\n  var _generatorOptions = generatorOptions,\n      _generatorOptions$def = _generatorOptions.defaultModifiers,\n      defaultModifiers = _generatorOptions$def === void 0 ? [] : _generatorOptions$def,\n      _generatorOptions$def2 = _generatorOptions.defaultOptions,\n      defaultOptions = _generatorOptions$def2 === void 0 ? DEFAULT_OPTIONS : _generatorOptions$def2;\n  return function createPopper(reference, popper, options) {\n    if (options === void 0) {\n      options = defaultOptions;\n    }\n\n    var state = {\n      placement: 'bottom',\n      orderedModifiers: [],\n      options: Object.assign({}, DEFAULT_OPTIONS, defaultOptions),\n      modifiersData: {},\n      elements: {\n        reference: reference,\n        popper: popper\n      },\n      attributes: {},\n      styles: {}\n    };\n    var effectCleanupFns = [];\n    var isDestroyed = false;\n    var instance = {\n      state: state,\n      setOptions: function setOptions(setOptionsAction) {\n        var options = typeof setOptionsAction === 'function' ? setOptionsAction(state.options) : setOptionsAction;\n        cleanupModifierEffects();\n        state.options = Object.assign({}, defaultOptions, state.options, options);\n        state.scrollParents = {\n          reference: isElement(reference) ? listScrollParents(reference) : reference.contextElement ? listScrollParents(reference.contextElement) : [],\n          popper: listScrollParents(popper)\n        }; // Orders the modifiers based on their dependencies and `phase`\n        // properties\n\n        var orderedModifiers = orderModifiers(mergeByName([].concat(defaultModifiers, state.options.modifiers))); // Strip out disabled modifiers\n\n        state.orderedModifiers = orderedModifiers.filter(function (m) {\n          return m.enabled;\n        });\n        runModifierEffects();\n        return instance.update();\n      },\n      // Sync update – it will always be executed, even if not necessary. This\n      // is useful for low frequency updates where sync behavior simplifies the\n      // logic.\n      // For high frequency updates (e.g. `resize` and `scroll` events), always\n      // prefer the async Popper#update method\n      forceUpdate: function forceUpdate() {\n        if (isDestroyed) {\n          return;\n        }\n\n        var _state$elements = state.elements,\n            reference = _state$elements.reference,\n            popper = _state$elements.popper; // Don't proceed if `reference` or `popper` are not valid elements\n        // anymore\n\n        if (!areValidElements(reference, popper)) {\n          return;\n        } // Store the reference and popper rects to be read by modifiers\n\n\n        state.rects = {\n          reference: getCompositeRect(reference, getOffsetParent(popper), state.options.strategy === 'fixed'),\n          popper: getLayoutRect(popper)\n        }; // Modifiers have the ability to reset the current update cycle. The\n        // most common use case for this is the `flip` modifier changing the\n        // placement, which then needs to re-run all the modifiers, because the\n        // logic was previously ran for the previous placement and is therefore\n        // stale/incorrect\n\n        state.reset = false;\n        state.placement = state.options.placement; // On each update cycle, the `modifiersData` property for each modifier\n        // is filled with the initial data specified by the modifier. This means\n        // it doesn't persist and is fresh on each update.\n        // To ensure persistent data, use `${name}#persistent`\n\n        state.orderedModifiers.forEach(function (modifier) {\n          return state.modifiersData[modifier.name] = Object.assign({}, modifier.data);\n        });\n\n        for (var index = 0; index < state.orderedModifiers.length; index++) {\n          if (state.reset === true) {\n            state.reset = false;\n            index = -1;\n            continue;\n          }\n\n          var _state$orderedModifie = state.orderedModifiers[index],\n              fn = _state$orderedModifie.fn,\n              _state$orderedModifie2 = _state$orderedModifie.options,\n              _options = _state$orderedModifie2 === void 0 ? {} : _state$orderedModifie2,\n              name = _state$orderedModifie.name;\n\n          if (typeof fn === 'function') {\n            state = fn({\n              state: state,\n              options: _options,\n              name: name,\n              instance: instance\n            }) || state;\n          }\n        }\n      },\n      // Async and optimistically optimized update – it will not be executed if\n      // not necessary (debounced to run at most once-per-tick)\n      update: debounce(function () {\n        return new Promise(function (resolve) {\n          instance.forceUpdate();\n          resolve(state);\n        });\n      }),\n      destroy: function destroy() {\n        cleanupModifierEffects();\n        isDestroyed = true;\n      }\n    };\n\n    if (!areValidElements(reference, popper)) {\n      return instance;\n    }\n\n    instance.setOptions(options).then(function (state) {\n      if (!isDestroyed && options.onFirstUpdate) {\n        options.onFirstUpdate(state);\n      }\n    }); // Modifiers have the ability to execute arbitrary code before the first\n    // update cycle runs. They will be executed in the same order as the update\n    // cycle. This is useful when a modifier adds some persistent data that\n    // other modifiers need to use, but the modifier is run after the dependent\n    // one.\n\n    function runModifierEffects() {\n      state.orderedModifiers.forEach(function (_ref) {\n        var name = _ref.name,\n            _ref$options = _ref.options,\n            options = _ref$options === void 0 ? {} : _ref$options,\n            effect = _ref.effect;\n\n        if (typeof effect === 'function') {\n          var cleanupFn = effect({\n            state: state,\n            name: name,\n            instance: instance,\n            options: options\n          });\n\n          var noopFn = function noopFn() {};\n\n          effectCleanupFns.push(cleanupFn || noopFn);\n        }\n      });\n    }\n\n    function cleanupModifierEffects() {\n      effectCleanupFns.forEach(function (fn) {\n        return fn();\n      });\n      effectCleanupFns = [];\n    }\n\n    return instance;\n  };\n}\nexport var createPopper = /*#__PURE__*/popperGenerator(); // eslint-disable-next-line import/no-unused-modules\n\nexport { detectOverflow };","export default function debounce(fn) {\n  var pending;\n  return function () {\n    if (!pending) {\n      pending = new Promise(function (resolve) {\n        Promise.resolve().then(function () {\n          pending = undefined;\n          resolve(fn());\n        });\n      });\n    }\n\n    return pending;\n  };\n}","export default function mergeByName(modifiers) {\n  var merged = modifiers.reduce(function (merged, current) {\n    var existing = merged[current.name];\n    merged[current.name] = existing ? Object.assign({}, existing, current, {\n      options: Object.assign({}, existing.options, current.options),\n      data: Object.assign({}, existing.data, current.data)\n    }) : current;\n    return merged;\n  }, {}); // IE11 does not support Object.values\n\n  return Object.keys(merged).map(function (key) {\n    return merged[key];\n  });\n}","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nimport offset from \"./modifiers/offset.js\";\nimport flip from \"./modifiers/flip.js\";\nimport preventOverflow from \"./modifiers/preventOverflow.js\";\nimport arrow from \"./modifiers/arrow.js\";\nimport hide from \"./modifiers/hide.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles, offset, flip, preventOverflow, arrow, hide];\nvar createPopper = /*#__PURE__*/popperGenerator({\n  defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow }; // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper as createPopperLite } from \"./popper-lite.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport * from \"./modifiers/index.js\";","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles];\nvar createPopper = /*#__PURE__*/popperGenerator({\n  defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow };","/*!\n  * Bootstrap v5.3.2 (https://getbootstrap.com/)\n  * Copyright 2011-2023 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)\n  * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n  */\nimport * as Popper from '@popperjs/core';\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/data.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n/**\n * Constants\n */\n\nconst elementMap = new Map();\nconst Data = {\n  set(element, key, instance) {\n    if (!elementMap.has(element)) {\n      elementMap.set(element, new Map());\n    }\n    const instanceMap = elementMap.get(element);\n\n    // make it clear we only want one instance per element\n    // can be removed later when multiple key/instances are fine to be used\n    if (!instanceMap.has(key) && instanceMap.size !== 0) {\n      // eslint-disable-next-line no-console\n      console.error(`Bootstrap doesn't allow more than one instance per element. Bound instance: ${Array.from(instanceMap.keys())[0]}.`);\n      return;\n    }\n    instanceMap.set(key, instance);\n  },\n  get(element, key) {\n    if (elementMap.has(element)) {\n      return elementMap.get(element).get(key) || null;\n    }\n    return null;\n  },\n  remove(element, key) {\n    if (!elementMap.has(element)) {\n      return;\n    }\n    const instanceMap = elementMap.get(element);\n    instanceMap.delete(key);\n\n    // free up element references if there are no instances left for an element\n    if (instanceMap.size === 0) {\n      elementMap.delete(element);\n    }\n  }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/index.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst MAX_UID = 1000000;\nconst MILLISECONDS_MULTIPLIER = 1000;\nconst TRANSITION_END = 'transitionend';\n\n/**\n * Properly escape IDs selectors to handle weird IDs\n * @param {string} selector\n * @returns {string}\n */\nconst parseSelector = selector => {\n  if (selector && window.CSS && window.CSS.escape) {\n    // document.querySelector needs escaping to handle IDs (html5+) containing for instance /\n    selector = selector.replace(/#([^\\s\"#']+)/g, (match, id) => `#${CSS.escape(id)}`);\n  }\n  return selector;\n};\n\n// Shout-out Angus Croll (https://goo.gl/pxwQGp)\nconst toType = object => {\n  if (object === null || object === undefined) {\n    return `${object}`;\n  }\n  return Object.prototype.toString.call(object).match(/\\s([a-z]+)/i)[1].toLowerCase();\n};\n\n/**\n * Public Util API\n */\n\nconst getUID = prefix => {\n  do {\n    prefix += Math.floor(Math.random() * MAX_UID);\n  } while (document.getElementById(prefix));\n  return prefix;\n};\nconst getTransitionDurationFromElement = element => {\n  if (!element) {\n    return 0;\n  }\n\n  // Get transition-duration of the element\n  let {\n    transitionDuration,\n    transitionDelay\n  } = window.getComputedStyle(element);\n  const floatTransitionDuration = Number.parseFloat(transitionDuration);\n  const floatTransitionDelay = Number.parseFloat(transitionDelay);\n\n  // Return 0 if element or transition duration is not found\n  if (!floatTransitionDuration && !floatTransitionDelay) {\n    return 0;\n  }\n\n  // If multiple durations are defined, take the first\n  transitionDuration = transitionDuration.split(',')[0];\n  transitionDelay = transitionDelay.split(',')[0];\n  return (Number.parseFloat(transitionDuration) + Number.parseFloat(transitionDelay)) * MILLISECONDS_MULTIPLIER;\n};\nconst triggerTransitionEnd = element => {\n  element.dispatchEvent(new Event(TRANSITION_END));\n};\nconst isElement = object => {\n  if (!object || typeof object !== 'object') {\n    return false;\n  }\n  if (typeof object.jquery !== 'undefined') {\n    object = object[0];\n  }\n  return typeof object.nodeType !== 'undefined';\n};\nconst getElement = object => {\n  // it's a jQuery object or a node element\n  if (isElement(object)) {\n    return object.jquery ? object[0] : object;\n  }\n  if (typeof object === 'string' && object.length > 0) {\n    return document.querySelector(parseSelector(object));\n  }\n  return null;\n};\nconst isVisible = element => {\n  if (!isElement(element) || element.getClientRects().length === 0) {\n    return false;\n  }\n  const elementIsVisible = getComputedStyle(element).getPropertyValue('visibility') === 'visible';\n  // Handle `details` element as its content may falsie appear visible when it is closed\n  const closedDetails = element.closest('details:not([open])');\n  if (!closedDetails) {\n    return elementIsVisible;\n  }\n  if (closedDetails !== element) {\n    const summary = element.closest('summary');\n    if (summary && summary.parentNode !== closedDetails) {\n      return false;\n    }\n    if (summary === null) {\n      return false;\n    }\n  }\n  return elementIsVisible;\n};\nconst isDisabled = element => {\n  if (!element || element.nodeType !== Node.ELEMENT_NODE) {\n    return true;\n  }\n  if (element.classList.contains('disabled')) {\n    return true;\n  }\n  if (typeof element.disabled !== 'undefined') {\n    return element.disabled;\n  }\n  return element.hasAttribute('disabled') && element.getAttribute('disabled') !== 'false';\n};\nconst findShadowRoot = element => {\n  if (!document.documentElement.attachShadow) {\n    return null;\n  }\n\n  // Can find the shadow root otherwise it'll return the document\n  if (typeof element.getRootNode === 'function') {\n    const root = element.getRootNode();\n    return root instanceof ShadowRoot ? root : null;\n  }\n  if (element instanceof ShadowRoot) {\n    return element;\n  }\n\n  // when we don't find a shadow root\n  if (!element.parentNode) {\n    return null;\n  }\n  return findShadowRoot(element.parentNode);\n};\nconst noop = () => {};\n\n/**\n * Trick to restart an element's animation\n *\n * @param {HTMLElement} element\n * @return void\n *\n * @see https://www.charistheo.io/blog/2021/02/restart-a-css-animation-with-javascript/#restarting-a-css-animation\n */\nconst reflow = element => {\n  element.offsetHeight; // eslint-disable-line no-unused-expressions\n};\n\nconst getjQuery = () => {\n  if (window.jQuery && !document.body.hasAttribute('data-bs-no-jquery')) {\n    return window.jQuery;\n  }\n  return null;\n};\nconst DOMContentLoadedCallbacks = [];\nconst onDOMContentLoaded = callback => {\n  if (document.readyState === 'loading') {\n    // add listener on the first call when the document is in loading state\n    if (!DOMContentLoadedCallbacks.length) {\n      document.addEventListener('DOMContentLoaded', () => {\n        for (const callback of DOMContentLoadedCallbacks) {\n          callback();\n        }\n      });\n    }\n    DOMContentLoadedCallbacks.push(callback);\n  } else {\n    callback();\n  }\n};\nconst isRTL = () => document.documentElement.dir === 'rtl';\nconst defineJQueryPlugin = plugin => {\n  onDOMContentLoaded(() => {\n    const $ = getjQuery();\n    /* istanbul ignore if */\n    if ($) {\n      const name = plugin.NAME;\n      const JQUERY_NO_CONFLICT = $.fn[name];\n      $.fn[name] = plugin.jQueryInterface;\n      $.fn[name].Constructor = plugin;\n      $.fn[name].noConflict = () => {\n        $.fn[name] = JQUERY_NO_CONFLICT;\n        return plugin.jQueryInterface;\n      };\n    }\n  });\n};\nconst execute = (possibleCallback, args = [], defaultValue = possibleCallback) => {\n  return typeof possibleCallback === 'function' ? possibleCallback(...args) : defaultValue;\n};\nconst executeAfterTransition = (callback, transitionElement, waitForTransition = true) => {\n  if (!waitForTransition) {\n    execute(callback);\n    return;\n  }\n  const durationPadding = 5;\n  const emulatedDuration = getTransitionDurationFromElement(transitionElement) + durationPadding;\n  let called = false;\n  const handler = ({\n    target\n  }) => {\n    if (target !== transitionElement) {\n      return;\n    }\n    called = true;\n    transitionElement.removeEventListener(TRANSITION_END, handler);\n    execute(callback);\n  };\n  transitionElement.addEventListener(TRANSITION_END, handler);\n  setTimeout(() => {\n    if (!called) {\n      triggerTransitionEnd(transitionElement);\n    }\n  }, emulatedDuration);\n};\n\n/**\n * Return the previous/next element of a list.\n *\n * @param {array} list    The list of elements\n * @param activeElement   The active element\n * @param shouldGetNext   Choose to get next or previous element\n * @param isCycleAllowed\n * @return {Element|elem} The proper element\n */\nconst getNextActiveElement = (list, activeElement, shouldGetNext, isCycleAllowed) => {\n  const listLength = list.length;\n  let index = list.indexOf(activeElement);\n\n  // if the element does not exist in the list return an element\n  // depending on the direction and if cycle is allowed\n  if (index === -1) {\n    return !shouldGetNext && isCycleAllowed ? list[listLength - 1] : list[0];\n  }\n  index += shouldGetNext ? 1 : -1;\n  if (isCycleAllowed) {\n    index = (index + listLength) % listLength;\n  }\n  return list[Math.max(0, Math.min(index, listLength - 1))];\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/event-handler.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst namespaceRegex = /[^.]*(?=\\..*)\\.|.*/;\nconst stripNameRegex = /\\..*/;\nconst stripUidRegex = /::\\d+$/;\nconst eventRegistry = {}; // Events storage\nlet uidEvent = 1;\nconst customEvents = {\n  mouseenter: 'mouseover',\n  mouseleave: 'mouseout'\n};\nconst nativeEvents = new Set(['click', 'dblclick', 'mouseup', 'mousedown', 'contextmenu', 'mousewheel', 'DOMMouseScroll', 'mouseover', 'mouseout', 'mousemove', 'selectstart', 'selectend', 'keydown', 'keypress', 'keyup', 'orientationchange', 'touchstart', 'touchmove', 'touchend', 'touchcancel', 'pointerdown', 'pointermove', 'pointerup', 'pointerleave', 'pointercancel', 'gesturestart', 'gesturechange', 'gestureend', 'focus', 'blur', 'change', 'reset', 'select', 'submit', 'focusin', 'focusout', 'load', 'unload', 'beforeunload', 'resize', 'move', 'DOMContentLoaded', 'readystatechange', 'error', 'abort', 'scroll']);\n\n/**\n * Private methods\n */\n\nfunction makeEventUid(element, uid) {\n  return uid && `${uid}::${uidEvent++}` || element.uidEvent || uidEvent++;\n}\nfunction getElementEvents(element) {\n  const uid = makeEventUid(element);\n  element.uidEvent = uid;\n  eventRegistry[uid] = eventRegistry[uid] || {};\n  return eventRegistry[uid];\n}\nfunction bootstrapHandler(element, fn) {\n  return function handler(event) {\n    hydrateObj(event, {\n      delegateTarget: element\n    });\n    if (handler.oneOff) {\n      EventHandler.off(element, event.type, fn);\n    }\n    return fn.apply(element, [event]);\n  };\n}\nfunction bootstrapDelegationHandler(element, selector, fn) {\n  return function handler(event) {\n    const domElements = element.querySelectorAll(selector);\n    for (let {\n      target\n    } = event; target && target !== this; target = target.parentNode) {\n      for (const domElement of domElements) {\n        if (domElement !== target) {\n          continue;\n        }\n        hydrateObj(event, {\n          delegateTarget: target\n        });\n        if (handler.oneOff) {\n          EventHandler.off(element, event.type, selector, fn);\n        }\n        return fn.apply(target, [event]);\n      }\n    }\n  };\n}\nfunction findHandler(events, callable, delegationSelector = null) {\n  return Object.values(events).find(event => event.callable === callable && event.delegationSelector === delegationSelector);\n}\nfunction normalizeParameters(originalTypeEvent, handler, delegationFunction) {\n  const isDelegated = typeof handler === 'string';\n  // TODO: tooltip passes `false` instead of selector, so we need to check\n  const callable = isDelegated ? delegationFunction : handler || delegationFunction;\n  let typeEvent = getTypeEvent(originalTypeEvent);\n  if (!nativeEvents.has(typeEvent)) {\n    typeEvent = originalTypeEvent;\n  }\n  return [isDelegated, callable, typeEvent];\n}\nfunction addHandler(element, originalTypeEvent, handler, delegationFunction, oneOff) {\n  if (typeof originalTypeEvent !== 'string' || !element) {\n    return;\n  }\n  let [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n\n  // in case of mouseenter or mouseleave wrap the handler within a function that checks for its DOM position\n  // this prevents the handler from being dispatched the same way as mouseover or mouseout does\n  if (originalTypeEvent in customEvents) {\n    const wrapFunction = fn => {\n      return function (event) {\n        if (!event.relatedTarget || event.relatedTarget !== event.delegateTarget && !event.delegateTarget.contains(event.relatedTarget)) {\n          return fn.call(this, event);\n        }\n      };\n    };\n    callable = wrapFunction(callable);\n  }\n  const events = getElementEvents(element);\n  const handlers = events[typeEvent] || (events[typeEvent] = {});\n  const previousFunction = findHandler(handlers, callable, isDelegated ? handler : null);\n  if (previousFunction) {\n    previousFunction.oneOff = previousFunction.oneOff && oneOff;\n    return;\n  }\n  const uid = makeEventUid(callable, originalTypeEvent.replace(namespaceRegex, ''));\n  const fn = isDelegated ? bootstrapDelegationHandler(element, handler, callable) : bootstrapHandler(element, callable);\n  fn.delegationSelector = isDelegated ? handler : null;\n  fn.callable = callable;\n  fn.oneOff = oneOff;\n  fn.uidEvent = uid;\n  handlers[uid] = fn;\n  element.addEventListener(typeEvent, fn, isDelegated);\n}\nfunction removeHandler(element, events, typeEvent, handler, delegationSelector) {\n  const fn = findHandler(events[typeEvent], handler, delegationSelector);\n  if (!fn) {\n    return;\n  }\n  element.removeEventListener(typeEvent, fn, Boolean(delegationSelector));\n  delete events[typeEvent][fn.uidEvent];\n}\nfunction removeNamespacedHandlers(element, events, typeEvent, namespace) {\n  const storeElementEvent = events[typeEvent] || {};\n  for (const [handlerKey, event] of Object.entries(storeElementEvent)) {\n    if (handlerKey.includes(namespace)) {\n      removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n    }\n  }\n}\nfunction getTypeEvent(event) {\n  // allow to get the native events from namespaced events ('click.bs.button' --> 'click')\n  event = event.replace(stripNameRegex, '');\n  return customEvents[event] || event;\n}\nconst EventHandler = {\n  on(element, event, handler, delegationFunction) {\n    addHandler(element, event, handler, delegationFunction, false);\n  },\n  one(element, event, handler, delegationFunction) {\n    addHandler(element, event, handler, delegationFunction, true);\n  },\n  off(element, originalTypeEvent, handler, delegationFunction) {\n    if (typeof originalTypeEvent !== 'string' || !element) {\n      return;\n    }\n    const [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n    const inNamespace = typeEvent !== originalTypeEvent;\n    const events = getElementEvents(element);\n    const storeElementEvent = events[typeEvent] || {};\n    const isNamespace = originalTypeEvent.startsWith('.');\n    if (typeof callable !== 'undefined') {\n      // Simplest case: handler is passed, remove that listener ONLY.\n      if (!Object.keys(storeElementEvent).length) {\n        return;\n      }\n      removeHandler(element, events, typeEvent, callable, isDelegated ? handler : null);\n      return;\n    }\n    if (isNamespace) {\n      for (const elementEvent of Object.keys(events)) {\n        removeNamespacedHandlers(element, events, elementEvent, originalTypeEvent.slice(1));\n      }\n    }\n    for (const [keyHandlers, event] of Object.entries(storeElementEvent)) {\n      const handlerKey = keyHandlers.replace(stripUidRegex, '');\n      if (!inNamespace || originalTypeEvent.includes(handlerKey)) {\n        removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n      }\n    }\n  },\n  trigger(element, event, args) {\n    if (typeof event !== 'string' || !element) {\n      return null;\n    }\n    const $ = getjQuery();\n    const typeEvent = getTypeEvent(event);\n    const inNamespace = event !== typeEvent;\n    let jQueryEvent = null;\n    let bubbles = true;\n    let nativeDispatch = true;\n    let defaultPrevented = false;\n    if (inNamespace && $) {\n      jQueryEvent = $.Event(event, args);\n      $(element).trigger(jQueryEvent);\n      bubbles = !jQueryEvent.isPropagationStopped();\n      nativeDispatch = !jQueryEvent.isImmediatePropagationStopped();\n      defaultPrevented = jQueryEvent.isDefaultPrevented();\n    }\n    const evt = hydrateObj(new Event(event, {\n      bubbles,\n      cancelable: true\n    }), args);\n    if (defaultPrevented) {\n      evt.preventDefault();\n    }\n    if (nativeDispatch) {\n      element.dispatchEvent(evt);\n    }\n    if (evt.defaultPrevented && jQueryEvent) {\n      jQueryEvent.preventDefault();\n    }\n    return evt;\n  }\n};\nfunction hydrateObj(obj, meta = {}) {\n  for (const [key, value] of Object.entries(meta)) {\n    try {\n      obj[key] = value;\n    } catch (_unused) {\n      Object.defineProperty(obj, key, {\n        configurable: true,\n        get() {\n          return value;\n        }\n      });\n    }\n  }\n  return obj;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/manipulator.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nfunction normalizeData(value) {\n  if (value === 'true') {\n    return true;\n  }\n  if (value === 'false') {\n    return false;\n  }\n  if (value === Number(value).toString()) {\n    return Number(value);\n  }\n  if (value === '' || value === 'null') {\n    return null;\n  }\n  if (typeof value !== 'string') {\n    return value;\n  }\n  try {\n    return JSON.parse(decodeURIComponent(value));\n  } catch (_unused) {\n    return value;\n  }\n}\nfunction normalizeDataKey(key) {\n  return key.replace(/[A-Z]/g, chr => `-${chr.toLowerCase()}`);\n}\nconst Manipulator = {\n  setDataAttribute(element, key, value) {\n    element.setAttribute(`data-bs-${normalizeDataKey(key)}`, value);\n  },\n  removeDataAttribute(element, key) {\n    element.removeAttribute(`data-bs-${normalizeDataKey(key)}`);\n  },\n  getDataAttributes(element) {\n    if (!element) {\n      return {};\n    }\n    const attributes = {};\n    const bsKeys = Object.keys(element.dataset).filter(key => key.startsWith('bs') && !key.startsWith('bsConfig'));\n    for (const key of bsKeys) {\n      let pureKey = key.replace(/^bs/, '');\n      pureKey = pureKey.charAt(0).toLowerCase() + pureKey.slice(1, pureKey.length);\n      attributes[pureKey] = normalizeData(element.dataset[key]);\n    }\n    return attributes;\n  },\n  getDataAttribute(element, key) {\n    return normalizeData(element.getAttribute(`data-bs-${normalizeDataKey(key)}`));\n  }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/config.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Class definition\n */\n\nclass Config {\n  // Getters\n  static get Default() {\n    return {};\n  }\n  static get DefaultType() {\n    return {};\n  }\n  static get NAME() {\n    throw new Error('You have to implement the static method \"NAME\", for each component!');\n  }\n  _getConfig(config) {\n    config = this._mergeConfigObj(config);\n    config = this._configAfterMerge(config);\n    this._typeCheckConfig(config);\n    return config;\n  }\n  _configAfterMerge(config) {\n    return config;\n  }\n  _mergeConfigObj(config, element) {\n    const jsonConfig = isElement(element) ? Manipulator.getDataAttribute(element, 'config') : {}; // try to parse\n\n    return {\n      ...this.constructor.Default,\n      ...(typeof jsonConfig === 'object' ? jsonConfig : {}),\n      ...(isElement(element) ? Manipulator.getDataAttributes(element) : {}),\n      ...(typeof config === 'object' ? config : {})\n    };\n  }\n  _typeCheckConfig(config, configTypes = this.constructor.DefaultType) {\n    for (const [property, expectedTypes] of Object.entries(configTypes)) {\n      const value = config[property];\n      const valueType = isElement(value) ? 'element' : toType(value);\n      if (!new RegExp(expectedTypes).test(valueType)) {\n        throw new TypeError(`${this.constructor.NAME.toUpperCase()}: Option \"${property}\" provided type \"${valueType}\" but expected type \"${expectedTypes}\".`);\n      }\n    }\n  }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap base-component.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst VERSION = '5.3.2';\n\n/**\n * Class definition\n */\n\nclass BaseComponent extends Config {\n  constructor(element, config) {\n    super();\n    element = getElement(element);\n    if (!element) {\n      return;\n    }\n    this._element = element;\n    this._config = this._getConfig(config);\n    Data.set(this._element, this.constructor.DATA_KEY, this);\n  }\n\n  // Public\n  dispose() {\n    Data.remove(this._element, this.constructor.DATA_KEY);\n    EventHandler.off(this._element, this.constructor.EVENT_KEY);\n    for (const propertyName of Object.getOwnPropertyNames(this)) {\n      this[propertyName] = null;\n    }\n  }\n  _queueCallback(callback, element, isAnimated = true) {\n    executeAfterTransition(callback, element, isAnimated);\n  }\n  _getConfig(config) {\n    config = this._mergeConfigObj(config, this._element);\n    config = this._configAfterMerge(config);\n    this._typeCheckConfig(config);\n    return config;\n  }\n\n  // Static\n  static getInstance(element) {\n    return Data.get(getElement(element), this.DATA_KEY);\n  }\n  static getOrCreateInstance(element, config = {}) {\n    return this.getInstance(element) || new this(element, typeof config === 'object' ? config : null);\n  }\n  static get VERSION() {\n    return VERSION;\n  }\n  static get DATA_KEY() {\n    return `bs.${this.NAME}`;\n  }\n  static get EVENT_KEY() {\n    return `.${this.DATA_KEY}`;\n  }\n  static eventName(name) {\n    return `${name}${this.EVENT_KEY}`;\n  }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/selector-engine.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst getSelector = element => {\n  let selector = element.getAttribute('data-bs-target');\n  if (!selector || selector === '#') {\n    let hrefAttribute = element.getAttribute('href');\n\n    // The only valid content that could double as a selector are IDs or classes,\n    // so everything starting with `#` or `.`. If a \"real\" URL is used as the selector,\n    // `document.querySelector` will rightfully complain it is invalid.\n    // See https://github.com/twbs/bootstrap/issues/32273\n    if (!hrefAttribute || !hrefAttribute.includes('#') && !hrefAttribute.startsWith('.')) {\n      return null;\n    }\n\n    // Just in case some CMS puts out a full URL with the anchor appended\n    if (hrefAttribute.includes('#') && !hrefAttribute.startsWith('#')) {\n      hrefAttribute = `#${hrefAttribute.split('#')[1]}`;\n    }\n    selector = hrefAttribute && hrefAttribute !== '#' ? parseSelector(hrefAttribute.trim()) : null;\n  }\n  return selector;\n};\nconst SelectorEngine = {\n  find(selector, element = document.documentElement) {\n    return [].concat(...Element.prototype.querySelectorAll.call(element, selector));\n  },\n  findOne(selector, element = document.documentElement) {\n    return Element.prototype.querySelector.call(element, selector);\n  },\n  children(element, selector) {\n    return [].concat(...element.children).filter(child => child.matches(selector));\n  },\n  parents(element, selector) {\n    const parents = [];\n    let ancestor = element.parentNode.closest(selector);\n    while (ancestor) {\n      parents.push(ancestor);\n      ancestor = ancestor.parentNode.closest(selector);\n    }\n    return parents;\n  },\n  prev(element, selector) {\n    let previous = element.previousElementSibling;\n    while (previous) {\n      if (previous.matches(selector)) {\n        return [previous];\n      }\n      previous = previous.previousElementSibling;\n    }\n    return [];\n  },\n  // TODO: this is now unused; remove later along with prev()\n  next(element, selector) {\n    let next = element.nextElementSibling;\n    while (next) {\n      if (next.matches(selector)) {\n        return [next];\n      }\n      next = next.nextElementSibling;\n    }\n    return [];\n  },\n  focusableChildren(element) {\n    const focusables = ['a', 'button', 'input', 'textarea', 'select', 'details', '[tabindex]', '[contenteditable=\"true\"]'].map(selector => `${selector}:not([tabindex^=\"-\"])`).join(',');\n    return this.find(focusables, element).filter(el => !isDisabled(el) && isVisible(el));\n  },\n  getSelectorFromElement(element) {\n    const selector = getSelector(element);\n    if (selector) {\n      return SelectorEngine.findOne(selector) ? selector : null;\n    }\n    return null;\n  },\n  getElementFromSelector(element) {\n    const selector = getSelector(element);\n    return selector ? SelectorEngine.findOne(selector) : null;\n  },\n  getMultipleElementsFromSelector(element) {\n    const selector = getSelector(element);\n    return selector ? SelectorEngine.find(selector) : [];\n  }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/component-functions.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst enableDismissTrigger = (component, method = 'hide') => {\n  const clickEvent = `click.dismiss${component.EVENT_KEY}`;\n  const name = component.NAME;\n  EventHandler.on(document, clickEvent, `[data-bs-dismiss=\"${name}\"]`, function (event) {\n    if (['A', 'AREA'].includes(this.tagName)) {\n      event.preventDefault();\n    }\n    if (isDisabled(this)) {\n      return;\n    }\n    const target = SelectorEngine.getElementFromSelector(this) || this.closest(`.${name}`);\n    const instance = component.getOrCreateInstance(target);\n\n    // Method argument is left, for Alert and only, as it doesn't implement the 'hide' method\n    instance[method]();\n  });\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap alert.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$f = 'alert';\nconst DATA_KEY$a = 'bs.alert';\nconst EVENT_KEY$b = `.${DATA_KEY$a}`;\nconst EVENT_CLOSE = `close${EVENT_KEY$b}`;\nconst EVENT_CLOSED = `closed${EVENT_KEY$b}`;\nconst CLASS_NAME_FADE$5 = 'fade';\nconst CLASS_NAME_SHOW$8 = 'show';\n\n/**\n * Class definition\n */\n\nclass Alert extends BaseComponent {\n  // Getters\n  static get NAME() {\n    return NAME$f;\n  }\n\n  // Public\n  close() {\n    const closeEvent = EventHandler.trigger(this._element, EVENT_CLOSE);\n    if (closeEvent.defaultPrevented) {\n      return;\n    }\n    this._element.classList.remove(CLASS_NAME_SHOW$8);\n    const isAnimated = this._element.classList.contains(CLASS_NAME_FADE$5);\n    this._queueCallback(() => this._destroyElement(), this._element, isAnimated);\n  }\n\n  // Private\n  _destroyElement() {\n    this._element.remove();\n    EventHandler.trigger(this._element, EVENT_CLOSED);\n    this.dispose();\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = Alert.getOrCreateInstance(this);\n      if (typeof config !== 'string') {\n        return;\n      }\n      if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n        throw new TypeError(`No method named \"${config}\"`);\n      }\n      data[config](this);\n    });\n  }\n}\n\n/**\n * Data API implementation\n */\n\nenableDismissTrigger(Alert, 'close');\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Alert);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap button.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$e = 'button';\nconst DATA_KEY$9 = 'bs.button';\nconst EVENT_KEY$a = `.${DATA_KEY$9}`;\nconst DATA_API_KEY$6 = '.data-api';\nconst CLASS_NAME_ACTIVE$3 = 'active';\nconst SELECTOR_DATA_TOGGLE$5 = '[data-bs-toggle=\"button\"]';\nconst EVENT_CLICK_DATA_API$6 = `click${EVENT_KEY$a}${DATA_API_KEY$6}`;\n\n/**\n * Class definition\n */\n\nclass Button extends BaseComponent {\n  // Getters\n  static get NAME() {\n    return NAME$e;\n  }\n\n  // Public\n  toggle() {\n    // Toggle class and sync the `aria-pressed` attribute with the return value of the `.toggle()` method\n    this._element.setAttribute('aria-pressed', this._element.classList.toggle(CLASS_NAME_ACTIVE$3));\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = Button.getOrCreateInstance(this);\n      if (config === 'toggle') {\n        data[config]();\n      }\n    });\n  }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$6, SELECTOR_DATA_TOGGLE$5, event => {\n  event.preventDefault();\n  const button = event.target.closest(SELECTOR_DATA_TOGGLE$5);\n  const data = Button.getOrCreateInstance(button);\n  data.toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Button);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/swipe.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$d = 'swipe';\nconst EVENT_KEY$9 = '.bs.swipe';\nconst EVENT_TOUCHSTART = `touchstart${EVENT_KEY$9}`;\nconst EVENT_TOUCHMOVE = `touchmove${EVENT_KEY$9}`;\nconst EVENT_TOUCHEND = `touchend${EVENT_KEY$9}`;\nconst EVENT_POINTERDOWN = `pointerdown${EVENT_KEY$9}`;\nconst EVENT_POINTERUP = `pointerup${EVENT_KEY$9}`;\nconst POINTER_TYPE_TOUCH = 'touch';\nconst POINTER_TYPE_PEN = 'pen';\nconst CLASS_NAME_POINTER_EVENT = 'pointer-event';\nconst SWIPE_THRESHOLD = 40;\nconst Default$c = {\n  endCallback: null,\n  leftCallback: null,\n  rightCallback: null\n};\nconst DefaultType$c = {\n  endCallback: '(function|null)',\n  leftCallback: '(function|null)',\n  rightCallback: '(function|null)'\n};\n\n/**\n * Class definition\n */\n\nclass Swipe extends Config {\n  constructor(element, config) {\n    super();\n    this._element = element;\n    if (!element || !Swipe.isSupported()) {\n      return;\n    }\n    this._config = this._getConfig(config);\n    this._deltaX = 0;\n    this._supportPointerEvents = Boolean(window.PointerEvent);\n    this._initEvents();\n  }\n\n  // Getters\n  static get Default() {\n    return Default$c;\n  }\n  static get DefaultType() {\n    return DefaultType$c;\n  }\n  static get NAME() {\n    return NAME$d;\n  }\n\n  // Public\n  dispose() {\n    EventHandler.off(this._element, EVENT_KEY$9);\n  }\n\n  // Private\n  _start(event) {\n    if (!this._supportPointerEvents) {\n      this._deltaX = event.touches[0].clientX;\n      return;\n    }\n    if (this._eventIsPointerPenTouch(event)) {\n      this._deltaX = event.clientX;\n    }\n  }\n  _end(event) {\n    if (this._eventIsPointerPenTouch(event)) {\n      this._deltaX = event.clientX - this._deltaX;\n    }\n    this._handleSwipe();\n    execute(this._config.endCallback);\n  }\n  _move(event) {\n    this._deltaX = event.touches && event.touches.length > 1 ? 0 : event.touches[0].clientX - this._deltaX;\n  }\n  _handleSwipe() {\n    const absDeltaX = Math.abs(this._deltaX);\n    if (absDeltaX <= SWIPE_THRESHOLD) {\n      return;\n    }\n    const direction = absDeltaX / this._deltaX;\n    this._deltaX = 0;\n    if (!direction) {\n      return;\n    }\n    execute(direction > 0 ? this._config.rightCallback : this._config.leftCallback);\n  }\n  _initEvents() {\n    if (this._supportPointerEvents) {\n      EventHandler.on(this._element, EVENT_POINTERDOWN, event => this._start(event));\n      EventHandler.on(this._element, EVENT_POINTERUP, event => this._end(event));\n      this._element.classList.add(CLASS_NAME_POINTER_EVENT);\n    } else {\n      EventHandler.on(this._element, EVENT_TOUCHSTART, event => this._start(event));\n      EventHandler.on(this._element, EVENT_TOUCHMOVE, event => this._move(event));\n      EventHandler.on(this._element, EVENT_TOUCHEND, event => this._end(event));\n    }\n  }\n  _eventIsPointerPenTouch(event) {\n    return this._supportPointerEvents && (event.pointerType === POINTER_TYPE_PEN || event.pointerType === POINTER_TYPE_TOUCH);\n  }\n\n  // Static\n  static isSupported() {\n    return 'ontouchstart' in document.documentElement || navigator.maxTouchPoints > 0;\n  }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap carousel.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$c = 'carousel';\nconst DATA_KEY$8 = 'bs.carousel';\nconst EVENT_KEY$8 = `.${DATA_KEY$8}`;\nconst DATA_API_KEY$5 = '.data-api';\nconst ARROW_LEFT_KEY$1 = 'ArrowLeft';\nconst ARROW_RIGHT_KEY$1 = 'ArrowRight';\nconst TOUCHEVENT_COMPAT_WAIT = 500; // Time for mouse compat events to fire after touch\n\nconst ORDER_NEXT = 'next';\nconst ORDER_PREV = 'prev';\nconst DIRECTION_LEFT = 'left';\nconst DIRECTION_RIGHT = 'right';\nconst EVENT_SLIDE = `slide${EVENT_KEY$8}`;\nconst EVENT_SLID = `slid${EVENT_KEY$8}`;\nconst EVENT_KEYDOWN$1 = `keydown${EVENT_KEY$8}`;\nconst EVENT_MOUSEENTER$1 = `mouseenter${EVENT_KEY$8}`;\nconst EVENT_MOUSELEAVE$1 = `mouseleave${EVENT_KEY$8}`;\nconst EVENT_DRAG_START = `dragstart${EVENT_KEY$8}`;\nconst EVENT_LOAD_DATA_API$3 = `load${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst EVENT_CLICK_DATA_API$5 = `click${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst CLASS_NAME_CAROUSEL = 'carousel';\nconst CLASS_NAME_ACTIVE$2 = 'active';\nconst CLASS_NAME_SLIDE = 'slide';\nconst CLASS_NAME_END = 'carousel-item-end';\nconst CLASS_NAME_START = 'carousel-item-start';\nconst CLASS_NAME_NEXT = 'carousel-item-next';\nconst CLASS_NAME_PREV = 'carousel-item-prev';\nconst SELECTOR_ACTIVE = '.active';\nconst SELECTOR_ITEM = '.carousel-item';\nconst SELECTOR_ACTIVE_ITEM = SELECTOR_ACTIVE + SELECTOR_ITEM;\nconst SELECTOR_ITEM_IMG = '.carousel-item img';\nconst SELECTOR_INDICATORS = '.carousel-indicators';\nconst SELECTOR_DATA_SLIDE = '[data-bs-slide], [data-bs-slide-to]';\nconst SELECTOR_DATA_RIDE = '[data-bs-ride=\"carousel\"]';\nconst KEY_TO_DIRECTION = {\n  [ARROW_LEFT_KEY$1]: DIRECTION_RIGHT,\n  [ARROW_RIGHT_KEY$1]: DIRECTION_LEFT\n};\nconst Default$b = {\n  interval: 5000,\n  keyboard: true,\n  pause: 'hover',\n  ride: false,\n  touch: true,\n  wrap: true\n};\nconst DefaultType$b = {\n  interval: '(number|boolean)',\n  // TODO:v6 remove boolean support\n  keyboard: 'boolean',\n  pause: '(string|boolean)',\n  ride: '(boolean|string)',\n  touch: 'boolean',\n  wrap: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Carousel extends BaseComponent {\n  constructor(element, config) {\n    super(element, config);\n    this._interval = null;\n    this._activeElement = null;\n    this._isSliding = false;\n    this.touchTimeout = null;\n    this._swipeHelper = null;\n    this._indicatorsElement = SelectorEngine.findOne(SELECTOR_INDICATORS, this._element);\n    this._addEventListeners();\n    if (this._config.ride === CLASS_NAME_CAROUSEL) {\n      this.cycle();\n    }\n  }\n\n  // Getters\n  static get Default() {\n    return Default$b;\n  }\n  static get DefaultType() {\n    return DefaultType$b;\n  }\n  static get NAME() {\n    return NAME$c;\n  }\n\n  // Public\n  next() {\n    this._slide(ORDER_NEXT);\n  }\n  nextWhenVisible() {\n    // FIXME TODO use `document.visibilityState`\n    // Don't call next when the page isn't visible\n    // or the carousel or its parent isn't visible\n    if (!document.hidden && isVisible(this._element)) {\n      this.next();\n    }\n  }\n  prev() {\n    this._slide(ORDER_PREV);\n  }\n  pause() {\n    if (this._isSliding) {\n      triggerTransitionEnd(this._element);\n    }\n    this._clearInterval();\n  }\n  cycle() {\n    this._clearInterval();\n    this._updateInterval();\n    this._interval = setInterval(() => this.nextWhenVisible(), this._config.interval);\n  }\n  _maybeEnableCycle() {\n    if (!this._config.ride) {\n      return;\n    }\n    if (this._isSliding) {\n      EventHandler.one(this._element, EVENT_SLID, () => this.cycle());\n      return;\n    }\n    this.cycle();\n  }\n  to(index) {\n    const items = this._getItems();\n    if (index > items.length - 1 || index < 0) {\n      return;\n    }\n    if (this._isSliding) {\n      EventHandler.one(this._element, EVENT_SLID, () => this.to(index));\n      return;\n    }\n    const activeIndex = this._getItemIndex(this._getActive());\n    if (activeIndex === index) {\n      return;\n    }\n    const order = index > activeIndex ? ORDER_NEXT : ORDER_PREV;\n    this._slide(order, items[index]);\n  }\n  dispose() {\n    if (this._swipeHelper) {\n      this._swipeHelper.dispose();\n    }\n    super.dispose();\n  }\n\n  // Private\n  _configAfterMerge(config) {\n    config.defaultInterval = config.interval;\n    return config;\n  }\n  _addEventListeners() {\n    if (this._config.keyboard) {\n      EventHandler.on(this._element, EVENT_KEYDOWN$1, event => this._keydown(event));\n    }\n    if (this._config.pause === 'hover') {\n      EventHandler.on(this._element, EVENT_MOUSEENTER$1, () => this.pause());\n      EventHandler.on(this._element, EVENT_MOUSELEAVE$1, () => this._maybeEnableCycle());\n    }\n    if (this._config.touch && Swipe.isSupported()) {\n      this._addTouchEventListeners();\n    }\n  }\n  _addTouchEventListeners() {\n    for (const img of SelectorEngine.find(SELECTOR_ITEM_IMG, this._element)) {\n      EventHandler.on(img, EVENT_DRAG_START, event => event.preventDefault());\n    }\n    const endCallBack = () => {\n      if (this._config.pause !== 'hover') {\n        return;\n      }\n\n      // If it's a touch-enabled device, mouseenter/leave are fired as\n      // part of the mouse compatibility events on first tap - the carousel\n      // would stop cycling until user tapped out of it;\n      // here, we listen for touchend, explicitly pause the carousel\n      // (as if it's the second time we tap on it, mouseenter compat event\n      // is NOT fired) and after a timeout (to allow for mouse compatibility\n      // events to fire) we explicitly restart cycling\n\n      this.pause();\n      if (this.touchTimeout) {\n        clearTimeout(this.touchTimeout);\n      }\n      this.touchTimeout = setTimeout(() => this._maybeEnableCycle(), TOUCHEVENT_COMPAT_WAIT + this._config.interval);\n    };\n    const swipeConfig = {\n      leftCallback: () => this._slide(this._directionToOrder(DIRECTION_LEFT)),\n      rightCallback: () => this._slide(this._directionToOrder(DIRECTION_RIGHT)),\n      endCallback: endCallBack\n    };\n    this._swipeHelper = new Swipe(this._element, swipeConfig);\n  }\n  _keydown(event) {\n    if (/input|textarea/i.test(event.target.tagName)) {\n      return;\n    }\n    const direction = KEY_TO_DIRECTION[event.key];\n    if (direction) {\n      event.preventDefault();\n      this._slide(this._directionToOrder(direction));\n    }\n  }\n  _getItemIndex(element) {\n    return this._getItems().indexOf(element);\n  }\n  _setActiveIndicatorElement(index) {\n    if (!this._indicatorsElement) {\n      return;\n    }\n    const activeIndicator = SelectorEngine.findOne(SELECTOR_ACTIVE, this._indicatorsElement);\n    activeIndicator.classList.remove(CLASS_NAME_ACTIVE$2);\n    activeIndicator.removeAttribute('aria-current');\n    const newActiveIndicator = SelectorEngine.findOne(`[data-bs-slide-to=\"${index}\"]`, this._indicatorsElement);\n    if (newActiveIndicator) {\n      newActiveIndicator.classList.add(CLASS_NAME_ACTIVE$2);\n      newActiveIndicator.setAttribute('aria-current', 'true');\n    }\n  }\n  _updateInterval() {\n    const element = this._activeElement || this._getActive();\n    if (!element) {\n      return;\n    }\n    const elementInterval = Number.parseInt(element.getAttribute('data-bs-interval'), 10);\n    this._config.interval = elementInterval || this._config.defaultInterval;\n  }\n  _slide(order, element = null) {\n    if (this._isSliding) {\n      return;\n    }\n    const activeElement = this._getActive();\n    const isNext = order === ORDER_NEXT;\n    const nextElement = element || getNextActiveElement(this._getItems(), activeElement, isNext, this._config.wrap);\n    if (nextElement === activeElement) {\n      return;\n    }\n    const nextElementIndex = this._getItemIndex(nextElement);\n    const triggerEvent = eventName => {\n      return EventHandler.trigger(this._element, eventName, {\n        relatedTarget: nextElement,\n        direction: this._orderToDirection(order),\n        from: this._getItemIndex(activeElement),\n        to: nextElementIndex\n      });\n    };\n    const slideEvent = triggerEvent(EVENT_SLIDE);\n    if (slideEvent.defaultPrevented) {\n      return;\n    }\n    if (!activeElement || !nextElement) {\n      // Some weirdness is happening, so we bail\n      // TODO: change tests that use empty divs to avoid this check\n      return;\n    }\n    const isCycling = Boolean(this._interval);\n    this.pause();\n    this._isSliding = true;\n    this._setActiveIndicatorElement(nextElementIndex);\n    this._activeElement = nextElement;\n    const directionalClassName = isNext ? CLASS_NAME_START : CLASS_NAME_END;\n    const orderClassName = isNext ? CLASS_NAME_NEXT : CLASS_NAME_PREV;\n    nextElement.classList.add(orderClassName);\n    reflow(nextElement);\n    activeElement.classList.add(directionalClassName);\n    nextElement.classList.add(directionalClassName);\n    const completeCallBack = () => {\n      nextElement.classList.remove(directionalClassName, orderClassName);\n      nextElement.classList.add(CLASS_NAME_ACTIVE$2);\n      activeElement.classList.remove(CLASS_NAME_ACTIVE$2, orderClassName, directionalClassName);\n      this._isSliding = false;\n      triggerEvent(EVENT_SLID);\n    };\n    this._queueCallback(completeCallBack, activeElement, this._isAnimated());\n    if (isCycling) {\n      this.cycle();\n    }\n  }\n  _isAnimated() {\n    return this._element.classList.contains(CLASS_NAME_SLIDE);\n  }\n  _getActive() {\n    return SelectorEngine.findOne(SELECTOR_ACTIVE_ITEM, this._element);\n  }\n  _getItems() {\n    return SelectorEngine.find(SELECTOR_ITEM, this._element);\n  }\n  _clearInterval() {\n    if (this._interval) {\n      clearInterval(this._interval);\n      this._interval = null;\n    }\n  }\n  _directionToOrder(direction) {\n    if (isRTL()) {\n      return direction === DIRECTION_LEFT ? ORDER_PREV : ORDER_NEXT;\n    }\n    return direction === DIRECTION_LEFT ? ORDER_NEXT : ORDER_PREV;\n  }\n  _orderToDirection(order) {\n    if (isRTL()) {\n      return order === ORDER_PREV ? DIRECTION_LEFT : DIRECTION_RIGHT;\n    }\n    return order === ORDER_PREV ? DIRECTION_RIGHT : DIRECTION_LEFT;\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = Carousel.getOrCreateInstance(this, config);\n      if (typeof config === 'number') {\n        data.to(config);\n        return;\n      }\n      if (typeof config === 'string') {\n        if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n          throw new TypeError(`No method named \"${config}\"`);\n        }\n        data[config]();\n      }\n    });\n  }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$5, SELECTOR_DATA_SLIDE, function (event) {\n  const target = SelectorEngine.getElementFromSelector(this);\n  if (!target || !target.classList.contains(CLASS_NAME_CAROUSEL)) {\n    return;\n  }\n  event.preventDefault();\n  const carousel = Carousel.getOrCreateInstance(target);\n  const slideIndex = this.getAttribute('data-bs-slide-to');\n  if (slideIndex) {\n    carousel.to(slideIndex);\n    carousel._maybeEnableCycle();\n    return;\n  }\n  if (Manipulator.getDataAttribute(this, 'slide') === 'next') {\n    carousel.next();\n    carousel._maybeEnableCycle();\n    return;\n  }\n  carousel.prev();\n  carousel._maybeEnableCycle();\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$3, () => {\n  const carousels = SelectorEngine.find(SELECTOR_DATA_RIDE);\n  for (const carousel of carousels) {\n    Carousel.getOrCreateInstance(carousel);\n  }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Carousel);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap collapse.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$b = 'collapse';\nconst DATA_KEY$7 = 'bs.collapse';\nconst EVENT_KEY$7 = `.${DATA_KEY$7}`;\nconst DATA_API_KEY$4 = '.data-api';\nconst EVENT_SHOW$6 = `show${EVENT_KEY$7}`;\nconst EVENT_SHOWN$6 = `shown${EVENT_KEY$7}`;\nconst EVENT_HIDE$6 = `hide${EVENT_KEY$7}`;\nconst EVENT_HIDDEN$6 = `hidden${EVENT_KEY$7}`;\nconst EVENT_CLICK_DATA_API$4 = `click${EVENT_KEY$7}${DATA_API_KEY$4}`;\nconst CLASS_NAME_SHOW$7 = 'show';\nconst CLASS_NAME_COLLAPSE = 'collapse';\nconst CLASS_NAME_COLLAPSING = 'collapsing';\nconst CLASS_NAME_COLLAPSED = 'collapsed';\nconst CLASS_NAME_DEEPER_CHILDREN = `:scope .${CLASS_NAME_COLLAPSE} .${CLASS_NAME_COLLAPSE}`;\nconst CLASS_NAME_HORIZONTAL = 'collapse-horizontal';\nconst WIDTH = 'width';\nconst HEIGHT = 'height';\nconst SELECTOR_ACTIVES = '.collapse.show, .collapse.collapsing';\nconst SELECTOR_DATA_TOGGLE$4 = '[data-bs-toggle=\"collapse\"]';\nconst Default$a = {\n  parent: null,\n  toggle: true\n};\nconst DefaultType$a = {\n  parent: '(null|element)',\n  toggle: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Collapse extends BaseComponent {\n  constructor(element, config) {\n    super(element, config);\n    this._isTransitioning = false;\n    this._triggerArray = [];\n    const toggleList = SelectorEngine.find(SELECTOR_DATA_TOGGLE$4);\n    for (const elem of toggleList) {\n      const selector = SelectorEngine.getSelectorFromElement(elem);\n      const filterElement = SelectorEngine.find(selector).filter(foundElement => foundElement === this._element);\n      if (selector !== null && filterElement.length) {\n        this._triggerArray.push(elem);\n      }\n    }\n    this._initializeChildren();\n    if (!this._config.parent) {\n      this._addAriaAndCollapsedClass(this._triggerArray, this._isShown());\n    }\n    if (this._config.toggle) {\n      this.toggle();\n    }\n  }\n\n  // Getters\n  static get Default() {\n    return Default$a;\n  }\n  static get DefaultType() {\n    return DefaultType$a;\n  }\n  static get NAME() {\n    return NAME$b;\n  }\n\n  // Public\n  toggle() {\n    if (this._isShown()) {\n      this.hide();\n    } else {\n      this.show();\n    }\n  }\n  show() {\n    if (this._isTransitioning || this._isShown()) {\n      return;\n    }\n    let activeChildren = [];\n\n    // find active children\n    if (this._config.parent) {\n      activeChildren = this._getFirstLevelChildren(SELECTOR_ACTIVES).filter(element => element !== this._element).map(element => Collapse.getOrCreateInstance(element, {\n        toggle: false\n      }));\n    }\n    if (activeChildren.length && activeChildren[0]._isTransitioning) {\n      return;\n    }\n    const startEvent = EventHandler.trigger(this._element, EVENT_SHOW$6);\n    if (startEvent.defaultPrevented) {\n      return;\n    }\n    for (const activeInstance of activeChildren) {\n      activeInstance.hide();\n    }\n    const dimension = this._getDimension();\n    this._element.classList.remove(CLASS_NAME_COLLAPSE);\n    this._element.classList.add(CLASS_NAME_COLLAPSING);\n    this._element.style[dimension] = 0;\n    this._addAriaAndCollapsedClass(this._triggerArray, true);\n    this._isTransitioning = true;\n    const complete = () => {\n      this._isTransitioning = false;\n      this._element.classList.remove(CLASS_NAME_COLLAPSING);\n      this._element.classList.add(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n      this._element.style[dimension] = '';\n      EventHandler.trigger(this._element, EVENT_SHOWN$6);\n    };\n    const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1);\n    const scrollSize = `scroll${capitalizedDimension}`;\n    this._queueCallback(complete, this._element, true);\n    this._element.style[dimension] = `${this._element[scrollSize]}px`;\n  }\n  hide() {\n    if (this._isTransitioning || !this._isShown()) {\n      return;\n    }\n    const startEvent = EventHandler.trigger(this._element, EVENT_HIDE$6);\n    if (startEvent.defaultPrevented) {\n      return;\n    }\n    const dimension = this._getDimension();\n    this._element.style[dimension] = `${this._element.getBoundingClientRect()[dimension]}px`;\n    reflow(this._element);\n    this._element.classList.add(CLASS_NAME_COLLAPSING);\n    this._element.classList.remove(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n    for (const trigger of this._triggerArray) {\n      const element = SelectorEngine.getElementFromSelector(trigger);\n      if (element && !this._isShown(element)) {\n        this._addAriaAndCollapsedClass([trigger], false);\n      }\n    }\n    this._isTransitioning = true;\n    const complete = () => {\n      this._isTransitioning = false;\n      this._element.classList.remove(CLASS_NAME_COLLAPSING);\n      this._element.classList.add(CLASS_NAME_COLLAPSE);\n      EventHandler.trigger(this._element, EVENT_HIDDEN$6);\n    };\n    this._element.style[dimension] = '';\n    this._queueCallback(complete, this._element, true);\n  }\n  _isShown(element = this._element) {\n    return element.classList.contains(CLASS_NAME_SHOW$7);\n  }\n\n  // Private\n  _configAfterMerge(config) {\n    config.toggle = Boolean(config.toggle); // Coerce string values\n    config.parent = getElement(config.parent);\n    return config;\n  }\n  _getDimension() {\n    return this._element.classList.contains(CLASS_NAME_HORIZONTAL) ? WIDTH : HEIGHT;\n  }\n  _initializeChildren() {\n    if (!this._config.parent) {\n      return;\n    }\n    const children = this._getFirstLevelChildren(SELECTOR_DATA_TOGGLE$4);\n    for (const element of children) {\n      const selected = SelectorEngine.getElementFromSelector(element);\n      if (selected) {\n        this._addAriaAndCollapsedClass([element], this._isShown(selected));\n      }\n    }\n  }\n  _getFirstLevelChildren(selector) {\n    const children = SelectorEngine.find(CLASS_NAME_DEEPER_CHILDREN, this._config.parent);\n    // remove children if greater depth\n    return SelectorEngine.find(selector, this._config.parent).filter(element => !children.includes(element));\n  }\n  _addAriaAndCollapsedClass(triggerArray, isOpen) {\n    if (!triggerArray.length) {\n      return;\n    }\n    for (const element of triggerArray) {\n      element.classList.toggle(CLASS_NAME_COLLAPSED, !isOpen);\n      element.setAttribute('aria-expanded', isOpen);\n    }\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    const _config = {};\n    if (typeof config === 'string' && /show|hide/.test(config)) {\n      _config.toggle = false;\n    }\n    return this.each(function () {\n      const data = Collapse.getOrCreateInstance(this, _config);\n      if (typeof config === 'string') {\n        if (typeof data[config] === 'undefined') {\n          throw new TypeError(`No method named \"${config}\"`);\n        }\n        data[config]();\n      }\n    });\n  }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$4, SELECTOR_DATA_TOGGLE$4, function (event) {\n  // preventDefault only for <a> elements (which change the URL) not inside the collapsible element\n  if (event.target.tagName === 'A' || event.delegateTarget && event.delegateTarget.tagName === 'A') {\n    event.preventDefault();\n  }\n  for (const element of SelectorEngine.getMultipleElementsFromSelector(this)) {\n    Collapse.getOrCreateInstance(element, {\n      toggle: false\n    }).toggle();\n  }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Collapse);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dropdown.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$a = 'dropdown';\nconst DATA_KEY$6 = 'bs.dropdown';\nconst EVENT_KEY$6 = `.${DATA_KEY$6}`;\nconst DATA_API_KEY$3 = '.data-api';\nconst ESCAPE_KEY$2 = 'Escape';\nconst TAB_KEY$1 = 'Tab';\nconst ARROW_UP_KEY$1 = 'ArrowUp';\nconst ARROW_DOWN_KEY$1 = 'ArrowDown';\nconst RIGHT_MOUSE_BUTTON = 2; // MouseEvent.button value for the secondary button, usually the right button\n\nconst EVENT_HIDE$5 = `hide${EVENT_KEY$6}`;\nconst EVENT_HIDDEN$5 = `hidden${EVENT_KEY$6}`;\nconst EVENT_SHOW$5 = `show${EVENT_KEY$6}`;\nconst EVENT_SHOWN$5 = `shown${EVENT_KEY$6}`;\nconst EVENT_CLICK_DATA_API$3 = `click${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYDOWN_DATA_API = `keydown${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYUP_DATA_API = `keyup${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst CLASS_NAME_SHOW$6 = 'show';\nconst CLASS_NAME_DROPUP = 'dropup';\nconst CLASS_NAME_DROPEND = 'dropend';\nconst CLASS_NAME_DROPSTART = 'dropstart';\nconst CLASS_NAME_DROPUP_CENTER = 'dropup-center';\nconst CLASS_NAME_DROPDOWN_CENTER = 'dropdown-center';\nconst SELECTOR_DATA_TOGGLE$3 = '[data-bs-toggle=\"dropdown\"]:not(.disabled):not(:disabled)';\nconst SELECTOR_DATA_TOGGLE_SHOWN = `${SELECTOR_DATA_TOGGLE$3}.${CLASS_NAME_SHOW$6}`;\nconst SELECTOR_MENU = '.dropdown-menu';\nconst SELECTOR_NAVBAR = '.navbar';\nconst SELECTOR_NAVBAR_NAV = '.navbar-nav';\nconst SELECTOR_VISIBLE_ITEMS = '.dropdown-menu .dropdown-item:not(.disabled):not(:disabled)';\nconst PLACEMENT_TOP = isRTL() ? 'top-end' : 'top-start';\nconst PLACEMENT_TOPEND = isRTL() ? 'top-start' : 'top-end';\nconst PLACEMENT_BOTTOM = isRTL() ? 'bottom-end' : 'bottom-start';\nconst PLACEMENT_BOTTOMEND = isRTL() ? 'bottom-start' : 'bottom-end';\nconst PLACEMENT_RIGHT = isRTL() ? 'left-start' : 'right-start';\nconst PLACEMENT_LEFT = isRTL() ? 'right-start' : 'left-start';\nconst PLACEMENT_TOPCENTER = 'top';\nconst PLACEMENT_BOTTOMCENTER = 'bottom';\nconst Default$9 = {\n  autoClose: true,\n  boundary: 'clippingParents',\n  display: 'dynamic',\n  offset: [0, 2],\n  popperConfig: null,\n  reference: 'toggle'\n};\nconst DefaultType$9 = {\n  autoClose: '(boolean|string)',\n  boundary: '(string|element)',\n  display: 'string',\n  offset: '(array|string|function)',\n  popperConfig: '(null|object|function)',\n  reference: '(string|element|object)'\n};\n\n/**\n * Class definition\n */\n\nclass Dropdown extends BaseComponent {\n  constructor(element, config) {\n    super(element, config);\n    this._popper = null;\n    this._parent = this._element.parentNode; // dropdown wrapper\n    // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n    this._menu = SelectorEngine.next(this._element, SELECTOR_MENU)[0] || SelectorEngine.prev(this._element, SELECTOR_MENU)[0] || SelectorEngine.findOne(SELECTOR_MENU, this._parent);\n    this._inNavbar = this._detectNavbar();\n  }\n\n  // Getters\n  static get Default() {\n    return Default$9;\n  }\n  static get DefaultType() {\n    return DefaultType$9;\n  }\n  static get NAME() {\n    return NAME$a;\n  }\n\n  // Public\n  toggle() {\n    return this._isShown() ? this.hide() : this.show();\n  }\n  show() {\n    if (isDisabled(this._element) || this._isShown()) {\n      return;\n    }\n    const relatedTarget = {\n      relatedTarget: this._element\n    };\n    const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$5, relatedTarget);\n    if (showEvent.defaultPrevented) {\n      return;\n    }\n    this._createPopper();\n\n    // If this is a touch-enabled device we add extra\n    // empty mouseover listeners to the body's immediate children;\n    // only needed because of broken event delegation on iOS\n    // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n    if ('ontouchstart' in document.documentElement && !this._parent.closest(SELECTOR_NAVBAR_NAV)) {\n      for (const element of [].concat(...document.body.children)) {\n        EventHandler.on(element, 'mouseover', noop);\n      }\n    }\n    this._element.focus();\n    this._element.setAttribute('aria-expanded', true);\n    this._menu.classList.add(CLASS_NAME_SHOW$6);\n    this._element.classList.add(CLASS_NAME_SHOW$6);\n    EventHandler.trigger(this._element, EVENT_SHOWN$5, relatedTarget);\n  }\n  hide() {\n    if (isDisabled(this._element) || !this._isShown()) {\n      return;\n    }\n    const relatedTarget = {\n      relatedTarget: this._element\n    };\n    this._completeHide(relatedTarget);\n  }\n  dispose() {\n    if (this._popper) {\n      this._popper.destroy();\n    }\n    super.dispose();\n  }\n  update() {\n    this._inNavbar = this._detectNavbar();\n    if (this._popper) {\n      this._popper.update();\n    }\n  }\n\n  // Private\n  _completeHide(relatedTarget) {\n    const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$5, relatedTarget);\n    if (hideEvent.defaultPrevented) {\n      return;\n    }\n\n    // If this is a touch-enabled device we remove the extra\n    // empty mouseover listeners we added for iOS support\n    if ('ontouchstart' in document.documentElement) {\n      for (const element of [].concat(...document.body.children)) {\n        EventHandler.off(element, 'mouseover', noop);\n      }\n    }\n    if (this._popper) {\n      this._popper.destroy();\n    }\n    this._menu.classList.remove(CLASS_NAME_SHOW$6);\n    this._element.classList.remove(CLASS_NAME_SHOW$6);\n    this._element.setAttribute('aria-expanded', 'false');\n    Manipulator.removeDataAttribute(this._menu, 'popper');\n    EventHandler.trigger(this._element, EVENT_HIDDEN$5, relatedTarget);\n  }\n  _getConfig(config) {\n    config = super._getConfig(config);\n    if (typeof config.reference === 'object' && !isElement(config.reference) && typeof config.reference.getBoundingClientRect !== 'function') {\n      // Popper virtual elements require a getBoundingClientRect method\n      throw new TypeError(`${NAME$a.toUpperCase()}: Option \"reference\" provided type \"object\" without a required \"getBoundingClientRect\" method.`);\n    }\n    return config;\n  }\n  _createPopper() {\n    if (typeof Popper === 'undefined') {\n      throw new TypeError('Bootstrap\\'s dropdowns require Popper (https://popper.js.org)');\n    }\n    let referenceElement = this._element;\n    if (this._config.reference === 'parent') {\n      referenceElement = this._parent;\n    } else if (isElement(this._config.reference)) {\n      referenceElement = getElement(this._config.reference);\n    } else if (typeof this._config.reference === 'object') {\n      referenceElement = this._config.reference;\n    }\n    const popperConfig = this._getPopperConfig();\n    this._popper = Popper.createPopper(referenceElement, this._menu, popperConfig);\n  }\n  _isShown() {\n    return this._menu.classList.contains(CLASS_NAME_SHOW$6);\n  }\n  _getPlacement() {\n    const parentDropdown = this._parent;\n    if (parentDropdown.classList.contains(CLASS_NAME_DROPEND)) {\n      return PLACEMENT_RIGHT;\n    }\n    if (parentDropdown.classList.contains(CLASS_NAME_DROPSTART)) {\n      return PLACEMENT_LEFT;\n    }\n    if (parentDropdown.classList.contains(CLASS_NAME_DROPUP_CENTER)) {\n      return PLACEMENT_TOPCENTER;\n    }\n    if (parentDropdown.classList.contains(CLASS_NAME_DROPDOWN_CENTER)) {\n      return PLACEMENT_BOTTOMCENTER;\n    }\n\n    // We need to trim the value because custom properties can also include spaces\n    const isEnd = getComputedStyle(this._menu).getPropertyValue('--bs-position').trim() === 'end';\n    if (parentDropdown.classList.contains(CLASS_NAME_DROPUP)) {\n      return isEnd ? PLACEMENT_TOPEND : PLACEMENT_TOP;\n    }\n    return isEnd ? PLACEMENT_BOTTOMEND : PLACEMENT_BOTTOM;\n  }\n  _detectNavbar() {\n    return this._element.closest(SELECTOR_NAVBAR) !== null;\n  }\n  _getOffset() {\n    const {\n      offset\n    } = this._config;\n    if (typeof offset === 'string') {\n      return offset.split(',').map(value => Number.parseInt(value, 10));\n    }\n    if (typeof offset === 'function') {\n      return popperData => offset(popperData, this._element);\n    }\n    return offset;\n  }\n  _getPopperConfig() {\n    const defaultBsPopperConfig = {\n      placement: this._getPlacement(),\n      modifiers: [{\n        name: 'preventOverflow',\n        options: {\n          boundary: this._config.boundary\n        }\n      }, {\n        name: 'offset',\n        options: {\n          offset: this._getOffset()\n        }\n      }]\n    };\n\n    // Disable Popper if we have a static display or Dropdown is in Navbar\n    if (this._inNavbar || this._config.display === 'static') {\n      Manipulator.setDataAttribute(this._menu, 'popper', 'static'); // TODO: v6 remove\n      defaultBsPopperConfig.modifiers = [{\n        name: 'applyStyles',\n        enabled: false\n      }];\n    }\n    return {\n      ...defaultBsPopperConfig,\n      ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n    };\n  }\n  _selectMenuItem({\n    key,\n    target\n  }) {\n    const items = SelectorEngine.find(SELECTOR_VISIBLE_ITEMS, this._menu).filter(element => isVisible(element));\n    if (!items.length) {\n      return;\n    }\n\n    // if target isn't included in items (e.g. when expanding the dropdown)\n    // allow cycling to get the last item in case key equals ARROW_UP_KEY\n    getNextActiveElement(items, target, key === ARROW_DOWN_KEY$1, !items.includes(target)).focus();\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = Dropdown.getOrCreateInstance(this, config);\n      if (typeof config !== 'string') {\n        return;\n      }\n      if (typeof data[config] === 'undefined') {\n        throw new TypeError(`No method named \"${config}\"`);\n      }\n      data[config]();\n    });\n  }\n  static clearMenus(event) {\n    if (event.button === RIGHT_MOUSE_BUTTON || event.type === 'keyup' && event.key !== TAB_KEY$1) {\n      return;\n    }\n    const openToggles = SelectorEngine.find(SELECTOR_DATA_TOGGLE_SHOWN);\n    for (const toggle of openToggles) {\n      const context = Dropdown.getInstance(toggle);\n      if (!context || context._config.autoClose === false) {\n        continue;\n      }\n      const composedPath = event.composedPath();\n      const isMenuTarget = composedPath.includes(context._menu);\n      if (composedPath.includes(context._element) || context._config.autoClose === 'inside' && !isMenuTarget || context._config.autoClose === 'outside' && isMenuTarget) {\n        continue;\n      }\n\n      // Tab navigation through the dropdown menu or events from contained inputs shouldn't close the menu\n      if (context._menu.contains(event.target) && (event.type === 'keyup' && event.key === TAB_KEY$1 || /input|select|option|textarea|form/i.test(event.target.tagName))) {\n        continue;\n      }\n      const relatedTarget = {\n        relatedTarget: context._element\n      };\n      if (event.type === 'click') {\n        relatedTarget.clickEvent = event;\n      }\n      context._completeHide(relatedTarget);\n    }\n  }\n  static dataApiKeydownHandler(event) {\n    // If not an UP | DOWN | ESCAPE key => not a dropdown command\n    // If input/textarea && if key is other than ESCAPE => not a dropdown command\n\n    const isInput = /input|textarea/i.test(event.target.tagName);\n    const isEscapeEvent = event.key === ESCAPE_KEY$2;\n    const isUpOrDownEvent = [ARROW_UP_KEY$1, ARROW_DOWN_KEY$1].includes(event.key);\n    if (!isUpOrDownEvent && !isEscapeEvent) {\n      return;\n    }\n    if (isInput && !isEscapeEvent) {\n      return;\n    }\n    event.preventDefault();\n\n    // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n    const getToggleButton = this.matches(SELECTOR_DATA_TOGGLE$3) ? this : SelectorEngine.prev(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.next(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.findOne(SELECTOR_DATA_TOGGLE$3, event.delegateTarget.parentNode);\n    const instance = Dropdown.getOrCreateInstance(getToggleButton);\n    if (isUpOrDownEvent) {\n      event.stopPropagation();\n      instance.show();\n      instance._selectMenuItem(event);\n      return;\n    }\n    if (instance._isShown()) {\n      // else is escape and we check if it is shown\n      event.stopPropagation();\n      instance.hide();\n      getToggleButton.focus();\n    }\n  }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_DATA_TOGGLE$3, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_MENU, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_KEYUP_DATA_API, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, SELECTOR_DATA_TOGGLE$3, function (event) {\n  event.preventDefault();\n  Dropdown.getOrCreateInstance(this).toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Dropdown);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/backdrop.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$9 = 'backdrop';\nconst CLASS_NAME_FADE$4 = 'fade';\nconst CLASS_NAME_SHOW$5 = 'show';\nconst EVENT_MOUSEDOWN = `mousedown.bs.${NAME$9}`;\nconst Default$8 = {\n  className: 'modal-backdrop',\n  clickCallback: null,\n  isAnimated: false,\n  isVisible: true,\n  // if false, we use the backdrop helper without adding any element to the dom\n  rootElement: 'body' // give the choice to place backdrop under different elements\n};\n\nconst DefaultType$8 = {\n  className: 'string',\n  clickCallback: '(function|null)',\n  isAnimated: 'boolean',\n  isVisible: 'boolean',\n  rootElement: '(element|string)'\n};\n\n/**\n * Class definition\n */\n\nclass Backdrop extends Config {\n  constructor(config) {\n    super();\n    this._config = this._getConfig(config);\n    this._isAppended = false;\n    this._element = null;\n  }\n\n  // Getters\n  static get Default() {\n    return Default$8;\n  }\n  static get DefaultType() {\n    return DefaultType$8;\n  }\n  static get NAME() {\n    return NAME$9;\n  }\n\n  // Public\n  show(callback) {\n    if (!this._config.isVisible) {\n      execute(callback);\n      return;\n    }\n    this._append();\n    const element = this._getElement();\n    if (this._config.isAnimated) {\n      reflow(element);\n    }\n    element.classList.add(CLASS_NAME_SHOW$5);\n    this._emulateAnimation(() => {\n      execute(callback);\n    });\n  }\n  hide(callback) {\n    if (!this._config.isVisible) {\n      execute(callback);\n      return;\n    }\n    this._getElement().classList.remove(CLASS_NAME_SHOW$5);\n    this._emulateAnimation(() => {\n      this.dispose();\n      execute(callback);\n    });\n  }\n  dispose() {\n    if (!this._isAppended) {\n      return;\n    }\n    EventHandler.off(this._element, EVENT_MOUSEDOWN);\n    this._element.remove();\n    this._isAppended = false;\n  }\n\n  // Private\n  _getElement() {\n    if (!this._element) {\n      const backdrop = document.createElement('div');\n      backdrop.className = this._config.className;\n      if (this._config.isAnimated) {\n        backdrop.classList.add(CLASS_NAME_FADE$4);\n      }\n      this._element = backdrop;\n    }\n    return this._element;\n  }\n  _configAfterMerge(config) {\n    // use getElement() with the default \"body\" to get a fresh Element on each instantiation\n    config.rootElement = getElement(config.rootElement);\n    return config;\n  }\n  _append() {\n    if (this._isAppended) {\n      return;\n    }\n    const element = this._getElement();\n    this._config.rootElement.append(element);\n    EventHandler.on(element, EVENT_MOUSEDOWN, () => {\n      execute(this._config.clickCallback);\n    });\n    this._isAppended = true;\n  }\n  _emulateAnimation(callback) {\n    executeAfterTransition(callback, this._getElement(), this._config.isAnimated);\n  }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/focustrap.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$8 = 'focustrap';\nconst DATA_KEY$5 = 'bs.focustrap';\nconst EVENT_KEY$5 = `.${DATA_KEY$5}`;\nconst EVENT_FOCUSIN$2 = `focusin${EVENT_KEY$5}`;\nconst EVENT_KEYDOWN_TAB = `keydown.tab${EVENT_KEY$5}`;\nconst TAB_KEY = 'Tab';\nconst TAB_NAV_FORWARD = 'forward';\nconst TAB_NAV_BACKWARD = 'backward';\nconst Default$7 = {\n  autofocus: true,\n  trapElement: null // The element to trap focus inside of\n};\n\nconst DefaultType$7 = {\n  autofocus: 'boolean',\n  trapElement: 'element'\n};\n\n/**\n * Class definition\n */\n\nclass FocusTrap extends Config {\n  constructor(config) {\n    super();\n    this._config = this._getConfig(config);\n    this._isActive = false;\n    this._lastTabNavDirection = null;\n  }\n\n  // Getters\n  static get Default() {\n    return Default$7;\n  }\n  static get DefaultType() {\n    return DefaultType$7;\n  }\n  static get NAME() {\n    return NAME$8;\n  }\n\n  // Public\n  activate() {\n    if (this._isActive) {\n      return;\n    }\n    if (this._config.autofocus) {\n      this._config.trapElement.focus();\n    }\n    EventHandler.off(document, EVENT_KEY$5); // guard against infinite focus loop\n    EventHandler.on(document, EVENT_FOCUSIN$2, event => this._handleFocusin(event));\n    EventHandler.on(document, EVENT_KEYDOWN_TAB, event => this._handleKeydown(event));\n    this._isActive = true;\n  }\n  deactivate() {\n    if (!this._isActive) {\n      return;\n    }\n    this._isActive = false;\n    EventHandler.off(document, EVENT_KEY$5);\n  }\n\n  // Private\n  _handleFocusin(event) {\n    const {\n      trapElement\n    } = this._config;\n    if (event.target === document || event.target === trapElement || trapElement.contains(event.target)) {\n      return;\n    }\n    const elements = SelectorEngine.focusableChildren(trapElement);\n    if (elements.length === 0) {\n      trapElement.focus();\n    } else if (this._lastTabNavDirection === TAB_NAV_BACKWARD) {\n      elements[elements.length - 1].focus();\n    } else {\n      elements[0].focus();\n    }\n  }\n  _handleKeydown(event) {\n    if (event.key !== TAB_KEY) {\n      return;\n    }\n    this._lastTabNavDirection = event.shiftKey ? TAB_NAV_BACKWARD : TAB_NAV_FORWARD;\n  }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/scrollBar.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst SELECTOR_FIXED_CONTENT = '.fixed-top, .fixed-bottom, .is-fixed, .sticky-top';\nconst SELECTOR_STICKY_CONTENT = '.sticky-top';\nconst PROPERTY_PADDING = 'padding-right';\nconst PROPERTY_MARGIN = 'margin-right';\n\n/**\n * Class definition\n */\n\nclass ScrollBarHelper {\n  constructor() {\n    this._element = document.body;\n  }\n\n  // Public\n  getWidth() {\n    // https://developer.mozilla.org/en-US/docs/Web/API/Window/innerWidth#usage_notes\n    const documentWidth = document.documentElement.clientWidth;\n    return Math.abs(window.innerWidth - documentWidth);\n  }\n  hide() {\n    const width = this.getWidth();\n    this._disableOverFlow();\n    // give padding to element to balance the hidden scrollbar width\n    this._setElementAttributes(this._element, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n    // trick: We adjust positive paddingRight and negative marginRight to sticky-top elements to keep showing fullwidth\n    this._setElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n    this._setElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN, calculatedValue => calculatedValue - width);\n  }\n  reset() {\n    this._resetElementAttributes(this._element, 'overflow');\n    this._resetElementAttributes(this._element, PROPERTY_PADDING);\n    this._resetElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING);\n    this._resetElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN);\n  }\n  isOverflowing() {\n    return this.getWidth() > 0;\n  }\n\n  // Private\n  _disableOverFlow() {\n    this._saveInitialAttribute(this._element, 'overflow');\n    this._element.style.overflow = 'hidden';\n  }\n  _setElementAttributes(selector, styleProperty, callback) {\n    const scrollbarWidth = this.getWidth();\n    const manipulationCallBack = element => {\n      if (element !== this._element && window.innerWidth > element.clientWidth + scrollbarWidth) {\n        return;\n      }\n      this._saveInitialAttribute(element, styleProperty);\n      const calculatedValue = window.getComputedStyle(element).getPropertyValue(styleProperty);\n      element.style.setProperty(styleProperty, `${callback(Number.parseFloat(calculatedValue))}px`);\n    };\n    this._applyManipulationCallback(selector, manipulationCallBack);\n  }\n  _saveInitialAttribute(element, styleProperty) {\n    const actualValue = element.style.getPropertyValue(styleProperty);\n    if (actualValue) {\n      Manipulator.setDataAttribute(element, styleProperty, actualValue);\n    }\n  }\n  _resetElementAttributes(selector, styleProperty) {\n    const manipulationCallBack = element => {\n      const value = Manipulator.getDataAttribute(element, styleProperty);\n      // We only want to remove the property if the value is `null`; the value can also be zero\n      if (value === null) {\n        element.style.removeProperty(styleProperty);\n        return;\n      }\n      Manipulator.removeDataAttribute(element, styleProperty);\n      element.style.setProperty(styleProperty, value);\n    };\n    this._applyManipulationCallback(selector, manipulationCallBack);\n  }\n  _applyManipulationCallback(selector, callBack) {\n    if (isElement(selector)) {\n      callBack(selector);\n      return;\n    }\n    for (const sel of SelectorEngine.find(selector, this._element)) {\n      callBack(sel);\n    }\n  }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap modal.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$7 = 'modal';\nconst DATA_KEY$4 = 'bs.modal';\nconst EVENT_KEY$4 = `.${DATA_KEY$4}`;\nconst DATA_API_KEY$2 = '.data-api';\nconst ESCAPE_KEY$1 = 'Escape';\nconst EVENT_HIDE$4 = `hide${EVENT_KEY$4}`;\nconst EVENT_HIDE_PREVENTED$1 = `hidePrevented${EVENT_KEY$4}`;\nconst EVENT_HIDDEN$4 = `hidden${EVENT_KEY$4}`;\nconst EVENT_SHOW$4 = `show${EVENT_KEY$4}`;\nconst EVENT_SHOWN$4 = `shown${EVENT_KEY$4}`;\nconst EVENT_RESIZE$1 = `resize${EVENT_KEY$4}`;\nconst EVENT_CLICK_DISMISS = `click.dismiss${EVENT_KEY$4}`;\nconst EVENT_MOUSEDOWN_DISMISS = `mousedown.dismiss${EVENT_KEY$4}`;\nconst EVENT_KEYDOWN_DISMISS$1 = `keydown.dismiss${EVENT_KEY$4}`;\nconst EVENT_CLICK_DATA_API$2 = `click${EVENT_KEY$4}${DATA_API_KEY$2}`;\nconst CLASS_NAME_OPEN = 'modal-open';\nconst CLASS_NAME_FADE$3 = 'fade';\nconst CLASS_NAME_SHOW$4 = 'show';\nconst CLASS_NAME_STATIC = 'modal-static';\nconst OPEN_SELECTOR$1 = '.modal.show';\nconst SELECTOR_DIALOG = '.modal-dialog';\nconst SELECTOR_MODAL_BODY = '.modal-body';\nconst SELECTOR_DATA_TOGGLE$2 = '[data-bs-toggle=\"modal\"]';\nconst Default$6 = {\n  backdrop: true,\n  focus: true,\n  keyboard: true\n};\nconst DefaultType$6 = {\n  backdrop: '(boolean|string)',\n  focus: 'boolean',\n  keyboard: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Modal extends BaseComponent {\n  constructor(element, config) {\n    super(element, config);\n    this._dialog = SelectorEngine.findOne(SELECTOR_DIALOG, this._element);\n    this._backdrop = this._initializeBackDrop();\n    this._focustrap = this._initializeFocusTrap();\n    this._isShown = false;\n    this._isTransitioning = false;\n    this._scrollBar = new ScrollBarHelper();\n    this._addEventListeners();\n  }\n\n  // Getters\n  static get Default() {\n    return Default$6;\n  }\n  static get DefaultType() {\n    return DefaultType$6;\n  }\n  static get NAME() {\n    return NAME$7;\n  }\n\n  // Public\n  toggle(relatedTarget) {\n    return this._isShown ? this.hide() : this.show(relatedTarget);\n  }\n  show(relatedTarget) {\n    if (this._isShown || this._isTransitioning) {\n      return;\n    }\n    const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$4, {\n      relatedTarget\n    });\n    if (showEvent.defaultPrevented) {\n      return;\n    }\n    this._isShown = true;\n    this._isTransitioning = true;\n    this._scrollBar.hide();\n    document.body.classList.add(CLASS_NAME_OPEN);\n    this._adjustDialog();\n    this._backdrop.show(() => this._showElement(relatedTarget));\n  }\n  hide() {\n    if (!this._isShown || this._isTransitioning) {\n      return;\n    }\n    const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$4);\n    if (hideEvent.defaultPrevented) {\n      return;\n    }\n    this._isShown = false;\n    this._isTransitioning = true;\n    this._focustrap.deactivate();\n    this._element.classList.remove(CLASS_NAME_SHOW$4);\n    this._queueCallback(() => this._hideModal(), this._element, this._isAnimated());\n  }\n  dispose() {\n    EventHandler.off(window, EVENT_KEY$4);\n    EventHandler.off(this._dialog, EVENT_KEY$4);\n    this._backdrop.dispose();\n    this._focustrap.deactivate();\n    super.dispose();\n  }\n  handleUpdate() {\n    this._adjustDialog();\n  }\n\n  // Private\n  _initializeBackDrop() {\n    return new Backdrop({\n      isVisible: Boolean(this._config.backdrop),\n      // 'static' option will be translated to true, and booleans will keep their value,\n      isAnimated: this._isAnimated()\n    });\n  }\n  _initializeFocusTrap() {\n    return new FocusTrap({\n      trapElement: this._element\n    });\n  }\n  _showElement(relatedTarget) {\n    // try to append dynamic modal\n    if (!document.body.contains(this._element)) {\n      document.body.append(this._element);\n    }\n    this._element.style.display = 'block';\n    this._element.removeAttribute('aria-hidden');\n    this._element.setAttribute('aria-modal', true);\n    this._element.setAttribute('role', 'dialog');\n    this._element.scrollTop = 0;\n    const modalBody = SelectorEngine.findOne(SELECTOR_MODAL_BODY, this._dialog);\n    if (modalBody) {\n      modalBody.scrollTop = 0;\n    }\n    reflow(this._element);\n    this._element.classList.add(CLASS_NAME_SHOW$4);\n    const transitionComplete = () => {\n      if (this._config.focus) {\n        this._focustrap.activate();\n      }\n      this._isTransitioning = false;\n      EventHandler.trigger(this._element, EVENT_SHOWN$4, {\n        relatedTarget\n      });\n    };\n    this._queueCallback(transitionComplete, this._dialog, this._isAnimated());\n  }\n  _addEventListeners() {\n    EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS$1, event => {\n      if (event.key !== ESCAPE_KEY$1) {\n        return;\n      }\n      if (this._config.keyboard) {\n        this.hide();\n        return;\n      }\n      this._triggerBackdropTransition();\n    });\n    EventHandler.on(window, EVENT_RESIZE$1, () => {\n      if (this._isShown && !this._isTransitioning) {\n        this._adjustDialog();\n      }\n    });\n    EventHandler.on(this._element, EVENT_MOUSEDOWN_DISMISS, event => {\n      // a bad trick to segregate clicks that may start inside dialog but end outside, and avoid listen to scrollbar clicks\n      EventHandler.one(this._element, EVENT_CLICK_DISMISS, event2 => {\n        if (this._element !== event.target || this._element !== event2.target) {\n          return;\n        }\n        if (this._config.backdrop === 'static') {\n          this._triggerBackdropTransition();\n          return;\n        }\n        if (this._config.backdrop) {\n          this.hide();\n        }\n      });\n    });\n  }\n  _hideModal() {\n    this._element.style.display = 'none';\n    this._element.setAttribute('aria-hidden', true);\n    this._element.removeAttribute('aria-modal');\n    this._element.removeAttribute('role');\n    this._isTransitioning = false;\n    this._backdrop.hide(() => {\n      document.body.classList.remove(CLASS_NAME_OPEN);\n      this._resetAdjustments();\n      this._scrollBar.reset();\n      EventHandler.trigger(this._element, EVENT_HIDDEN$4);\n    });\n  }\n  _isAnimated() {\n    return this._element.classList.contains(CLASS_NAME_FADE$3);\n  }\n  _triggerBackdropTransition() {\n    const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED$1);\n    if (hideEvent.defaultPrevented) {\n      return;\n    }\n    const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n    const initialOverflowY = this._element.style.overflowY;\n    // return if the following background transition hasn't yet completed\n    if (initialOverflowY === 'hidden' || this._element.classList.contains(CLASS_NAME_STATIC)) {\n      return;\n    }\n    if (!isModalOverflowing) {\n      this._element.style.overflowY = 'hidden';\n    }\n    this._element.classList.add(CLASS_NAME_STATIC);\n    this._queueCallback(() => {\n      this._element.classList.remove(CLASS_NAME_STATIC);\n      this._queueCallback(() => {\n        this._element.style.overflowY = initialOverflowY;\n      }, this._dialog);\n    }, this._dialog);\n    this._element.focus();\n  }\n\n  /**\n   * The following methods are used to handle overflowing modals\n   */\n\n  _adjustDialog() {\n    const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n    const scrollbarWidth = this._scrollBar.getWidth();\n    const isBodyOverflowing = scrollbarWidth > 0;\n    if (isBodyOverflowing && !isModalOverflowing) {\n      const property = isRTL() ? 'paddingLeft' : 'paddingRight';\n      this._element.style[property] = `${scrollbarWidth}px`;\n    }\n    if (!isBodyOverflowing && isModalOverflowing) {\n      const property = isRTL() ? 'paddingRight' : 'paddingLeft';\n      this._element.style[property] = `${scrollbarWidth}px`;\n    }\n  }\n  _resetAdjustments() {\n    this._element.style.paddingLeft = '';\n    this._element.style.paddingRight = '';\n  }\n\n  // Static\n  static jQueryInterface(config, relatedTarget) {\n    return this.each(function () {\n      const data = Modal.getOrCreateInstance(this, config);\n      if (typeof config !== 'string') {\n        return;\n      }\n      if (typeof data[config] === 'undefined') {\n        throw new TypeError(`No method named \"${config}\"`);\n      }\n      data[config](relatedTarget);\n    });\n  }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$2, SELECTOR_DATA_TOGGLE$2, function (event) {\n  const target = SelectorEngine.getElementFromSelector(this);\n  if (['A', 'AREA'].includes(this.tagName)) {\n    event.preventDefault();\n  }\n  EventHandler.one(target, EVENT_SHOW$4, showEvent => {\n    if (showEvent.defaultPrevented) {\n      // only register focus restorer if modal will actually get shown\n      return;\n    }\n    EventHandler.one(target, EVENT_HIDDEN$4, () => {\n      if (isVisible(this)) {\n        this.focus();\n      }\n    });\n  });\n\n  // avoid conflict when clicking modal toggler while another one is open\n  const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR$1);\n  if (alreadyOpen) {\n    Modal.getInstance(alreadyOpen).hide();\n  }\n  const data = Modal.getOrCreateInstance(target);\n  data.toggle(this);\n});\nenableDismissTrigger(Modal);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Modal);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap offcanvas.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$6 = 'offcanvas';\nconst DATA_KEY$3 = 'bs.offcanvas';\nconst EVENT_KEY$3 = `.${DATA_KEY$3}`;\nconst DATA_API_KEY$1 = '.data-api';\nconst EVENT_LOAD_DATA_API$2 = `load${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst ESCAPE_KEY = 'Escape';\nconst CLASS_NAME_SHOW$3 = 'show';\nconst CLASS_NAME_SHOWING$1 = 'showing';\nconst CLASS_NAME_HIDING = 'hiding';\nconst CLASS_NAME_BACKDROP = 'offcanvas-backdrop';\nconst OPEN_SELECTOR = '.offcanvas.show';\nconst EVENT_SHOW$3 = `show${EVENT_KEY$3}`;\nconst EVENT_SHOWN$3 = `shown${EVENT_KEY$3}`;\nconst EVENT_HIDE$3 = `hide${EVENT_KEY$3}`;\nconst EVENT_HIDE_PREVENTED = `hidePrevented${EVENT_KEY$3}`;\nconst EVENT_HIDDEN$3 = `hidden${EVENT_KEY$3}`;\nconst EVENT_RESIZE = `resize${EVENT_KEY$3}`;\nconst EVENT_CLICK_DATA_API$1 = `click${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst EVENT_KEYDOWN_DISMISS = `keydown.dismiss${EVENT_KEY$3}`;\nconst SELECTOR_DATA_TOGGLE$1 = '[data-bs-toggle=\"offcanvas\"]';\nconst Default$5 = {\n  backdrop: true,\n  keyboard: true,\n  scroll: false\n};\nconst DefaultType$5 = {\n  backdrop: '(boolean|string)',\n  keyboard: 'boolean',\n  scroll: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Offcanvas extends BaseComponent {\n  constructor(element, config) {\n    super(element, config);\n    this._isShown = false;\n    this._backdrop = this._initializeBackDrop();\n    this._focustrap = this._initializeFocusTrap();\n    this._addEventListeners();\n  }\n\n  // Getters\n  static get Default() {\n    return Default$5;\n  }\n  static get DefaultType() {\n    return DefaultType$5;\n  }\n  static get NAME() {\n    return NAME$6;\n  }\n\n  // Public\n  toggle(relatedTarget) {\n    return this._isShown ? this.hide() : this.show(relatedTarget);\n  }\n  show(relatedTarget) {\n    if (this._isShown) {\n      return;\n    }\n    const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$3, {\n      relatedTarget\n    });\n    if (showEvent.defaultPrevented) {\n      return;\n    }\n    this._isShown = true;\n    this._backdrop.show();\n    if (!this._config.scroll) {\n      new ScrollBarHelper().hide();\n    }\n    this._element.setAttribute('aria-modal', true);\n    this._element.setAttribute('role', 'dialog');\n    this._element.classList.add(CLASS_NAME_SHOWING$1);\n    const completeCallBack = () => {\n      if (!this._config.scroll || this._config.backdrop) {\n        this._focustrap.activate();\n      }\n      this._element.classList.add(CLASS_NAME_SHOW$3);\n      this._element.classList.remove(CLASS_NAME_SHOWING$1);\n      EventHandler.trigger(this._element, EVENT_SHOWN$3, {\n        relatedTarget\n      });\n    };\n    this._queueCallback(completeCallBack, this._element, true);\n  }\n  hide() {\n    if (!this._isShown) {\n      return;\n    }\n    const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$3);\n    if (hideEvent.defaultPrevented) {\n      return;\n    }\n    this._focustrap.deactivate();\n    this._element.blur();\n    this._isShown = false;\n    this._element.classList.add(CLASS_NAME_HIDING);\n    this._backdrop.hide();\n    const completeCallback = () => {\n      this._element.classList.remove(CLASS_NAME_SHOW$3, CLASS_NAME_HIDING);\n      this._element.removeAttribute('aria-modal');\n      this._element.removeAttribute('role');\n      if (!this._config.scroll) {\n        new ScrollBarHelper().reset();\n      }\n      EventHandler.trigger(this._element, EVENT_HIDDEN$3);\n    };\n    this._queueCallback(completeCallback, this._element, true);\n  }\n  dispose() {\n    this._backdrop.dispose();\n    this._focustrap.deactivate();\n    super.dispose();\n  }\n\n  // Private\n  _initializeBackDrop() {\n    const clickCallback = () => {\n      if (this._config.backdrop === 'static') {\n        EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n        return;\n      }\n      this.hide();\n    };\n\n    // 'static' option will be translated to true, and booleans will keep their value\n    const isVisible = Boolean(this._config.backdrop);\n    return new Backdrop({\n      className: CLASS_NAME_BACKDROP,\n      isVisible,\n      isAnimated: true,\n      rootElement: this._element.parentNode,\n      clickCallback: isVisible ? clickCallback : null\n    });\n  }\n  _initializeFocusTrap() {\n    return new FocusTrap({\n      trapElement: this._element\n    });\n  }\n  _addEventListeners() {\n    EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS, event => {\n      if (event.key !== ESCAPE_KEY) {\n        return;\n      }\n      if (this._config.keyboard) {\n        this.hide();\n        return;\n      }\n      EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n    });\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = Offcanvas.getOrCreateInstance(this, config);\n      if (typeof config !== 'string') {\n        return;\n      }\n      if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n        throw new TypeError(`No method named \"${config}\"`);\n      }\n      data[config](this);\n    });\n  }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$1, SELECTOR_DATA_TOGGLE$1, function (event) {\n  const target = SelectorEngine.getElementFromSelector(this);\n  if (['A', 'AREA'].includes(this.tagName)) {\n    event.preventDefault();\n  }\n  if (isDisabled(this)) {\n    return;\n  }\n  EventHandler.one(target, EVENT_HIDDEN$3, () => {\n    // focus on trigger when it is closed\n    if (isVisible(this)) {\n      this.focus();\n    }\n  });\n\n  // avoid conflict when clicking a toggler of an offcanvas, while another is open\n  const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR);\n  if (alreadyOpen && alreadyOpen !== target) {\n    Offcanvas.getInstance(alreadyOpen).hide();\n  }\n  const data = Offcanvas.getOrCreateInstance(target);\n  data.toggle(this);\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$2, () => {\n  for (const selector of SelectorEngine.find(OPEN_SELECTOR)) {\n    Offcanvas.getOrCreateInstance(selector).show();\n  }\n});\nEventHandler.on(window, EVENT_RESIZE, () => {\n  for (const element of SelectorEngine.find('[aria-modal][class*=show][class*=offcanvas-]')) {\n    if (getComputedStyle(element).position !== 'fixed') {\n      Offcanvas.getOrCreateInstance(element).hide();\n    }\n  }\n});\nenableDismissTrigger(Offcanvas);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Offcanvas);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/sanitizer.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n// js-docs-start allow-list\nconst ARIA_ATTRIBUTE_PATTERN = /^aria-[\\w-]*$/i;\nconst DefaultAllowlist = {\n  // Global attributes allowed on any supplied element below.\n  '*': ['class', 'dir', 'id', 'lang', 'role', ARIA_ATTRIBUTE_PATTERN],\n  a: ['target', 'href', 'title', 'rel'],\n  area: [],\n  b: [],\n  br: [],\n  col: [],\n  code: [],\n  div: [],\n  em: [],\n  hr: [],\n  h1: [],\n  h2: [],\n  h3: [],\n  h4: [],\n  h5: [],\n  h6: [],\n  i: [],\n  img: ['src', 'srcset', 'alt', 'title', 'width', 'height'],\n  li: [],\n  ol: [],\n  p: [],\n  pre: [],\n  s: [],\n  small: [],\n  span: [],\n  sub: [],\n  sup: [],\n  strong: [],\n  u: [],\n  ul: []\n};\n// js-docs-end allow-list\n\nconst uriAttributes = new Set(['background', 'cite', 'href', 'itemtype', 'longdesc', 'poster', 'src', 'xlink:href']);\n\n/**\n * A pattern that recognizes URLs that are safe wrt. XSS in URL navigation\n * contexts.\n *\n * Shout-out to Angular https://github.com/angular/angular/blob/15.2.8/packages/core/src/sanitization/url_sanitizer.ts#L38\n */\n// eslint-disable-next-line unicorn/better-regex\nconst SAFE_URL_PATTERN = /^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i;\nconst allowedAttribute = (attribute, allowedAttributeList) => {\n  const attributeName = attribute.nodeName.toLowerCase();\n  if (allowedAttributeList.includes(attributeName)) {\n    if (uriAttributes.has(attributeName)) {\n      return Boolean(SAFE_URL_PATTERN.test(attribute.nodeValue));\n    }\n    return true;\n  }\n\n  // Check if a regular expression validates the attribute.\n  return allowedAttributeList.filter(attributeRegex => attributeRegex instanceof RegExp).some(regex => regex.test(attributeName));\n};\nfunction sanitizeHtml(unsafeHtml, allowList, sanitizeFunction) {\n  if (!unsafeHtml.length) {\n    return unsafeHtml;\n  }\n  if (sanitizeFunction && typeof sanitizeFunction === 'function') {\n    return sanitizeFunction(unsafeHtml);\n  }\n  const domParser = new window.DOMParser();\n  const createdDocument = domParser.parseFromString(unsafeHtml, 'text/html');\n  const elements = [].concat(...createdDocument.body.querySelectorAll('*'));\n  for (const element of elements) {\n    const elementName = element.nodeName.toLowerCase();\n    if (!Object.keys(allowList).includes(elementName)) {\n      element.remove();\n      continue;\n    }\n    const attributeList = [].concat(...element.attributes);\n    const allowedAttributes = [].concat(allowList['*'] || [], allowList[elementName] || []);\n    for (const attribute of attributeList) {\n      if (!allowedAttribute(attribute, allowedAttributes)) {\n        element.removeAttribute(attribute.nodeName);\n      }\n    }\n  }\n  return createdDocument.body.innerHTML;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/template-factory.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$5 = 'TemplateFactory';\nconst Default$4 = {\n  allowList: DefaultAllowlist,\n  content: {},\n  // { selector : text ,  selector2 : text2 , }\n  extraClass: '',\n  html: false,\n  sanitize: true,\n  sanitizeFn: null,\n  template: '<div></div>'\n};\nconst DefaultType$4 = {\n  allowList: 'object',\n  content: 'object',\n  extraClass: '(string|function)',\n  html: 'boolean',\n  sanitize: 'boolean',\n  sanitizeFn: '(null|function)',\n  template: 'string'\n};\nconst DefaultContentType = {\n  entry: '(string|element|function|null)',\n  selector: '(string|element)'\n};\n\n/**\n * Class definition\n */\n\nclass TemplateFactory extends Config {\n  constructor(config) {\n    super();\n    this._config = this._getConfig(config);\n  }\n\n  // Getters\n  static get Default() {\n    return Default$4;\n  }\n  static get DefaultType() {\n    return DefaultType$4;\n  }\n  static get NAME() {\n    return NAME$5;\n  }\n\n  // Public\n  getContent() {\n    return Object.values(this._config.content).map(config => this._resolvePossibleFunction(config)).filter(Boolean);\n  }\n  hasContent() {\n    return this.getContent().length > 0;\n  }\n  changeContent(content) {\n    this._checkContent(content);\n    this._config.content = {\n      ...this._config.content,\n      ...content\n    };\n    return this;\n  }\n  toHtml() {\n    const templateWrapper = document.createElement('div');\n    templateWrapper.innerHTML = this._maybeSanitize(this._config.template);\n    for (const [selector, text] of Object.entries(this._config.content)) {\n      this._setContent(templateWrapper, text, selector);\n    }\n    const template = templateWrapper.children[0];\n    const extraClass = this._resolvePossibleFunction(this._config.extraClass);\n    if (extraClass) {\n      template.classList.add(...extraClass.split(' '));\n    }\n    return template;\n  }\n\n  // Private\n  _typeCheckConfig(config) {\n    super._typeCheckConfig(config);\n    this._checkContent(config.content);\n  }\n  _checkContent(arg) {\n    for (const [selector, content] of Object.entries(arg)) {\n      super._typeCheckConfig({\n        selector,\n        entry: content\n      }, DefaultContentType);\n    }\n  }\n  _setContent(template, content, selector) {\n    const templateElement = SelectorEngine.findOne(selector, template);\n    if (!templateElement) {\n      return;\n    }\n    content = this._resolvePossibleFunction(content);\n    if (!content) {\n      templateElement.remove();\n      return;\n    }\n    if (isElement(content)) {\n      this._putElementInTemplate(getElement(content), templateElement);\n      return;\n    }\n    if (this._config.html) {\n      templateElement.innerHTML = this._maybeSanitize(content);\n      return;\n    }\n    templateElement.textContent = content;\n  }\n  _maybeSanitize(arg) {\n    return this._config.sanitize ? sanitizeHtml(arg, this._config.allowList, this._config.sanitizeFn) : arg;\n  }\n  _resolvePossibleFunction(arg) {\n    return execute(arg, [this]);\n  }\n  _putElementInTemplate(element, templateElement) {\n    if (this._config.html) {\n      templateElement.innerHTML = '';\n      templateElement.append(element);\n      return;\n    }\n    templateElement.textContent = element.textContent;\n  }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap tooltip.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$4 = 'tooltip';\nconst DISALLOWED_ATTRIBUTES = new Set(['sanitize', 'allowList', 'sanitizeFn']);\nconst CLASS_NAME_FADE$2 = 'fade';\nconst CLASS_NAME_MODAL = 'modal';\nconst CLASS_NAME_SHOW$2 = 'show';\nconst SELECTOR_TOOLTIP_INNER = '.tooltip-inner';\nconst SELECTOR_MODAL = `.${CLASS_NAME_MODAL}`;\nconst EVENT_MODAL_HIDE = 'hide.bs.modal';\nconst TRIGGER_HOVER = 'hover';\nconst TRIGGER_FOCUS = 'focus';\nconst TRIGGER_CLICK = 'click';\nconst TRIGGER_MANUAL = 'manual';\nconst EVENT_HIDE$2 = 'hide';\nconst EVENT_HIDDEN$2 = 'hidden';\nconst EVENT_SHOW$2 = 'show';\nconst EVENT_SHOWN$2 = 'shown';\nconst EVENT_INSERTED = 'inserted';\nconst EVENT_CLICK$1 = 'click';\nconst EVENT_FOCUSIN$1 = 'focusin';\nconst EVENT_FOCUSOUT$1 = 'focusout';\nconst EVENT_MOUSEENTER = 'mouseenter';\nconst EVENT_MOUSELEAVE = 'mouseleave';\nconst AttachmentMap = {\n  AUTO: 'auto',\n  TOP: 'top',\n  RIGHT: isRTL() ? 'left' : 'right',\n  BOTTOM: 'bottom',\n  LEFT: isRTL() ? 'right' : 'left'\n};\nconst Default$3 = {\n  allowList: DefaultAllowlist,\n  animation: true,\n  boundary: 'clippingParents',\n  container: false,\n  customClass: '',\n  delay: 0,\n  fallbackPlacements: ['top', 'right', 'bottom', 'left'],\n  html: false,\n  offset: [0, 6],\n  placement: 'top',\n  popperConfig: null,\n  sanitize: true,\n  sanitizeFn: null,\n  selector: false,\n  template: '<div class=\"tooltip\" role=\"tooltip\">' + '<div class=\"tooltip-arrow\"></div>' + '<div class=\"tooltip-inner\"></div>' + '</div>',\n  title: '',\n  trigger: 'hover focus'\n};\nconst DefaultType$3 = {\n  allowList: 'object',\n  animation: 'boolean',\n  boundary: '(string|element)',\n  container: '(string|element|boolean)',\n  customClass: '(string|function)',\n  delay: '(number|object)',\n  fallbackPlacements: 'array',\n  html: 'boolean',\n  offset: '(array|string|function)',\n  placement: '(string|function)',\n  popperConfig: '(null|object|function)',\n  sanitize: 'boolean',\n  sanitizeFn: '(null|function)',\n  selector: '(string|boolean)',\n  template: 'string',\n  title: '(string|element|function)',\n  trigger: 'string'\n};\n\n/**\n * Class definition\n */\n\nclass Tooltip extends BaseComponent {\n  constructor(element, config) {\n    if (typeof Popper === 'undefined') {\n      throw new TypeError('Bootstrap\\'s tooltips require Popper (https://popper.js.org)');\n    }\n    super(element, config);\n\n    // Private\n    this._isEnabled = true;\n    this._timeout = 0;\n    this._isHovered = null;\n    this._activeTrigger = {};\n    this._popper = null;\n    this._templateFactory = null;\n    this._newContent = null;\n\n    // Protected\n    this.tip = null;\n    this._setListeners();\n    if (!this._config.selector) {\n      this._fixTitle();\n    }\n  }\n\n  // Getters\n  static get Default() {\n    return Default$3;\n  }\n  static get DefaultType() {\n    return DefaultType$3;\n  }\n  static get NAME() {\n    return NAME$4;\n  }\n\n  // Public\n  enable() {\n    this._isEnabled = true;\n  }\n  disable() {\n    this._isEnabled = false;\n  }\n  toggleEnabled() {\n    this._isEnabled = !this._isEnabled;\n  }\n  toggle() {\n    if (!this._isEnabled) {\n      return;\n    }\n    this._activeTrigger.click = !this._activeTrigger.click;\n    if (this._isShown()) {\n      this._leave();\n      return;\n    }\n    this._enter();\n  }\n  dispose() {\n    clearTimeout(this._timeout);\n    EventHandler.off(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n    if (this._element.getAttribute('data-bs-original-title')) {\n      this._element.setAttribute('title', this._element.getAttribute('data-bs-original-title'));\n    }\n    this._disposePopper();\n    super.dispose();\n  }\n  show() {\n    if (this._element.style.display === 'none') {\n      throw new Error('Please use show on visible elements');\n    }\n    if (!(this._isWithContent() && this._isEnabled)) {\n      return;\n    }\n    const showEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOW$2));\n    const shadowRoot = findShadowRoot(this._element);\n    const isInTheDom = (shadowRoot || this._element.ownerDocument.documentElement).contains(this._element);\n    if (showEvent.defaultPrevented || !isInTheDom) {\n      return;\n    }\n\n    // TODO: v6 remove this or make it optional\n    this._disposePopper();\n    const tip = this._getTipElement();\n    this._element.setAttribute('aria-describedby', tip.getAttribute('id'));\n    const {\n      container\n    } = this._config;\n    if (!this._element.ownerDocument.documentElement.contains(this.tip)) {\n      container.append(tip);\n      EventHandler.trigger(this._element, this.constructor.eventName(EVENT_INSERTED));\n    }\n    this._popper = this._createPopper(tip);\n    tip.classList.add(CLASS_NAME_SHOW$2);\n\n    // If this is a touch-enabled device we add extra\n    // empty mouseover listeners to the body's immediate children;\n    // only needed because of broken event delegation on iOS\n    // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n    if ('ontouchstart' in document.documentElement) {\n      for (const element of [].concat(...document.body.children)) {\n        EventHandler.on(element, 'mouseover', noop);\n      }\n    }\n    const complete = () => {\n      EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOWN$2));\n      if (this._isHovered === false) {\n        this._leave();\n      }\n      this._isHovered = false;\n    };\n    this._queueCallback(complete, this.tip, this._isAnimated());\n  }\n  hide() {\n    if (!this._isShown()) {\n      return;\n    }\n    const hideEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDE$2));\n    if (hideEvent.defaultPrevented) {\n      return;\n    }\n    const tip = this._getTipElement();\n    tip.classList.remove(CLASS_NAME_SHOW$2);\n\n    // If this is a touch-enabled device we remove the extra\n    // empty mouseover listeners we added for iOS support\n    if ('ontouchstart' in document.documentElement) {\n      for (const element of [].concat(...document.body.children)) {\n        EventHandler.off(element, 'mouseover', noop);\n      }\n    }\n    this._activeTrigger[TRIGGER_CLICK] = false;\n    this._activeTrigger[TRIGGER_FOCUS] = false;\n    this._activeTrigger[TRIGGER_HOVER] = false;\n    this._isHovered = null; // it is a trick to support manual triggering\n\n    const complete = () => {\n      if (this._isWithActiveTrigger()) {\n        return;\n      }\n      if (!this._isHovered) {\n        this._disposePopper();\n      }\n      this._element.removeAttribute('aria-describedby');\n      EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDDEN$2));\n    };\n    this._queueCallback(complete, this.tip, this._isAnimated());\n  }\n  update() {\n    if (this._popper) {\n      this._popper.update();\n    }\n  }\n\n  // Protected\n  _isWithContent() {\n    return Boolean(this._getTitle());\n  }\n  _getTipElement() {\n    if (!this.tip) {\n      this.tip = this._createTipElement(this._newContent || this._getContentForTemplate());\n    }\n    return this.tip;\n  }\n  _createTipElement(content) {\n    const tip = this._getTemplateFactory(content).toHtml();\n\n    // TODO: remove this check in v6\n    if (!tip) {\n      return null;\n    }\n    tip.classList.remove(CLASS_NAME_FADE$2, CLASS_NAME_SHOW$2);\n    // TODO: v6 the following can be achieved with CSS only\n    tip.classList.add(`bs-${this.constructor.NAME}-auto`);\n    const tipId = getUID(this.constructor.NAME).toString();\n    tip.setAttribute('id', tipId);\n    if (this._isAnimated()) {\n      tip.classList.add(CLASS_NAME_FADE$2);\n    }\n    return tip;\n  }\n  setContent(content) {\n    this._newContent = content;\n    if (this._isShown()) {\n      this._disposePopper();\n      this.show();\n    }\n  }\n  _getTemplateFactory(content) {\n    if (this._templateFactory) {\n      this._templateFactory.changeContent(content);\n    } else {\n      this._templateFactory = new TemplateFactory({\n        ...this._config,\n        // the `content` var has to be after `this._config`\n        // to override config.content in case of popover\n        content,\n        extraClass: this._resolvePossibleFunction(this._config.customClass)\n      });\n    }\n    return this._templateFactory;\n  }\n  _getContentForTemplate() {\n    return {\n      [SELECTOR_TOOLTIP_INNER]: this._getTitle()\n    };\n  }\n  _getTitle() {\n    return this._resolvePossibleFunction(this._config.title) || this._element.getAttribute('data-bs-original-title');\n  }\n\n  // Private\n  _initializeOnDelegatedTarget(event) {\n    return this.constructor.getOrCreateInstance(event.delegateTarget, this._getDelegateConfig());\n  }\n  _isAnimated() {\n    return this._config.animation || this.tip && this.tip.classList.contains(CLASS_NAME_FADE$2);\n  }\n  _isShown() {\n    return this.tip && this.tip.classList.contains(CLASS_NAME_SHOW$2);\n  }\n  _createPopper(tip) {\n    const placement = execute(this._config.placement, [this, tip, this._element]);\n    const attachment = AttachmentMap[placement.toUpperCase()];\n    return Popper.createPopper(this._element, tip, this._getPopperConfig(attachment));\n  }\n  _getOffset() {\n    const {\n      offset\n    } = this._config;\n    if (typeof offset === 'string') {\n      return offset.split(',').map(value => Number.parseInt(value, 10));\n    }\n    if (typeof offset === 'function') {\n      return popperData => offset(popperData, this._element);\n    }\n    return offset;\n  }\n  _resolvePossibleFunction(arg) {\n    return execute(arg, [this._element]);\n  }\n  _getPopperConfig(attachment) {\n    const defaultBsPopperConfig = {\n      placement: attachment,\n      modifiers: [{\n        name: 'flip',\n        options: {\n          fallbackPlacements: this._config.fallbackPlacements\n        }\n      }, {\n        name: 'offset',\n        options: {\n          offset: this._getOffset()\n        }\n      }, {\n        name: 'preventOverflow',\n        options: {\n          boundary: this._config.boundary\n        }\n      }, {\n        name: 'arrow',\n        options: {\n          element: `.${this.constructor.NAME}-arrow`\n        }\n      }, {\n        name: 'preSetPlacement',\n        enabled: true,\n        phase: 'beforeMain',\n        fn: data => {\n          // Pre-set Popper's placement attribute in order to read the arrow sizes properly.\n          // Otherwise, Popper mixes up the width and height dimensions since the initial arrow style is for top placement\n          this._getTipElement().setAttribute('data-popper-placement', data.state.placement);\n        }\n      }]\n    };\n    return {\n      ...defaultBsPopperConfig,\n      ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n    };\n  }\n  _setListeners() {\n    const triggers = this._config.trigger.split(' ');\n    for (const trigger of triggers) {\n      if (trigger === 'click') {\n        EventHandler.on(this._element, this.constructor.eventName(EVENT_CLICK$1), this._config.selector, event => {\n          const context = this._initializeOnDelegatedTarget(event);\n          context.toggle();\n        });\n      } else if (trigger !== TRIGGER_MANUAL) {\n        const eventIn = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSEENTER) : this.constructor.eventName(EVENT_FOCUSIN$1);\n        const eventOut = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSELEAVE) : this.constructor.eventName(EVENT_FOCUSOUT$1);\n        EventHandler.on(this._element, eventIn, this._config.selector, event => {\n          const context = this._initializeOnDelegatedTarget(event);\n          context._activeTrigger[event.type === 'focusin' ? TRIGGER_FOCUS : TRIGGER_HOVER] = true;\n          context._enter();\n        });\n        EventHandler.on(this._element, eventOut, this._config.selector, event => {\n          const context = this._initializeOnDelegatedTarget(event);\n          context._activeTrigger[event.type === 'focusout' ? TRIGGER_FOCUS : TRIGGER_HOVER] = context._element.contains(event.relatedTarget);\n          context._leave();\n        });\n      }\n    }\n    this._hideModalHandler = () => {\n      if (this._element) {\n        this.hide();\n      }\n    };\n    EventHandler.on(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n  }\n  _fixTitle() {\n    const title = this._element.getAttribute('title');\n    if (!title) {\n      return;\n    }\n    if (!this._element.getAttribute('aria-label') && !this._element.textContent.trim()) {\n      this._element.setAttribute('aria-label', title);\n    }\n    this._element.setAttribute('data-bs-original-title', title); // DO NOT USE IT. Is only for backwards compatibility\n    this._element.removeAttribute('title');\n  }\n  _enter() {\n    if (this._isShown() || this._isHovered) {\n      this._isHovered = true;\n      return;\n    }\n    this._isHovered = true;\n    this._setTimeout(() => {\n      if (this._isHovered) {\n        this.show();\n      }\n    }, this._config.delay.show);\n  }\n  _leave() {\n    if (this._isWithActiveTrigger()) {\n      return;\n    }\n    this._isHovered = false;\n    this._setTimeout(() => {\n      if (!this._isHovered) {\n        this.hide();\n      }\n    }, this._config.delay.hide);\n  }\n  _setTimeout(handler, timeout) {\n    clearTimeout(this._timeout);\n    this._timeout = setTimeout(handler, timeout);\n  }\n  _isWithActiveTrigger() {\n    return Object.values(this._activeTrigger).includes(true);\n  }\n  _getConfig(config) {\n    const dataAttributes = Manipulator.getDataAttributes(this._element);\n    for (const dataAttribute of Object.keys(dataAttributes)) {\n      if (DISALLOWED_ATTRIBUTES.has(dataAttribute)) {\n        delete dataAttributes[dataAttribute];\n      }\n    }\n    config = {\n      ...dataAttributes,\n      ...(typeof config === 'object' && config ? config : {})\n    };\n    config = this._mergeConfigObj(config);\n    config = this._configAfterMerge(config);\n    this._typeCheckConfig(config);\n    return config;\n  }\n  _configAfterMerge(config) {\n    config.container = config.container === false ? document.body : getElement(config.container);\n    if (typeof config.delay === 'number') {\n      config.delay = {\n        show: config.delay,\n        hide: config.delay\n      };\n    }\n    if (typeof config.title === 'number') {\n      config.title = config.title.toString();\n    }\n    if (typeof config.content === 'number') {\n      config.content = config.content.toString();\n    }\n    return config;\n  }\n  _getDelegateConfig() {\n    const config = {};\n    for (const [key, value] of Object.entries(this._config)) {\n      if (this.constructor.Default[key] !== value) {\n        config[key] = value;\n      }\n    }\n    config.selector = false;\n    config.trigger = 'manual';\n\n    // In the future can be replaced with:\n    // const keysWithDifferentValues = Object.entries(this._config).filter(entry => this.constructor.Default[entry[0]] !== this._config[entry[0]])\n    // `Object.fromEntries(keysWithDifferentValues)`\n    return config;\n  }\n  _disposePopper() {\n    if (this._popper) {\n      this._popper.destroy();\n      this._popper = null;\n    }\n    if (this.tip) {\n      this.tip.remove();\n      this.tip = null;\n    }\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = Tooltip.getOrCreateInstance(this, config);\n      if (typeof config !== 'string') {\n        return;\n      }\n      if (typeof data[config] === 'undefined') {\n        throw new TypeError(`No method named \"${config}\"`);\n      }\n      data[config]();\n    });\n  }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Tooltip);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap popover.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$3 = 'popover';\nconst SELECTOR_TITLE = '.popover-header';\nconst SELECTOR_CONTENT = '.popover-body';\nconst Default$2 = {\n  ...Tooltip.Default,\n  content: '',\n  offset: [0, 8],\n  placement: 'right',\n  template: '<div class=\"popover\" role=\"tooltip\">' + '<div class=\"popover-arrow\"></div>' + '<h3 class=\"popover-header\"></h3>' + '<div class=\"popover-body\"></div>' + '</div>',\n  trigger: 'click'\n};\nconst DefaultType$2 = {\n  ...Tooltip.DefaultType,\n  content: '(null|string|element|function)'\n};\n\n/**\n * Class definition\n */\n\nclass Popover extends Tooltip {\n  // Getters\n  static get Default() {\n    return Default$2;\n  }\n  static get DefaultType() {\n    return DefaultType$2;\n  }\n  static get NAME() {\n    return NAME$3;\n  }\n\n  // Overrides\n  _isWithContent() {\n    return this._getTitle() || this._getContent();\n  }\n\n  // Private\n  _getContentForTemplate() {\n    return {\n      [SELECTOR_TITLE]: this._getTitle(),\n      [SELECTOR_CONTENT]: this._getContent()\n    };\n  }\n  _getContent() {\n    return this._resolvePossibleFunction(this._config.content);\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = Popover.getOrCreateInstance(this, config);\n      if (typeof config !== 'string') {\n        return;\n      }\n      if (typeof data[config] === 'undefined') {\n        throw new TypeError(`No method named \"${config}\"`);\n      }\n      data[config]();\n    });\n  }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Popover);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap scrollspy.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$2 = 'scrollspy';\nconst DATA_KEY$2 = 'bs.scrollspy';\nconst EVENT_KEY$2 = `.${DATA_KEY$2}`;\nconst DATA_API_KEY = '.data-api';\nconst EVENT_ACTIVATE = `activate${EVENT_KEY$2}`;\nconst EVENT_CLICK = `click${EVENT_KEY$2}`;\nconst EVENT_LOAD_DATA_API$1 = `load${EVENT_KEY$2}${DATA_API_KEY}`;\nconst CLASS_NAME_DROPDOWN_ITEM = 'dropdown-item';\nconst CLASS_NAME_ACTIVE$1 = 'active';\nconst SELECTOR_DATA_SPY = '[data-bs-spy=\"scroll\"]';\nconst SELECTOR_TARGET_LINKS = '[href]';\nconst SELECTOR_NAV_LIST_GROUP = '.nav, .list-group';\nconst SELECTOR_NAV_LINKS = '.nav-link';\nconst SELECTOR_NAV_ITEMS = '.nav-item';\nconst SELECTOR_LIST_ITEMS = '.list-group-item';\nconst SELECTOR_LINK_ITEMS = `${SELECTOR_NAV_LINKS}, ${SELECTOR_NAV_ITEMS} > ${SELECTOR_NAV_LINKS}, ${SELECTOR_LIST_ITEMS}`;\nconst SELECTOR_DROPDOWN = '.dropdown';\nconst SELECTOR_DROPDOWN_TOGGLE$1 = '.dropdown-toggle';\nconst Default$1 = {\n  offset: null,\n  // TODO: v6 @deprecated, keep it for backwards compatibility reasons\n  rootMargin: '0px 0px -25%',\n  smoothScroll: false,\n  target: null,\n  threshold: [0.1, 0.5, 1]\n};\nconst DefaultType$1 = {\n  offset: '(number|null)',\n  // TODO v6 @deprecated, keep it for backwards compatibility reasons\n  rootMargin: 'string',\n  smoothScroll: 'boolean',\n  target: 'element',\n  threshold: 'array'\n};\n\n/**\n * Class definition\n */\n\nclass ScrollSpy extends BaseComponent {\n  constructor(element, config) {\n    super(element, config);\n\n    // this._element is the observablesContainer and config.target the menu links wrapper\n    this._targetLinks = new Map();\n    this._observableSections = new Map();\n    this._rootElement = getComputedStyle(this._element).overflowY === 'visible' ? null : this._element;\n    this._activeTarget = null;\n    this._observer = null;\n    this._previousScrollData = {\n      visibleEntryTop: 0,\n      parentScrollTop: 0\n    };\n    this.refresh(); // initialize\n  }\n\n  // Getters\n  static get Default() {\n    return Default$1;\n  }\n  static get DefaultType() {\n    return DefaultType$1;\n  }\n  static get NAME() {\n    return NAME$2;\n  }\n\n  // Public\n  refresh() {\n    this._initializeTargetsAndObservables();\n    this._maybeEnableSmoothScroll();\n    if (this._observer) {\n      this._observer.disconnect();\n    } else {\n      this._observer = this._getNewObserver();\n    }\n    for (const section of this._observableSections.values()) {\n      this._observer.observe(section);\n    }\n  }\n  dispose() {\n    this._observer.disconnect();\n    super.dispose();\n  }\n\n  // Private\n  _configAfterMerge(config) {\n    // TODO: on v6 target should be given explicitly & remove the {target: 'ss-target'} case\n    config.target = getElement(config.target) || document.body;\n\n    // TODO: v6 Only for backwards compatibility reasons. Use rootMargin only\n    config.rootMargin = config.offset ? `${config.offset}px 0px -30%` : config.rootMargin;\n    if (typeof config.threshold === 'string') {\n      config.threshold = config.threshold.split(',').map(value => Number.parseFloat(value));\n    }\n    return config;\n  }\n  _maybeEnableSmoothScroll() {\n    if (!this._config.smoothScroll) {\n      return;\n    }\n\n    // unregister any previous listeners\n    EventHandler.off(this._config.target, EVENT_CLICK);\n    EventHandler.on(this._config.target, EVENT_CLICK, SELECTOR_TARGET_LINKS, event => {\n      const observableSection = this._observableSections.get(event.target.hash);\n      if (observableSection) {\n        event.preventDefault();\n        const root = this._rootElement || window;\n        const height = observableSection.offsetTop - this._element.offsetTop;\n        if (root.scrollTo) {\n          root.scrollTo({\n            top: height,\n            behavior: 'smooth'\n          });\n          return;\n        }\n\n        // Chrome 60 doesn't support `scrollTo`\n        root.scrollTop = height;\n      }\n    });\n  }\n  _getNewObserver() {\n    const options = {\n      root: this._rootElement,\n      threshold: this._config.threshold,\n      rootMargin: this._config.rootMargin\n    };\n    return new IntersectionObserver(entries => this._observerCallback(entries), options);\n  }\n\n  // The logic of selection\n  _observerCallback(entries) {\n    const targetElement = entry => this._targetLinks.get(`#${entry.target.id}`);\n    const activate = entry => {\n      this._previousScrollData.visibleEntryTop = entry.target.offsetTop;\n      this._process(targetElement(entry));\n    };\n    const parentScrollTop = (this._rootElement || document.documentElement).scrollTop;\n    const userScrollsDown = parentScrollTop >= this._previousScrollData.parentScrollTop;\n    this._previousScrollData.parentScrollTop = parentScrollTop;\n    for (const entry of entries) {\n      if (!entry.isIntersecting) {\n        this._activeTarget = null;\n        this._clearActiveClass(targetElement(entry));\n        continue;\n      }\n      const entryIsLowerThanPrevious = entry.target.offsetTop >= this._previousScrollData.visibleEntryTop;\n      // if we are scrolling down, pick the bigger offsetTop\n      if (userScrollsDown && entryIsLowerThanPrevious) {\n        activate(entry);\n        // if parent isn't scrolled, let's keep the first visible item, breaking the iteration\n        if (!parentScrollTop) {\n          return;\n        }\n        continue;\n      }\n\n      // if we are scrolling up, pick the smallest offsetTop\n      if (!userScrollsDown && !entryIsLowerThanPrevious) {\n        activate(entry);\n      }\n    }\n  }\n  _initializeTargetsAndObservables() {\n    this._targetLinks = new Map();\n    this._observableSections = new Map();\n    const targetLinks = SelectorEngine.find(SELECTOR_TARGET_LINKS, this._config.target);\n    for (const anchor of targetLinks) {\n      // ensure that the anchor has an id and is not disabled\n      if (!anchor.hash || isDisabled(anchor)) {\n        continue;\n      }\n      const observableSection = SelectorEngine.findOne(decodeURI(anchor.hash), this._element);\n\n      // ensure that the observableSection exists & is visible\n      if (isVisible(observableSection)) {\n        this._targetLinks.set(decodeURI(anchor.hash), anchor);\n        this._observableSections.set(anchor.hash, observableSection);\n      }\n    }\n  }\n  _process(target) {\n    if (this._activeTarget === target) {\n      return;\n    }\n    this._clearActiveClass(this._config.target);\n    this._activeTarget = target;\n    target.classList.add(CLASS_NAME_ACTIVE$1);\n    this._activateParents(target);\n    EventHandler.trigger(this._element, EVENT_ACTIVATE, {\n      relatedTarget: target\n    });\n  }\n  _activateParents(target) {\n    // Activate dropdown parents\n    if (target.classList.contains(CLASS_NAME_DROPDOWN_ITEM)) {\n      SelectorEngine.findOne(SELECTOR_DROPDOWN_TOGGLE$1, target.closest(SELECTOR_DROPDOWN)).classList.add(CLASS_NAME_ACTIVE$1);\n      return;\n    }\n    for (const listGroup of SelectorEngine.parents(target, SELECTOR_NAV_LIST_GROUP)) {\n      // Set triggered links parents as active\n      // With both <ul> and <nav> markup a parent is the previous sibling of any nav ancestor\n      for (const item of SelectorEngine.prev(listGroup, SELECTOR_LINK_ITEMS)) {\n        item.classList.add(CLASS_NAME_ACTIVE$1);\n      }\n    }\n  }\n  _clearActiveClass(parent) {\n    parent.classList.remove(CLASS_NAME_ACTIVE$1);\n    const activeNodes = SelectorEngine.find(`${SELECTOR_TARGET_LINKS}.${CLASS_NAME_ACTIVE$1}`, parent);\n    for (const node of activeNodes) {\n      node.classList.remove(CLASS_NAME_ACTIVE$1);\n    }\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = ScrollSpy.getOrCreateInstance(this, config);\n      if (typeof config !== 'string') {\n        return;\n      }\n      if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n        throw new TypeError(`No method named \"${config}\"`);\n      }\n      data[config]();\n    });\n  }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(window, EVENT_LOAD_DATA_API$1, () => {\n  for (const spy of SelectorEngine.find(SELECTOR_DATA_SPY)) {\n    ScrollSpy.getOrCreateInstance(spy);\n  }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(ScrollSpy);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap tab.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$1 = 'tab';\nconst DATA_KEY$1 = 'bs.tab';\nconst EVENT_KEY$1 = `.${DATA_KEY$1}`;\nconst EVENT_HIDE$1 = `hide${EVENT_KEY$1}`;\nconst EVENT_HIDDEN$1 = `hidden${EVENT_KEY$1}`;\nconst EVENT_SHOW$1 = `show${EVENT_KEY$1}`;\nconst EVENT_SHOWN$1 = `shown${EVENT_KEY$1}`;\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY$1}`;\nconst EVENT_KEYDOWN = `keydown${EVENT_KEY$1}`;\nconst EVENT_LOAD_DATA_API = `load${EVENT_KEY$1}`;\nconst ARROW_LEFT_KEY = 'ArrowLeft';\nconst ARROW_RIGHT_KEY = 'ArrowRight';\nconst ARROW_UP_KEY = 'ArrowUp';\nconst ARROW_DOWN_KEY = 'ArrowDown';\nconst HOME_KEY = 'Home';\nconst END_KEY = 'End';\nconst CLASS_NAME_ACTIVE = 'active';\nconst CLASS_NAME_FADE$1 = 'fade';\nconst CLASS_NAME_SHOW$1 = 'show';\nconst CLASS_DROPDOWN = 'dropdown';\nconst SELECTOR_DROPDOWN_TOGGLE = '.dropdown-toggle';\nconst SELECTOR_DROPDOWN_MENU = '.dropdown-menu';\nconst NOT_SELECTOR_DROPDOWN_TOGGLE = `:not(${SELECTOR_DROPDOWN_TOGGLE})`;\nconst SELECTOR_TAB_PANEL = '.list-group, .nav, [role=\"tablist\"]';\nconst SELECTOR_OUTER = '.nav-item, .list-group-item';\nconst SELECTOR_INNER = `.nav-link${NOT_SELECTOR_DROPDOWN_TOGGLE}, .list-group-item${NOT_SELECTOR_DROPDOWN_TOGGLE}, [role=\"tab\"]${NOT_SELECTOR_DROPDOWN_TOGGLE}`;\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"tab\"], [data-bs-toggle=\"pill\"], [data-bs-toggle=\"list\"]'; // TODO: could only be `tab` in v6\nconst SELECTOR_INNER_ELEM = `${SELECTOR_INNER}, ${SELECTOR_DATA_TOGGLE}`;\nconst SELECTOR_DATA_TOGGLE_ACTIVE = `.${CLASS_NAME_ACTIVE}[data-bs-toggle=\"tab\"], .${CLASS_NAME_ACTIVE}[data-bs-toggle=\"pill\"], .${CLASS_NAME_ACTIVE}[data-bs-toggle=\"list\"]`;\n\n/**\n * Class definition\n */\n\nclass Tab extends BaseComponent {\n  constructor(element) {\n    super(element);\n    this._parent = this._element.closest(SELECTOR_TAB_PANEL);\n    if (!this._parent) {\n      return;\n      // TODO: should throw exception in v6\n      // throw new TypeError(`${element.outerHTML} has not a valid parent ${SELECTOR_INNER_ELEM}`)\n    }\n\n    // Set up initial aria attributes\n    this._setInitialAttributes(this._parent, this._getChildren());\n    EventHandler.on(this._element, EVENT_KEYDOWN, event => this._keydown(event));\n  }\n\n  // Getters\n  static get NAME() {\n    return NAME$1;\n  }\n\n  // Public\n  show() {\n    // Shows this elem and deactivate the active sibling if exists\n    const innerElem = this._element;\n    if (this._elemIsActive(innerElem)) {\n      return;\n    }\n\n    // Search for active tab on same parent to deactivate it\n    const active = this._getActiveElem();\n    const hideEvent = active ? EventHandler.trigger(active, EVENT_HIDE$1, {\n      relatedTarget: innerElem\n    }) : null;\n    const showEvent = EventHandler.trigger(innerElem, EVENT_SHOW$1, {\n      relatedTarget: active\n    });\n    if (showEvent.defaultPrevented || hideEvent && hideEvent.defaultPrevented) {\n      return;\n    }\n    this._deactivate(active, innerElem);\n    this._activate(innerElem, active);\n  }\n\n  // Private\n  _activate(element, relatedElem) {\n    if (!element) {\n      return;\n    }\n    element.classList.add(CLASS_NAME_ACTIVE);\n    this._activate(SelectorEngine.getElementFromSelector(element)); // Search and activate/show the proper section\n\n    const complete = () => {\n      if (element.getAttribute('role') !== 'tab') {\n        element.classList.add(CLASS_NAME_SHOW$1);\n        return;\n      }\n      element.removeAttribute('tabindex');\n      element.setAttribute('aria-selected', true);\n      this._toggleDropDown(element, true);\n      EventHandler.trigger(element, EVENT_SHOWN$1, {\n        relatedTarget: relatedElem\n      });\n    };\n    this._queueCallback(complete, element, element.classList.contains(CLASS_NAME_FADE$1));\n  }\n  _deactivate(element, relatedElem) {\n    if (!element) {\n      return;\n    }\n    element.classList.remove(CLASS_NAME_ACTIVE);\n    element.blur();\n    this._deactivate(SelectorEngine.getElementFromSelector(element)); // Search and deactivate the shown section too\n\n    const complete = () => {\n      if (element.getAttribute('role') !== 'tab') {\n        element.classList.remove(CLASS_NAME_SHOW$1);\n        return;\n      }\n      element.setAttribute('aria-selected', false);\n      element.setAttribute('tabindex', '-1');\n      this._toggleDropDown(element, false);\n      EventHandler.trigger(element, EVENT_HIDDEN$1, {\n        relatedTarget: relatedElem\n      });\n    };\n    this._queueCallback(complete, element, element.classList.contains(CLASS_NAME_FADE$1));\n  }\n  _keydown(event) {\n    if (![ARROW_LEFT_KEY, ARROW_RIGHT_KEY, ARROW_UP_KEY, ARROW_DOWN_KEY, HOME_KEY, END_KEY].includes(event.key)) {\n      return;\n    }\n    event.stopPropagation(); // stopPropagation/preventDefault both added to support up/down keys without scrolling the page\n    event.preventDefault();\n    const children = this._getChildren().filter(element => !isDisabled(element));\n    let nextActiveElement;\n    if ([HOME_KEY, END_KEY].includes(event.key)) {\n      nextActiveElement = children[event.key === HOME_KEY ? 0 : children.length - 1];\n    } else {\n      const isNext = [ARROW_RIGHT_KEY, ARROW_DOWN_KEY].includes(event.key);\n      nextActiveElement = getNextActiveElement(children, event.target, isNext, true);\n    }\n    if (nextActiveElement) {\n      nextActiveElement.focus({\n        preventScroll: true\n      });\n      Tab.getOrCreateInstance(nextActiveElement).show();\n    }\n  }\n  _getChildren() {\n    // collection of inner elements\n    return SelectorEngine.find(SELECTOR_INNER_ELEM, this._parent);\n  }\n  _getActiveElem() {\n    return this._getChildren().find(child => this._elemIsActive(child)) || null;\n  }\n  _setInitialAttributes(parent, children) {\n    this._setAttributeIfNotExists(parent, 'role', 'tablist');\n    for (const child of children) {\n      this._setInitialAttributesOnChild(child);\n    }\n  }\n  _setInitialAttributesOnChild(child) {\n    child = this._getInnerElement(child);\n    const isActive = this._elemIsActive(child);\n    const outerElem = this._getOuterElement(child);\n    child.setAttribute('aria-selected', isActive);\n    if (outerElem !== child) {\n      this._setAttributeIfNotExists(outerElem, 'role', 'presentation');\n    }\n    if (!isActive) {\n      child.setAttribute('tabindex', '-1');\n    }\n    this._setAttributeIfNotExists(child, 'role', 'tab');\n\n    // set attributes to the related panel too\n    this._setInitialAttributesOnTargetPanel(child);\n  }\n  _setInitialAttributesOnTargetPanel(child) {\n    const target = SelectorEngine.getElementFromSelector(child);\n    if (!target) {\n      return;\n    }\n    this._setAttributeIfNotExists(target, 'role', 'tabpanel');\n    if (child.id) {\n      this._setAttributeIfNotExists(target, 'aria-labelledby', `${child.id}`);\n    }\n  }\n  _toggleDropDown(element, open) {\n    const outerElem = this._getOuterElement(element);\n    if (!outerElem.classList.contains(CLASS_DROPDOWN)) {\n      return;\n    }\n    const toggle = (selector, className) => {\n      const element = SelectorEngine.findOne(selector, outerElem);\n      if (element) {\n        element.classList.toggle(className, open);\n      }\n    };\n    toggle(SELECTOR_DROPDOWN_TOGGLE, CLASS_NAME_ACTIVE);\n    toggle(SELECTOR_DROPDOWN_MENU, CLASS_NAME_SHOW$1);\n    outerElem.setAttribute('aria-expanded', open);\n  }\n  _setAttributeIfNotExists(element, attribute, value) {\n    if (!element.hasAttribute(attribute)) {\n      element.setAttribute(attribute, value);\n    }\n  }\n  _elemIsActive(elem) {\n    return elem.classList.contains(CLASS_NAME_ACTIVE);\n  }\n\n  // Try to get the inner element (usually the .nav-link)\n  _getInnerElement(elem) {\n    return elem.matches(SELECTOR_INNER_ELEM) ? elem : SelectorEngine.findOne(SELECTOR_INNER_ELEM, elem);\n  }\n\n  // Try to get the outer element (usually the .nav-item)\n  _getOuterElement(elem) {\n    return elem.closest(SELECTOR_OUTER) || elem;\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = Tab.getOrCreateInstance(this);\n      if (typeof config !== 'string') {\n        return;\n      }\n      if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n        throw new TypeError(`No method named \"${config}\"`);\n      }\n      data[config]();\n    });\n  }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, function (event) {\n  if (['A', 'AREA'].includes(this.tagName)) {\n    event.preventDefault();\n  }\n  if (isDisabled(this)) {\n    return;\n  }\n  Tab.getOrCreateInstance(this).show();\n});\n\n/**\n * Initialize on focus\n */\nEventHandler.on(window, EVENT_LOAD_DATA_API, () => {\n  for (const element of SelectorEngine.find(SELECTOR_DATA_TOGGLE_ACTIVE)) {\n    Tab.getOrCreateInstance(element);\n  }\n});\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Tab);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap toast.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME = 'toast';\nconst DATA_KEY = 'bs.toast';\nconst EVENT_KEY = `.${DATA_KEY}`;\nconst EVENT_MOUSEOVER = `mouseover${EVENT_KEY}`;\nconst EVENT_MOUSEOUT = `mouseout${EVENT_KEY}`;\nconst EVENT_FOCUSIN = `focusin${EVENT_KEY}`;\nconst EVENT_FOCUSOUT = `focusout${EVENT_KEY}`;\nconst EVENT_HIDE = `hide${EVENT_KEY}`;\nconst EVENT_HIDDEN = `hidden${EVENT_KEY}`;\nconst EVENT_SHOW = `show${EVENT_KEY}`;\nconst EVENT_SHOWN = `shown${EVENT_KEY}`;\nconst CLASS_NAME_FADE = 'fade';\nconst CLASS_NAME_HIDE = 'hide'; // @deprecated - kept here only for backwards compatibility\nconst CLASS_NAME_SHOW = 'show';\nconst CLASS_NAME_SHOWING = 'showing';\nconst DefaultType = {\n  animation: 'boolean',\n  autohide: 'boolean',\n  delay: 'number'\n};\nconst Default = {\n  animation: true,\n  autohide: true,\n  delay: 5000\n};\n\n/**\n * Class definition\n */\n\nclass Toast extends BaseComponent {\n  constructor(element, config) {\n    super(element, config);\n    this._timeout = null;\n    this._hasMouseInteraction = false;\n    this._hasKeyboardInteraction = false;\n    this._setListeners();\n  }\n\n  // Getters\n  static get Default() {\n    return Default;\n  }\n  static get DefaultType() {\n    return DefaultType;\n  }\n  static get NAME() {\n    return NAME;\n  }\n\n  // Public\n  show() {\n    const showEvent = EventHandler.trigger(this._element, EVENT_SHOW);\n    if (showEvent.defaultPrevented) {\n      return;\n    }\n    this._clearTimeout();\n    if (this._config.animation) {\n      this._element.classList.add(CLASS_NAME_FADE);\n    }\n    const complete = () => {\n      this._element.classList.remove(CLASS_NAME_SHOWING);\n      EventHandler.trigger(this._element, EVENT_SHOWN);\n      this._maybeScheduleHide();\n    };\n    this._element.classList.remove(CLASS_NAME_HIDE); // @deprecated\n    reflow(this._element);\n    this._element.classList.add(CLASS_NAME_SHOW, CLASS_NAME_SHOWING);\n    this._queueCallback(complete, this._element, this._config.animation);\n  }\n  hide() {\n    if (!this.isShown()) {\n      return;\n    }\n    const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE);\n    if (hideEvent.defaultPrevented) {\n      return;\n    }\n    const complete = () => {\n      this._element.classList.add(CLASS_NAME_HIDE); // @deprecated\n      this._element.classList.remove(CLASS_NAME_SHOWING, CLASS_NAME_SHOW);\n      EventHandler.trigger(this._element, EVENT_HIDDEN);\n    };\n    this._element.classList.add(CLASS_NAME_SHOWING);\n    this._queueCallback(complete, this._element, this._config.animation);\n  }\n  dispose() {\n    this._clearTimeout();\n    if (this.isShown()) {\n      this._element.classList.remove(CLASS_NAME_SHOW);\n    }\n    super.dispose();\n  }\n  isShown() {\n    return this._element.classList.contains(CLASS_NAME_SHOW);\n  }\n\n  // Private\n\n  _maybeScheduleHide() {\n    if (!this._config.autohide) {\n      return;\n    }\n    if (this._hasMouseInteraction || this._hasKeyboardInteraction) {\n      return;\n    }\n    this._timeout = setTimeout(() => {\n      this.hide();\n    }, this._config.delay);\n  }\n  _onInteraction(event, isInteracting) {\n    switch (event.type) {\n      case 'mouseover':\n      case 'mouseout':\n        {\n          this._hasMouseInteraction = isInteracting;\n          break;\n        }\n      case 'focusin':\n      case 'focusout':\n        {\n          this._hasKeyboardInteraction = isInteracting;\n          break;\n        }\n    }\n    if (isInteracting) {\n      this._clearTimeout();\n      return;\n    }\n    const nextElement = event.relatedTarget;\n    if (this._element === nextElement || this._element.contains(nextElement)) {\n      return;\n    }\n    this._maybeScheduleHide();\n  }\n  _setListeners() {\n    EventHandler.on(this._element, EVENT_MOUSEOVER, event => this._onInteraction(event, true));\n    EventHandler.on(this._element, EVENT_MOUSEOUT, event => this._onInteraction(event, false));\n    EventHandler.on(this._element, EVENT_FOCUSIN, event => this._onInteraction(event, true));\n    EventHandler.on(this._element, EVENT_FOCUSOUT, event => this._onInteraction(event, false));\n  }\n  _clearTimeout() {\n    clearTimeout(this._timeout);\n    this._timeout = null;\n  }\n\n  // Static\n  static jQueryInterface(config) {\n    return this.each(function () {\n      const data = Toast.getOrCreateInstance(this, config);\n      if (typeof config === 'string') {\n        if (typeof data[config] === 'undefined') {\n          throw new TypeError(`No method named \"${config}\"`);\n        }\n        data[config](this);\n      }\n    });\n  }\n}\n\n/**\n * Data API implementation\n */\n\nenableDismissTrigger(Toast);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Toast);\n\nexport { Alert, Button, Carousel, Collapse, Dropdown, Modal, Offcanvas, Popover, ScrollSpy, Tab, Toast, Tooltip };\n//# sourceMappingURL=bootstrap.esm.js.map\n","/* define several functions to replace jQuery methods\n * inspired by https://tobiasahlin.com/blog/move-from-jquery-to-vanilla-javascript/\n */\n\n/**\n * Execute a method if DOM has finished loading\n *\n * @param {function} callback the method to execute\n */\nexport function documentReady(callback) {\n  if 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Symbol(\"webpack error\") : \"__webpack_error__\";\nvar resolveQueue = (queue) => {\n\tif(queue && queue.d < 1) {\n\t\tqueue.d = 1;\n\t\tqueue.forEach((fn) => (fn.r--));\n\t\tqueue.forEach((fn) => (fn.r-- ? fn.r++ : fn()));\n\t}\n}\nvar wrapDeps = (deps) => (deps.map((dep) => {\n\tif(dep !== null && typeof dep === \"object\") {\n\t\tif(dep[webpackQueues]) return dep;\n\t\tif(dep.then) {\n\t\t\tvar queue = [];\n\t\t\tqueue.d = 0;\n\t\t\tdep.then((r) => {\n\t\t\t\tobj[webpackExports] = r;\n\t\t\t\tresolveQueue(queue);\n\t\t\t}, (e) => {\n\t\t\t\tobj[webpackError] = e;\n\t\t\t\tresolveQueue(queue);\n\t\t\t});\n\t\t\tvar obj = {};\n\t\t\tobj[webpackQueues] = (fn) => (fn(queue));\n\t\t\treturn obj;\n\t\t}\n\t}\n\tvar ret = {};\n\tret[webpackQueues] = x => {};\n\tret[webpackExports] = dep;\n\treturn ret;\n}));\n__webpack_require__.a = (module, body, hasAwait) => {\n\tvar queue;\n\thasAwait && ((queue = []).d = -1);\n\tvar depQueues = new Set();\n\tvar exports = module.exports;\n\tvar currentDeps;\n\tvar outerResolve;\n\tvar reject;\n\tvar promise = new Promise((resolve, rej) => {\n\t\treject = rej;\n\t\touterResolve = resolve;\n\t});\n\tpromise[webpackExports] = exports;\n\tpromise[webpackQueues] = (fn) => (queue && fn(queue), depQueues.forEach(fn), promise[\"catch\"](x => {}));\n\tmodule.exports = promise;\n\tbody((deps) => {\n\t\tcurrentDeps = wrapDeps(deps);\n\t\tvar fn;\n\t\tvar getResult = () => (currentDeps.map((d) => {\n\t\t\tif(d[webpackError]) throw d[webpackError];\n\t\t\treturn d[webpackExports];\n\t\t}))\n\t\tvar promise = new Promise((resolve) => {\n\t\t\tfn = () => (resolve(getResult));\n\t\t\tfn.r = 0;\n\t\t\tvar fnQueue = (q) => (q !== queue && !depQueues.has(q) && (depQueues.add(q), q && !q.d && (fn.r++, q.push(fn))));\n\t\t\tcurrentDeps.map((dep) => (dep[webpackQueues](fnQueue)));\n\t\t});\n\t\treturn fn.r ? promise : getResult();\n\t}, (err) => ((err ? reject(promise[webpackError] = err) : outerResolve(exports)), resolveQueue(queue)));\n\tqueue && queue.d < 0 && (queue.d = 0);\n};","/**\n * Compare [semver](https://semver.org/) version strings to find greater, equal or lesser.\n * This library supports the full semver specification, including comparing versions with different number of digits like `1.0.0`, `1.0`, `1`, and pre-release versions like `1.0.0-alpha`.\n * @param v1 - First version to compare\n * @param v2 - Second version to compare\n * @returns Numeric value compatible with the [Array.sort(fn) interface](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/sort#Parameters).\n */\nexport const compareVersions = (v1, v2) => {\n    // validate input and split into segments\n    const n1 = validateAndParse(v1);\n    const n2 = validateAndParse(v2);\n    // pop off the patch\n    const p1 = n1.pop();\n    const p2 = n2.pop();\n    // validate numbers\n    const r = compareSegments(n1, n2);\n    if (r !== 0)\n        return r;\n    // validate pre-release\n    if (p1 && p2) {\n        return compareSegments(p1.split('.'), p2.split('.'));\n    }\n    else if (p1 || p2) {\n        return p1 ? -1 : 1;\n    }\n    return 0;\n};\n/**\n * Validate [semver](https://semver.org/) version strings.\n *\n * @param version Version number to validate\n * @returns `true` if the version number is a valid semver version number, `false` otherwise.\n *\n * @example\n * ```\n * validate('1.0.0-rc.1'); // return true\n * validate('1.0-rc.1'); // return false\n * validate('foo'); // return false\n * ```\n */\nexport const validate = (version) => typeof version === 'string' && /^[v\\d]/.test(version) && semver.test(version);\n/**\n * Compare [semver](https://semver.org/) version strings using the specified operator.\n *\n * @param v1 First version to compare\n * @param v2 Second version to compare\n * @param operator Allowed arithmetic operator to use\n * @returns `true` if the comparison between the firstVersion and the secondVersion satisfies the operator, `false` otherwise.\n *\n * @example\n * ```\n * compare('10.1.8', '10.0.4', '>'); // return true\n * compare('10.0.1', '10.0.1', '='); // return true\n * compare('10.1.1', '10.2.2', '<'); // return true\n * compare('10.1.1', '10.2.2', '<='); // return true\n * compare('10.1.1', '10.2.2', '>='); // return false\n * ```\n */\nexport const compare = (v1, v2, operator) => {\n    // validate input operator\n    assertValidOperator(operator);\n    // since result of compareVersions can only be -1 or 0 or 1\n    // a simple map can be used to replace switch\n    const res = compareVersions(v1, v2);\n    return operatorResMap[operator].includes(res);\n};\n/**\n * Match [npm semver](https://docs.npmjs.com/cli/v6/using-npm/semver) version range.\n *\n * @param version Version number to match\n * @param range Range pattern for version\n * @returns `true` if the version number is within the range, `false` otherwise.\n *\n * @example\n * ```\n * satisfies('1.1.0', '^1.0.0'); // return true\n * satisfies('1.1.0', '~1.0.0'); // return false\n * ```\n */\nexport const satisfies = (version, range) => {\n    // if no range operator then \"=\"\n    const m = range.match(/^([<>=~^]+)/);\n    const op = m ? m[1] : '=';\n    // if gt/lt/eq then operator compare\n    if (op !== '^' && op !== '~')\n        return compare(version, range, op);\n    // else range of either \"~\" or \"^\" is assumed\n    const [v1, v2, v3, , vp] = validateAndParse(version);\n    const [r1, r2, r3, , rp] = validateAndParse(range);\n    const v = [v1, v2, v3];\n    const r = [r1, r2 !== null && r2 !== void 0 ? r2 : 'x', r3 !== null && r3 !== void 0 ? r3 : 'x'];\n    // validate pre-release\n    if (rp) {\n        if (!vp)\n            return false;\n        if (compareSegments(v, r) !== 0)\n            return false;\n        if (compareSegments(vp.split('.'), rp.split('.')) === -1)\n            return false;\n    }\n    // first non-zero number\n    const nonZero = r.findIndex((v) => v !== '0') + 1;\n    // pointer to where segments can be >=\n    const i = op === '~' ? 2 : nonZero > 1 ? nonZero : 1;\n    // before pointer must be equal\n    if (compareSegments(v.slice(0, i), r.slice(0, i)) !== 0)\n        return false;\n    // after pointer must be >=\n    if (compareSegments(v.slice(i), r.slice(i)) === -1)\n        return false;\n    return true;\n};\nconst semver = /^[v^~<>=]*?(\\d+)(?:\\.([x*]|\\d+)(?:\\.([x*]|\\d+)(?:\\.([x*]|\\d+))?(?:-([\\da-z\\-]+(?:\\.[\\da-z\\-]+)*))?(?:\\+[\\da-z\\-]+(?:\\.[\\da-z\\-]+)*)?)?)?$/i;\nconst validateAndParse = (version) => {\n    if (typeof version !== 'string') {\n        throw new TypeError('Invalid argument expected string');\n    }\n    const match = version.match(semver);\n    if (!match) {\n        throw new Error(`Invalid argument not valid semver ('${version}' received)`);\n    }\n    match.shift();\n    return match;\n};\nconst isWildcard = (s) => s === '*' || s === 'x' || s === 'X';\nconst tryParse = (v) => {\n    const n = parseInt(v, 10);\n    return isNaN(n) ? v : n;\n};\nconst forceType = (a, b) => typeof a !== typeof b ? [String(a), String(b)] : [a, b];\nconst compareStrings = (a, b) => {\n    if (isWildcard(a) || isWildcard(b))\n        return 0;\n    const [ap, bp] = forceType(tryParse(a), tryParse(b));\n    if (ap > bp)\n        return 1;\n    if (ap < bp)\n        return -1;\n    return 0;\n};\nconst compareSegments = (a, b) => {\n    for (let i = 0; i < Math.max(a.length, b.length); i++) {\n        const r = compareStrings(a[i] || '0', b[i] || '0');\n        if (r !== 0)\n            return r;\n    }\n    return 0;\n};\nconst operatorResMap = {\n    '>': [1],\n    '>=': [0, 1],\n    '=': [0],\n    '<=': [-1, 0],\n    '<': [-1],\n};\nconst allowedOperators = Object.keys(operatorResMap);\nconst assertValidOperator = (op) => {\n    if (typeof op !== 'string') {\n        throw new TypeError(`Invalid operator type, expected string but got ${typeof op}`);\n    }\n    if (allowedOperators.indexOf(op) === -1) {\n        throw new Error(`Invalid operator, expected one of ${allowedOperators.join('|')}`);\n    }\n};\n//# sourceMappingURL=index.js.map","/* define several functions to replace jQuery methods\n * inspired by https://tobiasahlin.com/blog/move-from-jquery-to-vanilla-javascript/\n */\n\n/**\n * Execute a method if DOM has finished loading\n *\n * @param {function} callback the method to execute\n */\nexport function documentReady(callback) {\n  if (document.readyState != \"loading\") callback();\n  else document.addEventListener(\"DOMContentLoaded\", callback);\n}\n","// Define the custom behavior of the page\nimport { documentReady } from \"./mixin\";\nimport { compare, validate } from \"compare-versions\";\n\nimport \"../styles/pydata-sphinx-theme.scss\";\n\n/*******************************************************************************\n * Theme interaction\n */\n\nvar prefersDark = window.matchMedia(\"(prefers-color-scheme: dark)\");\n\n/**\n * set the the body theme to the one specified by the user browser\n *\n * @param {event} e\n */\nfunction autoTheme(e) {\n  document.documentElement.dataset.theme = prefersDark.matches\n    ? \"dark\"\n    : \"light\";\n}\n\n/**\n * Set the theme using the specified mode.\n * It can be one of [\"auto\", \"dark\", \"light\"]\n *\n * @param {str} mode\n */\nfunction setTheme(mode) {\n  if (mode !== \"light\" && mode !== \"dark\" && mode !== \"auto\") {\n    console.error(`Got invalid theme mode: ${mode}. Resetting to auto.`);\n    mode = \"auto\";\n  }\n\n  // get the theme\n  var colorScheme = prefersDark.matches ? \"dark\" : \"light\";\n  document.documentElement.dataset.mode = mode;\n  var theme = mode == \"auto\" ? colorScheme : mode;\n  document.documentElement.dataset.theme = theme;\n  // TODO: remove this line after Bootstrap upgrade\n  // v5.3 has a colors mode: https://getbootstrap.com/docs/5.3/customize/color-modes/\n  document.querySelectorAll(\".dropdown-menu\").forEach((el) => {\n    if (theme === \"dark\") {\n      el.classList.add(\"dropdown-menu-dark\");\n    } else {\n      el.classList.remove(\"dropdown-menu-dark\");\n    }\n  });\n\n  // save mode and theme\n  localStorage.setItem(\"mode\", mode);\n  localStorage.setItem(\"theme\", theme);\n  console.log(`[PST]: Changed to ${mode} mode using the ${theme} theme.`);\n\n  // add a listener if set on auto\n  prefersDark.onchange = mode == \"auto\" ? autoTheme : \"\";\n}\n\n/**\n * Change the theme option order so that clicking on the btn is always a change\n * from \"auto\"\n */\nfunction cycleMode() {\n  const defaultMode = document.documentElement.dataset.defaultMode || \"auto\";\n  const currentMode = localStorage.getItem(\"mode\") || defaultMode;\n\n  var loopArray = (arr, current) => {\n    var nextPosition = arr.indexOf(current) + 1;\n    if (nextPosition === arr.length) {\n      nextPosition = 0;\n    }\n    return arr[nextPosition];\n  };\n\n  // make sure the next theme after auto is always a change\n  var modeList = prefersDark.matches\n    ? [\"auto\", \"light\", \"dark\"]\n    : [\"auto\", \"dark\", \"light\"];\n  var newMode = loopArray(modeList, currentMode);\n  setTheme(newMode);\n}\n\n/**\n * add the theme listener on the btns of the navbar\n */\nfunction addModeListener() {\n  // the theme was set a first time using the initial mini-script\n  // running setMode will ensure the use of the dark mode if auto is selected\n  setTheme(document.documentElement.dataset.mode);\n\n  // Attach event handlers for toggling themes colors\n  document.querySelectorAll(\".theme-switch-button\").forEach((el) => {\n    el.addEventListener(\"click\", cycleMode);\n  });\n}\n\n/*******************************************************************************\n * TOC interactivity\n */\n\n/**\n * TOC sidebar - add \"active\" class to parent list\n *\n * Bootstrap's scrollspy adds the active class to the <a> link,\n * but for the automatic collapsing we need this on the parent list item.\n *\n * The event is triggered on \"window\" (and not the nav item as documented),\n * see https://github.com/twbs/bootstrap/issues/20086\n */\nfunction addTOCInteractivity() {\n  window.addEventListener(\"activate.bs.scrollspy\", function () {\n    const navLinks = document.querySelectorAll(\".bd-toc-nav a\");\n\n    navLinks.forEach((navLink) => {\n      navLink.parentElement.classList.remove(\"active\");\n    });\n\n    const activeNavLinks = document.querySelectorAll(\".bd-toc-nav a.active\");\n    activeNavLinks.forEach((navLink) => {\n      navLink.parentElement.classList.add(\"active\");\n    });\n  });\n}\n\n/*******************************************************************************\n * Scroll\n */\n\n/**\n * Navigation sidebar scrolling to active page\n */\nfunction scrollToActive() {\n  // If the docs nav doesn't exist, do nothing (e.g., on search page)\n  if (!document.querySelector(\".bd-docs-nav\")) {\n    return;\n  }\n\n  var sidebar = document.querySelector(\"div.bd-sidebar\");\n\n  // Remember the sidebar scroll position between page loads\n  // Inspired on source of revealjs.com\n  let storedScrollTop = parseInt(\n    sessionStorage.getItem(\"sidebar-scroll-top\"),\n    10\n  );\n\n  if (!isNaN(storedScrollTop)) {\n    // If we've got a saved scroll position, just use that\n    sidebar.scrollTop = storedScrollTop;\n    console.log(\"[PST]: Scrolled sidebar using stored browser position...\");\n  } else {\n    // Otherwise, calculate a position to scroll to based on the lowest `active` link\n    var sidebarNav = document.querySelector(\".bd-docs-nav\");\n    var active_pages = sidebarNav.querySelectorAll(\".active\");\n    if (active_pages.length > 0) {\n      // Use the last active page as the offset since it's the page we're on\n      var latest_active = active_pages[active_pages.length - 1];\n      var offset =\n        latest_active.getBoundingClientRect().y -\n        sidebar.getBoundingClientRect().y;\n      // Only scroll the navbar if the active link is lower than 50% of the page\n      if (latest_active.getBoundingClientRect().y > window.innerHeight * 0.5) {\n        let buffer = 0.25; // Buffer so we have some space above the scrolled item\n        sidebar.scrollTop = offset - sidebar.clientHeight * buffer;\n        console.log(\"[PST]: Scrolled sidebar using last active link...\");\n      }\n    }\n  }\n\n  // Store the sidebar scroll position\n  window.addEventListener(\"beforeunload\", () => {\n    sessionStorage.setItem(\"sidebar-scroll-top\", sidebar.scrollTop);\n  });\n}\n\n/*******************************************************************************\n * Search\n */\n\n/**\n * Find any search forms on the page and return their input element\n */\nvar findSearchInput = () => {\n  let forms = document.querySelectorAll(\"form.bd-search\");\n  if (!forms.length) {\n    // no search form found\n    return;\n  } else {\n    var form;\n    if (forms.length == 1) {\n      // there is exactly one search form (persistent or hidden)\n      form = forms[0];\n    } else {\n      // must be at least one persistent form, use the first persistent one\n      form = document.querySelector(\n        \"div:not(.search-button__search-container) > form.bd-search\"\n      );\n    }\n    return form.querySelector(\"input\");\n  }\n};\n\n/**\n * Activate the search field on the page.\n * - If there is a search field already visible it will be activated.\n * - If not, then a search field will pop up.\n */\nvar toggleSearchField = () => {\n  // Find the search input to highlight\n  let input = findSearchInput();\n\n  // if the input field is the hidden one (the one associated with the\n  // search button) then toggle the button state (to show/hide the field)\n  let searchPopupWrapper = document.querySelector(\".search-button__wrapper\");\n  let hiddenInput = searchPopupWrapper.querySelector(\"input\");\n  if (input === hiddenInput) {\n    searchPopupWrapper.classList.toggle(\"show\");\n  }\n  // when toggling off the search field, remove its focus\n  if (document.activeElement === input) {\n    input.blur();\n  } else {\n    input.focus();\n    input.select();\n    input.scrollIntoView({ block: \"center\" });\n  }\n};\n\n/**\n * Add an event listener for toggleSearchField() for Ctrl/Cmd + K\n */\nvar addEventListenerForSearchKeyboard = () => {\n  window.addEventListener(\n    \"keydown\",\n    (event) => {\n      let input = findSearchInput();\n      // toggle on Ctrl+k or ⌘+k\n      if (\n        // Ignore if shift or alt are pressed\n        !event.shiftKey &&\n        !event.altKey &&\n        // On Mac use ⌘, all other OS use Ctrl\n        (useCommandKey\n          ? event.metaKey && !event.ctrlKey\n          : !event.metaKey && event.ctrlKey) &&\n        // Case-insensitive so the shortcut still works with caps lock\n        /^k$/i.test(event.key)\n      ) {\n        event.preventDefault();\n        toggleSearchField();\n      }\n      // also allow Escape key to hide (but not show) the dynamic search field\n      else if (document.activeElement === input && /Escape/i.test(event.key)) {\n        toggleSearchField();\n      }\n    },\n    true\n  );\n};\n\n/**\n * If the user is on a Mac, use command (⌘) instead of control (ctrl) key\n *\n * Note: `navigator.platform` is deprecated; however MDN still recommends using\n * it for the one specific use case of detecting whether a keyboard shortcut\n * should use control or command:\n * https://developer.mozilla.org/en-US/docs/Web/API/Navigator/platform#examples\n */\nvar useCommandKey =\n  navigator.platform.indexOf(\"Mac\") === 0 || navigator.platform === \"iPhone\";\n\n/**\n * Change the search hint to `meta key` if we are a Mac\n */\n\nvar changeSearchShortcutKey = () => {\n  let shortcuts = document.querySelectorAll(\".search-button__kbd-shortcut\");\n  if (useCommandKey) {\n    shortcuts.forEach(\n      (f) => (f.querySelector(\"kbd.kbd-shortcut__modifier\").innerText = \"⌘\")\n    );\n  }\n};\n\n/**\n * Activate callbacks for search button popup\n */\nvar setupSearchButtons = () => {\n  changeSearchShortcutKey();\n  addEventListenerForSearchKeyboard();\n\n  // Add the search button trigger event callback\n  document.querySelectorAll(\".search-button__button\").forEach((btn) => {\n    btn.onclick = toggleSearchField;\n  });\n\n  // Add the search button overlay event callback\n  let overlay = document.querySelector(\".search-button__overlay\");\n  if (overlay) {\n    overlay.onclick = toggleSearchField;\n  }\n};\n\n/*******************************************************************************\n * Version Switcher\n * Note that this depends on two variables existing that are defined in\n * and `html-page-context` hook:\n *\n * - DOCUMENTATION_OPTIONS.pagename\n * - DOCUMENTATION_OPTIONS.theme_switcher_url\n */\n\n/**\n * Check if corresponding page path exists in other version of docs\n * and, if so, go there instead of the homepage of the other docs version\n *\n * @param {event} event the event that trigger the check\n */\nasync function checkPageExistsAndRedirect(event) {\n  // ensure we don't follow the initial link\n  event.preventDefault();\n  let currentFilePath = `${DOCUMENTATION_OPTIONS.pagename}.html`;\n  let tryUrl = event.currentTarget.getAttribute(\"href\");\n  let otherDocsHomepage = tryUrl.replace(currentFilePath, \"\");\n  try {\n    let head = await fetch(tryUrl, { method: \"HEAD\" });\n    if (head.ok) {\n      location.href = tryUrl; // the page exists, go there\n    } else {\n      location.href = otherDocsHomepage;\n    }\n  } catch (err) {\n    // something went wrong, probably CORS restriction, fallback to other docs homepage\n    location.href = otherDocsHomepage;\n  }\n}\n\n/**\n * Load and parse the version switcher JSON file from an absolute or relative URL.\n *\n * @param {string} url The URL to load version switcher entries from.\n */\nasync function fetchVersionSwitcherJSON(url) {\n  // first check if it's a valid URL\n  try {\n    var result = new URL(url);\n  } catch (err) {\n    if (err instanceof TypeError) {\n      // assume we got a relative path, and fix accordingly. But first, we need to\n      // use `fetch()` to follow redirects so we get the correct final base URL\n      const origin = await fetch(window.location.origin, { method: \"HEAD\" });\n      result = new URL(url, origin.url);\n    } else {\n      // something unexpected happened\n      throw err;\n    }\n  }\n  // load and return the JSON\n  const response = await fetch(result);\n  const data = await response.json();\n  return data;\n}\n\n// Populate the version switcher from the JSON data\nfunction populateVersionSwitcher(data, versionSwitcherBtns) {\n  const currentFilePath = `${DOCUMENTATION_OPTIONS.pagename}.html`;\n  versionSwitcherBtns.forEach((btn) => {\n    // Set empty strings by default so that these attributes exist and can be used in CSS selectors\n    btn.dataset[\"activeVersionName\"] = \"\";\n    btn.dataset[\"activeVersion\"] = \"\";\n  });\n  // in case there are multiple entries with the same version string, this helps us\n  // decide which entry's `name` to put on the button itself. Without this, it would\n  // always be the *last* version-matching entry; now it will be either the\n  // version-matching entry that is also marked as `\"preferred\": true`, or if that\n  // doesn't exist: the *first* version-matching entry.\n  data = data.map((entry) => {\n    // does this entry match the version that we're currently building/viewing?\n    entry.match =\n      entry.version == DOCUMENTATION_OPTIONS.theme_switcher_version_match;\n    entry.preferred = entry.preferred || false;\n    // if no custom name specified (e.g., \"latest\"), use version string\n    if (!(\"name\" in entry)) {\n      entry.name = entry.version;\n    }\n    return entry;\n  });\n  const hasMatchingPreferredEntry = data\n    .map((entry) => entry.preferred && entry.match)\n    .some(Boolean);\n  var foundMatch = false;\n  // create links to the corresponding page in the other docs versions\n  data.forEach((entry) => {\n    // create the node\n    const anchor = document.createElement(\"a\");\n    anchor.setAttribute(\n      \"class\",\n      \"dropdown-item list-group-item list-group-item-action py-1\"\n    );\n    anchor.setAttribute(\"href\", `${entry.url}${currentFilePath}`);\n    anchor.setAttribute(\"role\", \"option\");\n    const span = document.createElement(\"span\");\n    span.textContent = `${entry.name}`;\n    anchor.appendChild(span);\n    // Add dataset values for the version and name in case people want\n    // to apply CSS styling based on this information.\n    anchor.dataset[\"versionName\"] = entry.name;\n    anchor.dataset[\"version\"] = entry.version;\n    // replace dropdown button text with the preferred display name of the\n    // currently-viewed version, rather than using sphinx's {{ version }} variable.\n    // also highlight the dropdown entry for the currently-viewed version's entry\n    let matchesAndIsPreferred = hasMatchingPreferredEntry && entry.preferred;\n    let matchesAndIsFirst =\n      !hasMatchingPreferredEntry && !foundMatch && entry.match;\n    if (matchesAndIsPreferred || matchesAndIsFirst) {\n      anchor.classList.add(\"active\");\n      versionSwitcherBtns.forEach((btn) => {\n        btn.innerText = entry.name;\n        btn.dataset[\"activeVersionName\"] = entry.name;\n        btn.dataset[\"activeVersion\"] = entry.version;\n      });\n      foundMatch = true;\n    }\n    // There may be multiple version-switcher elements, e.g. one\n    // in a slide-over panel displayed on smaller screens.\n    document.querySelectorAll(\".version-switcher__menu\").forEach((menu) => {\n      // we need to clone the node for each menu, but onclick attributes are not\n      // preserved by `.cloneNode()` so we add onclick here after cloning.\n      let node = anchor.cloneNode(true);\n      node.onclick = checkPageExistsAndRedirect;\n      // on click, AJAX calls will check if the linked page exists before\n      // trying to redirect, and if not, will redirect to the homepage\n      // for that version of the docs.\n      menu.append(node);\n    });\n  });\n}\n\n/*******************************************************************************\n * Warning banner when viewing non-stable version of the docs.\n */\n\n/**\n * Show a warning banner when viewing a non-stable version of the docs.\n *\n * adapted 2023-06 from https://mne.tools/versionwarning.js, which was\n * originally adapted 2020-05 from https://scikit-learn.org/versionwarning.js\n *\n * @param {Array} data The version data used to populate the switcher menu.\n */\nfunction showVersionWarningBanner(data) {\n  var version = DOCUMENTATION_OPTIONS.VERSION;\n  // figure out what latest stable version is\n  var preferredEntries = data.filter((entry) => entry.preferred);\n  if (preferredEntries.length !== 1) {\n    const howMany = preferredEntries.length == 0 ? \"No\" : \"Multiple\";\n    console.log(\n      `[PST] ${howMany} versions marked \"preferred\" found in versions JSON, ignoring.`\n    );\n    return;\n  }\n  const preferredVersion = 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https://developer.mozilla.org/en-US/docs/Web/API/Fullscreen_API\n */\nvar toggleFullScreen = () => {\n  var isInFullScreen =\n    (document.fullscreenElement && document.fullscreenElement !== null) ||\n    (document.webkitFullscreenElement &&\n      document.webkitFullscreenElement !== null);\n  let docElm = document.documentElement;\n  if (!isInFullScreen) {\n    console.log(\"[SBT]: Entering full screen\");\n    if (docElm.requestFullscreen) {\n      docElm.requestFullscreen();\n    } else if (docElm.webkitRequestFullscreen) {\n      docElm.webkitRequestFullscreen();\n    }\n  } else {\n    console.log(\"[SBT]: Exiting full screen\");\n    if (document.exitFullscreen) {\n      document.exitFullscreen();\n    } else if (document.webkitExitFullscreen) {\n      document.webkitExitFullscreen();\n    }\n  }\n};\n\n/**\n * Manage scrolling behavior. This is primarily two things:\n *\n * 1. Hide the Table of Contents any time sidebar content is on the screen.\n *\n * This will be triggered any time a sidebar item enters or exits the screen.\n * It adds/removes items from an array if they have entered the screen, and\n * removes them when they exit the screen. It hides the TOC if anything is\n * on-screen.\n *\n * ref: https://developer.mozilla.org/en-US/docs/Web/API/Intersection_Observer_API\n *\n * 2. Add a `scrolled` class to <body> to trigger CSS changes.\n */\nvar initTocHide = () => {\n  var onScreenItems = [];\n  let hideTocCallback = (entries, observer) => {\n    // Check whether any sidebar item is displayed\n    entries.forEach((entry) => {\n      if (entry.isIntersecting) {\n        // If an element just came on screen, add it our list\n        onScreenItems.push(entry.target);\n      } else {\n        // Otherwise, if it's in our list then remove it\n        for (let ii = 0; ii < onScreenItems.length; ii++) {\n          if (onScreenItems[ii] === entry.target) {\n            onScreenItems.splice(ii, 1);\n            break;\n          }\n        }\n      }\n    });\n\n    // Hide the TOC if any margin content is displayed on the screen\n    if (onScreenItems.length > 0) {\n      document.querySelector(\"div.bd-sidebar-secondary\").classList.add(\"hide\");\n    } else {\n      document\n        .querySelector(\"div.bd-sidebar-secondary\")\n        .classList.remove(\"hide\");\n    }\n  };\n  let manageScrolledClassOnBody = (entries, observer) => {\n    // The pixel is at the top, so if we're < 0 that it means we've scrolled\n    if (entries[0].boundingClientRect.y < 0) {\n      document.body.classList.add(\"scrolled\");\n    } else {\n      document.body.classList.remove(\"scrolled\");\n    }\n  };\n\n  // Set up the intersection observer to watch all margin content\n  let options = {\n    // Trigger callback when the top of a margin item is 1/3 up the screen\n    rootMargin: \"0px 0px -33% 0px\",\n  };\n  let tocObserver = new IntersectionObserver(hideTocCallback, options);\n  // TODO: deprecate popout after v0.5.0\n  const selectorClasses = [\n    \"marginnote\",\n    \"sidenote\",\n    \"margin\",\n    \"margin-caption\",\n    \"full-width\",\n    \"sidebar\",\n    \"popout\",\n  ];\n  let marginSelector = [];\n  selectorClasses.forEach((ii) => {\n    // Use three permutations of each class name because `tag_` and `_` used to be supported\n    marginSelector.push(\n      ...[\n        `.${ii}`,\n        `.tag_${ii}`,\n        `.${ii.replace(\"-\", \"_\")}`,\n        `.tag_${ii.replace(\"-\", \"_\")}`,\n      ],\n    );\n  });\n  document.querySelectorAll(marginSelector.join(\", \")).forEach((ii) => {\n    tocObserver.observe(ii);\n  });\n\n  // Set up the observer to check if we've scrolled from top of page\n  let scrollObserver = new IntersectionObserver(manageScrolledClassOnBody);\n  scrollObserver.observe(document.querySelector(\".sbt-scroll-pixel-helper\"));\n};\n\n/**\n * Activate Thebe with a custom button click.\n */\nvar initThebeSBT = () => {\n  var title = document.querySelector(\"section h1\");\n  var sibling = title.nextElementSibling;\n  // If the next element after the title isn't a thebe button, add one now.\n  // That way it is initiatlized when thebe is first-clicked and isn't re-added after.\n  if (!sibling.classList.contains(\"thebe-launch-button\")) {\n    title.insertAdjacentHTML(\n      \"afterend\",\n      \"<button class='thebe-launch-button'></button>\",\n    );\n  }\n  // This function is provided by sphinx-thebe\n  initThebe();\n};\n\n/**\n * Add no print class to certain DOM elements\n */\n\nfunction addNoPrint() {\n  var noPrintSelector = [\n    \".bd-header-announcement\",\n    \".bd-header\",\n    \".bd-header-article\",\n    \".bd-sidebar-primary\",\n    \".bd-sidebar-secondary\",\n    \".bd-footer-article\",\n    \".bd-footer-content\",\n    \".bd-footer\",\n  ].join(\",\");\n  document.querySelectorAll(noPrintSelector).forEach((ii) => {\n    ii.classList.add(\"noprint\");\n  });\n}\n\n/**\n * Set up callback functions for UI click actions\n */\nwindow.initThebeSBT = initThebeSBT;\nwindow.toggleFullScreen = toggleFullScreen;\n\n/**\n * Set up functions to load when the DOM is ready\n */\nsbRunWhenDOMLoaded(initTocHide);\nsbRunWhenDOMLoaded(addNoPrint);\n"],"sourceRoot":""}
\ No newline at end of file
diff --git a/_static/searchtools.js b/_static/searchtools.js
new file mode 100644
index 0000000..92da3f8
--- /dev/null
+++ b/_static/searchtools.js
@@ -0,0 +1,619 @@
+/*
+ * searchtools.js
+ * ~~~~~~~~~~~~~~~~
+ *
+ * Sphinx JavaScript utilities for the full-text search.
+ *
+ * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+"use strict";
+
+/**
+ * Simple result scoring code.
+ */
+if (typeof Scorer === "undefined") {
+  var Scorer = {
+    // Implement the following function to further tweak the score for each result
+    // The function takes a result array [docname, title, anchor, descr, score, filename]
+    // and returns the new score.
+    /*
+    score: result => {
+      const [docname, title, anchor, descr, score, filename] = result
+      return score
+    },
+    */
+
+    // query matches the full name of an object
+    objNameMatch: 11,
+    // or matches in the last dotted part of the object name
+    objPartialMatch: 6,
+    // Additive scores depending on the priority of the object
+    objPrio: {
+      0: 15, // used to be importantResults
+      1: 5, // used to be objectResults
+      2: -5, // used to be unimportantResults
+    },
+    //  Used when the priority is not in the mapping.
+    objPrioDefault: 0,
+
+    // query found in title
+    title: 15,
+    partialTitle: 7,
+    // query found in terms
+    term: 5,
+    partialTerm: 2,
+  };
+}
+
+const _removeChildren = (element) => {
+  while (element && element.lastChild) element.removeChild(element.lastChild);
+};
+
+/**
+ * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping
+ */
+const _escapeRegExp = (string) =>
+  string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string
+
+const _displayItem = (item, searchTerms, highlightTerms) => {
+  const docBuilder = DOCUMENTATION_OPTIONS.BUILDER;
+  const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX;
+  const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX;
+  const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY;
+  const contentRoot = document.documentElement.dataset.content_root;
+
+  const [docName, title, anchor, descr, score, _filename] = item;
+
+  let listItem = document.createElement("li");
+  let requestUrl;
+  let linkUrl;
+  if (docBuilder === "dirhtml") {
+    // dirhtml builder
+    let dirname = docName + "/";
+    if (dirname.match(/\/index\/$/))
+      dirname = dirname.substring(0, dirname.length - 6);
+    else if (dirname === "index/") dirname = "";
+    requestUrl = contentRoot + dirname;
+    linkUrl = requestUrl;
+  } else {
+    // normal html builders
+    requestUrl = contentRoot + docName + docFileSuffix;
+    linkUrl = docName + docLinkSuffix;
+  }
+  let linkEl = listItem.appendChild(document.createElement("a"));
+  linkEl.href = linkUrl + anchor;
+  linkEl.dataset.score = score;
+  linkEl.innerHTML = title;
+  if (descr) {
+    listItem.appendChild(document.createElement("span")).innerHTML =
+      " (" + descr + ")";
+    // highlight search terms in the description
+    if (SPHINX_HIGHLIGHT_ENABLED)  // set in sphinx_highlight.js
+      highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
+  }
+  else if (showSearchSummary)
+    fetch(requestUrl)
+      .then((responseData) => responseData.text())
+      .then((data) => {
+        if (data)
+          listItem.appendChild(
+            Search.makeSearchSummary(data, searchTerms, anchor)
+          );
+        // highlight search terms in the summary
+        if (SPHINX_HIGHLIGHT_ENABLED)  // set in sphinx_highlight.js
+          highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
+      });
+  Search.output.appendChild(listItem);
+};
+const _finishSearch = (resultCount) => {
+  Search.stopPulse();
+  Search.title.innerText = _("Search Results");
+  if (!resultCount)
+    Search.status.innerText = Documentation.gettext(
+      "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories."
+    );
+  else
+    Search.status.innerText = _(
+      "Search finished, found ${resultCount} page(s) matching the search query."
+    ).replace('${resultCount}', resultCount);
+};
+const _displayNextItem = (
+  results,
+  resultCount,
+  searchTerms,
+  highlightTerms,
+) => {
+  // results left, load the summary and display it
+  // this is intended to be dynamic (don't sub resultsCount)
+  if (results.length) {
+    _displayItem(results.pop(), searchTerms, highlightTerms);
+    setTimeout(
+      () => _displayNextItem(results, resultCount, searchTerms, highlightTerms),
+      5
+    );
+  }
+  // search finished, update title and status message
+  else _finishSearch(resultCount);
+};
+// Helper function used by query() to order search results.
+// Each input is an array of [docname, title, anchor, descr, score, filename].
+// Order the results by score (in opposite order of appearance, since the
+// `_displayNextItem` function uses pop() to retrieve items) and then alphabetically.
+const _orderResultsByScoreThenName = (a, b) => {
+  const leftScore = a[4];
+  const rightScore = b[4];
+  if (leftScore === rightScore) {
+    // same score: sort alphabetically
+    const leftTitle = a[1].toLowerCase();
+    const rightTitle = b[1].toLowerCase();
+    if (leftTitle === rightTitle) return 0;
+    return leftTitle > rightTitle ? -1 : 1; // inverted is intentional
+  }
+  return leftScore > rightScore ? 1 : -1;
+};
+
+/**
+ * Default splitQuery function. Can be overridden in ``sphinx.search`` with a
+ * custom function per language.
+ *
+ * The regular expression works by splitting the string on consecutive characters
+ * that are not Unicode letters, numbers, underscores, or emoji characters.
+ * This is the same as ``\W+`` in Python, preserving the surrogate pair area.
+ */
+if (typeof splitQuery === "undefined") {
+  var splitQuery = (query) => query
+      .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu)
+      .filter(term => term)  // remove remaining empty strings
+}
+
+/**
+ * Search Module
+ */
+const Search = {
+  _index: null,
+  _queued_query: null,
+  _pulse_status: -1,
+
+  htmlToText: (htmlString, anchor) => {
+    const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html');
+    for (const removalQuery of [".headerlinks", "script", "style"]) {
+      htmlElement.querySelectorAll(removalQuery).forEach((el) => { el.remove() });
+    }
+    if (anchor) {
+      const anchorContent = htmlElement.querySelector(`[role="main"] ${anchor}`);
+      if (anchorContent) return anchorContent.textContent;
+
+      console.warn(
+        `Anchored content block not found. Sphinx search tries to obtain it via DOM query '[role=main] ${anchor}'. Check your theme or template.`
+      );
+    }
+
+    // if anchor not specified or not found, fall back to main content
+    const docContent = htmlElement.querySelector('[role="main"]');
+    if (docContent) return docContent.textContent;
+
+    console.warn(
+      "Content block not found. Sphinx search tries to obtain it via DOM query '[role=main]'. Check your theme or template."
+    );
+    return "";
+  },
+
+  init: () => {
+    const query = new URLSearchParams(window.location.search).get("q");
+    document
+      .querySelectorAll('input[name="q"]')
+      .forEach((el) => (el.value = query));
+    if (query) Search.performSearch(query);
+  },
+
+  loadIndex: (url) =>
+    (document.body.appendChild(document.createElement("script")).src = url),
+
+  setIndex: (index) => {
+    Search._index = index;
+    if (Search._queued_query !== null) {
+      const query = Search._queued_query;
+      Search._queued_query = null;
+      Search.query(query);
+    }
+  },
+
+  hasIndex: () => Search._index !== null,
+
+  deferQuery: (query) => (Search._queued_query = query),
+
+  stopPulse: () => (Search._pulse_status = -1),
+
+  startPulse: () => {
+    if (Search._pulse_status >= 0) return;
+
+    const pulse = () => {
+      Search._pulse_status = (Search._pulse_status + 1) % 4;
+      Search.dots.innerText = ".".repeat(Search._pulse_status);
+      if (Search._pulse_status >= 0) window.setTimeout(pulse, 500);
+    };
+    pulse();
+  },
+
+  /**
+   * perform a search for something (or wait until index is loaded)
+   */
+  performSearch: (query) => {
+    // create the required interface elements
+    const searchText = document.createElement("h2");
+    searchText.textContent = _("Searching");
+    const searchSummary = document.createElement("p");
+    searchSummary.classList.add("search-summary");
+    searchSummary.innerText = "";
+    const searchList = document.createElement("ul");
+    searchList.classList.add("search");
+
+    const out = document.getElementById("search-results");
+    Search.title = out.appendChild(searchText);
+    Search.dots = Search.title.appendChild(document.createElement("span"));
+    Search.status = out.appendChild(searchSummary);
+    Search.output = out.appendChild(searchList);
+
+    const searchProgress = document.getElementById("search-progress");
+    // Some themes don't use the search progress node
+    if (searchProgress) {
+      searchProgress.innerText = _("Preparing search...");
+    }
+    Search.startPulse();
+
+    // index already loaded, the browser was quick!
+    if (Search.hasIndex()) Search.query(query);
+    else Search.deferQuery(query);
+  },
+
+  _parseQuery: (query) => {
+    // stem the search terms and add them to the correct list
+    const stemmer = new Stemmer();
+    const searchTerms = new Set();
+    const excludedTerms = new Set();
+    const highlightTerms = new Set();
+    const objectTerms = new Set(splitQuery(query.toLowerCase().trim()));
+    splitQuery(query.trim()).forEach((queryTerm) => {
+      const queryTermLower = queryTerm.toLowerCase();
+
+      // maybe skip this "word"
+      // stopwords array is from language_data.js
+      if (
+        stopwords.indexOf(queryTermLower) !== -1 ||
+        queryTerm.match(/^\d+$/)
+      )
+        return;
+
+      // stem the word
+      let word = stemmer.stemWord(queryTermLower);
+      // select the correct list
+      if (word[0] === "-") excludedTerms.add(word.substr(1));
+      else {
+        searchTerms.add(word);
+        highlightTerms.add(queryTermLower);
+      }
+    });
+
+    if (SPHINX_HIGHLIGHT_ENABLED) {  // set in sphinx_highlight.js
+      localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" "))
+    }
+
+    // console.debug("SEARCH: searching for:");
+    // console.info("required: ", [...searchTerms]);
+    // console.info("excluded: ", [...excludedTerms]);
+
+    return [query, searchTerms, excludedTerms, highlightTerms, objectTerms];
+  },
+
+  /**
+   * execute search (requires search index to be loaded)
+   */
+  _performSearch: (query, searchTerms, excludedTerms, highlightTerms, objectTerms) => {
+    const filenames = Search._index.filenames;
+    const docNames = Search._index.docnames;
+    const titles = Search._index.titles;
+    const allTitles = Search._index.alltitles;
+    const indexEntries = Search._index.indexentries;
+
+    // Collect multiple result groups to be sorted separately and then ordered.
+    // Each is an array of [docname, title, anchor, descr, score, filename].
+    const normalResults = [];
+    const nonMainIndexResults = [];
+
+    _removeChildren(document.getElementById("search-progress"));
+
+    const queryLower = query.toLowerCase().trim();
+    for (const [title, foundTitles] of Object.entries(allTitles)) {
+      if (title.toLowerCase().trim().includes(queryLower) && (queryLower.length >= title.length/2)) {
+        for (const [file, id] of foundTitles) {
+          let score = Math.round(100 * queryLower.length / title.length)
+          normalResults.push([
+            docNames[file],
+            titles[file] !== title ? `${titles[file]} > ${title}` : title,
+            id !== null ? "#" + id : "",
+            null,
+            score,
+            filenames[file],
+          ]);
+        }
+      }
+    }
+
+    // search for explicit entries in index directives
+    for (const [entry, foundEntries] of Object.entries(indexEntries)) {
+      if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) {
+        for (const [file, id, isMain] of foundEntries) {
+          const score = Math.round(100 * queryLower.length / entry.length);
+          const result = [
+            docNames[file],
+            titles[file],
+            id ? "#" + id : "",
+            null,
+            score,
+            filenames[file],
+          ];
+          if (isMain) {
+            normalResults.push(result);
+          } else {
+            nonMainIndexResults.push(result);
+          }
+        }
+      }
+    }
+
+    // lookup as object
+    objectTerms.forEach((term) =>
+      normalResults.push(...Search.performObjectSearch(term, objectTerms))
+    );
+
+    // lookup as search terms in fulltext
+    normalResults.push(...Search.performTermsSearch(searchTerms, excludedTerms));
+
+    // let the scorer override scores with a custom scoring function
+    if (Scorer.score) {
+      normalResults.forEach((item) => (item[4] = Scorer.score(item)));
+      nonMainIndexResults.forEach((item) => (item[4] = Scorer.score(item)));
+    }
+
+    // Sort each group of results by score and then alphabetically by name.
+    normalResults.sort(_orderResultsByScoreThenName);
+    nonMainIndexResults.sort(_orderResultsByScoreThenName);
+
+    // Combine the result groups in (reverse) order.
+    // Non-main index entries are typically arbitrary cross-references,
+    // so display them after other results.
+    let results = [...nonMainIndexResults, ...normalResults];
+
+    // remove duplicate search results
+    // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept
+    let seen = new Set();
+    results = results.reverse().reduce((acc, result) => {
+      let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(',');
+      if (!seen.has(resultStr)) {
+        acc.push(result);
+        seen.add(resultStr);
+      }
+      return acc;
+    }, []);
+
+    return results.reverse();
+  },
+
+  query: (query) => {
+    const [searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms] = Search._parseQuery(query);
+    const results = Search._performSearch(searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms);
+
+    // for debugging
+    //Search.lastresults = results.slice();  // a copy
+    // console.info("search results:", Search.lastresults);
+
+    // print the results
+    _displayNextItem(results, results.length, searchTerms, highlightTerms);
+  },
+
+  /**
+   * search for object names
+   */
+  performObjectSearch: (object, objectTerms) => {
+    const filenames = Search._index.filenames;
+    const docNames = Search._index.docnames;
+    const objects = Search._index.objects;
+    const objNames = Search._index.objnames;
+    const titles = Search._index.titles;
+
+    const results = [];
+
+    const objectSearchCallback = (prefix, match) => {
+      const name = match[4]
+      const fullname = (prefix ? prefix + "." : "") + name;
+      const fullnameLower = fullname.toLowerCase();
+      if (fullnameLower.indexOf(object) < 0) return;
+
+      let score = 0;
+      const parts = fullnameLower.split(".");
+
+      // check for different match types: exact matches of full name or
+      // "last name" (i.e. last dotted part)
+      if (fullnameLower === object || parts.slice(-1)[0] === object)
+        score += Scorer.objNameMatch;
+      else if (parts.slice(-1)[0].indexOf(object) > -1)
+        score += Scorer.objPartialMatch; // matches in last name
+
+      const objName = objNames[match[1]][2];
+      const title = titles[match[0]];
+
+      // If more than one term searched for, we require other words to be
+      // found in the name/title/description
+      const otherTerms = new Set(objectTerms);
+      otherTerms.delete(object);
+      if (otherTerms.size > 0) {
+        const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase();
+        if (
+          [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0)
+        )
+          return;
+      }
+
+      let anchor = match[3];
+      if (anchor === "") anchor = fullname;
+      else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname;
+
+      const descr = objName + _(", in ") + title;
+
+      // add custom score for some objects according to scorer
+      if (Scorer.objPrio.hasOwnProperty(match[2]))
+        score += Scorer.objPrio[match[2]];
+      else score += Scorer.objPrioDefault;
+
+      results.push([
+        docNames[match[0]],
+        fullname,
+        "#" + anchor,
+        descr,
+        score,
+        filenames[match[0]],
+      ]);
+    };
+    Object.keys(objects).forEach((prefix) =>
+      objects[prefix].forEach((array) =>
+        objectSearchCallback(prefix, array)
+      )
+    );
+    return results;
+  },
+
+  /**
+   * search for full-text terms in the index
+   */
+  performTermsSearch: (searchTerms, excludedTerms) => {
+    // prepare search
+    const terms = Search._index.terms;
+    const titleTerms = Search._index.titleterms;
+    const filenames = Search._index.filenames;
+    const docNames = Search._index.docnames;
+    const titles = Search._index.titles;
+
+    const scoreMap = new Map();
+    const fileMap = new Map();
+
+    // perform the search on the required terms
+    searchTerms.forEach((word) => {
+      const files = [];
+      const arr = [
+        { files: terms[word], score: Scorer.term },
+        { files: titleTerms[word], score: Scorer.title },
+      ];
+      // add support for partial matches
+      if (word.length > 2) {
+        const escapedWord = _escapeRegExp(word);
+        if (!terms.hasOwnProperty(word)) {
+          Object.keys(terms).forEach((term) => {
+            if (term.match(escapedWord))
+              arr.push({ files: terms[term], score: Scorer.partialTerm });
+          });
+        }
+        if (!titleTerms.hasOwnProperty(word)) {
+          Object.keys(titleTerms).forEach((term) => {
+            if (term.match(escapedWord))
+              arr.push({ files: titleTerms[term], score: Scorer.partialTitle });
+          });
+        }
+      }
+
+      // no match but word was a required one
+      if (arr.every((record) => record.files === undefined)) return;
+
+      // found search word in contents
+      arr.forEach((record) => {
+        if (record.files === undefined) return;
+
+        let recordFiles = record.files;
+        if (recordFiles.length === undefined) recordFiles = [recordFiles];
+        files.push(...recordFiles);
+
+        // set score for the word in each file
+        recordFiles.forEach((file) => {
+          if (!scoreMap.has(file)) scoreMap.set(file, {});
+          scoreMap.get(file)[word] = record.score;
+        });
+      });
+
+      // create the mapping
+      files.forEach((file) => {
+        if (!fileMap.has(file)) fileMap.set(file, [word]);
+        else if (fileMap.get(file).indexOf(word) === -1) fileMap.get(file).push(word);
+      });
+    });
+
+    // now check if the files don't contain excluded terms
+    const results = [];
+    for (const [file, wordList] of fileMap) {
+      // check if all requirements are matched
+
+      // as search terms with length < 3 are discarded
+      const filteredTermCount = [...searchTerms].filter(
+        (term) => term.length > 2
+      ).length;
+      if (
+        wordList.length !== searchTerms.size &&
+        wordList.length !== filteredTermCount
+      )
+        continue;
+
+      // ensure that none of the excluded terms is in the search result
+      if (
+        [...excludedTerms].some(
+          (term) =>
+            terms[term] === file ||
+            titleTerms[term] === file ||
+            (terms[term] || []).includes(file) ||
+            (titleTerms[term] || []).includes(file)
+        )
+      )
+        break;
+
+      // select one (max) score for the file.
+      const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w]));
+      // add result to the result list
+      results.push([
+        docNames[file],
+        titles[file],
+        "",
+        null,
+        score,
+        filenames[file],
+      ]);
+    }
+    return results;
+  },
+
+  /**
+   * helper function to return a node containing the
+   * search summary for a given text. keywords is a list
+   * of stemmed words.
+   */
+  makeSearchSummary: (htmlText, keywords, anchor) => {
+    const text = Search.htmlToText(htmlText, anchor);
+    if (text === "") return null;
+
+    const textLower = text.toLowerCase();
+    const actualStartPosition = [...keywords]
+      .map((k) => textLower.indexOf(k.toLowerCase()))
+      .filter((i) => i > -1)
+      .slice(-1)[0];
+    const startWithContext = Math.max(actualStartPosition - 120, 0);
+
+    const top = startWithContext === 0 ? "" : "...";
+    const tail = startWithContext + 240 < text.length ? "..." : "";
+
+    let summary = document.createElement("p");
+    summary.classList.add("context");
+    summary.textContent = top + text.substr(startWithContext, 240).trim() + tail;
+
+    return summary;
+  },
+};
+
+_ready(Search.init);
diff --git a/_static/sphinx_highlight.js b/_static/sphinx_highlight.js
new file mode 100644
index 0000000..8a96c69
--- /dev/null
+++ b/_static/sphinx_highlight.js
@@ -0,0 +1,154 @@
+/* Highlighting utilities for Sphinx HTML documentation. */
+"use strict";
+
+const SPHINX_HIGHLIGHT_ENABLED = true
+
+/**
+ * highlight a given string on a node by wrapping it in
+ * span elements with the given class name.
+ */
+const _highlight = (node, addItems, text, className) => {
+  if (node.nodeType === Node.TEXT_NODE) {
+    const val = node.nodeValue;
+    const parent = node.parentNode;
+    const pos = val.toLowerCase().indexOf(text);
+    if (
+      pos >= 0 &&
+      !parent.classList.contains(className) &&
+      !parent.classList.contains("nohighlight")
+    ) {
+      let span;
+
+      const closestNode = parent.closest("body, svg, foreignObject");
+      const isInSVG = closestNode && closestNode.matches("svg");
+      if (isInSVG) {
+        span = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
+      } else {
+        span = document.createElement("span");
+        span.classList.add(className);
+      }
+
+      span.appendChild(document.createTextNode(val.substr(pos, text.length)));
+      const rest = document.createTextNode(val.substr(pos + text.length));
+      parent.insertBefore(
+        span,
+        parent.insertBefore(
+          rest,
+          node.nextSibling
+        )
+      );
+      node.nodeValue = val.substr(0, pos);
+      /* There may be more occurrences of search term in this node. So call this
+       * function recursively on the remaining fragment.
+       */
+      _highlight(rest, addItems, text, className);
+
+      if (isInSVG) {
+        const rect = document.createElementNS(
+          "http://www.w3.org/2000/svg",
+          "rect"
+        );
+        const bbox = parent.getBBox();
+        rect.x.baseVal.value = bbox.x;
+        rect.y.baseVal.value = bbox.y;
+        rect.width.baseVal.value = bbox.width;
+        rect.height.baseVal.value = bbox.height;
+        rect.setAttribute("class", className);
+        addItems.push({ parent: parent, target: rect });
+      }
+    }
+  } else if (node.matches && !node.matches("button, select, textarea")) {
+    node.childNodes.forEach((el) => _highlight(el, addItems, text, className));
+  }
+};
+const _highlightText = (thisNode, text, className) => {
+  let addItems = [];
+  _highlight(thisNode, addItems, text, className);
+  addItems.forEach((obj) =>
+    obj.parent.insertAdjacentElement("beforebegin", obj.target)
+  );
+};
+
+/**
+ * Small JavaScript module for the documentation.
+ */
+const SphinxHighlight = {
+
+  /**
+   * highlight the search words provided in localstorage in the text
+   */
+  highlightSearchWords: () => {
+    if (!SPHINX_HIGHLIGHT_ENABLED) return;  // bail if no highlight
+
+    // get and clear terms from localstorage
+    const url = new URL(window.location);
+    const highlight =
+        localStorage.getItem("sphinx_highlight_terms")
+        || url.searchParams.get("highlight")
+        || "";
+    localStorage.removeItem("sphinx_highlight_terms")
+    url.searchParams.delete("highlight");
+    window.history.replaceState({}, "", url);
+
+    // get individual terms from highlight string
+    const terms = highlight.toLowerCase().split(/\s+/).filter(x => x);
+    if (terms.length === 0) return; // nothing to do
+
+    // There should never be more than one element matching "div.body"
+    const divBody = document.querySelectorAll("div.body");
+    const body = divBody.length ? divBody[0] : document.querySelector("body");
+    window.setTimeout(() => {
+      terms.forEach((term) => _highlightText(body, term, "highlighted"));
+    }, 10);
+
+    const searchBox = document.getElementById("searchbox");
+    if (searchBox === null) return;
+    searchBox.appendChild(
+      document
+        .createRange()
+        .createContextualFragment(
+          '<p class="highlight-link">' +
+            '<a href="javascript:SphinxHighlight.hideSearchWords()">' +
+            _("Hide Search Matches") +
+            "</a></p>"
+        )
+    );
+  },
+
+  /**
+   * helper function to hide the search marks again
+   */
+  hideSearchWords: () => {
+    document
+      .querySelectorAll("#searchbox .highlight-link")
+      .forEach((el) => el.remove());
+    document
+      .querySelectorAll("span.highlighted")
+      .forEach((el) => el.classList.remove("highlighted"));
+    localStorage.removeItem("sphinx_highlight_terms")
+  },
+
+  initEscapeListener: () => {
+    // only install a listener if it is really needed
+    if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return;
+
+    document.addEventListener("keydown", (event) => {
+      // bail for input elements
+      if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return;
+      // bail with special keys
+      if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return;
+      if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) {
+        SphinxHighlight.hideSearchWords();
+        event.preventDefault();
+      }
+    });
+  },
+};
+
+_ready(() => {
+  /* Do not call highlightSearchWords() when we are on the search page.
+   * It will highlight words from the *previous* search query.
+   */
+  if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords();
+  SphinxHighlight.initEscapeListener();
+});
diff --git a/_static/sphinx_toolbox_installation.css b/_static/sphinx_toolbox_installation.css
new file mode 100644
index 0000000..4a073b1
--- /dev/null
+++ b/_static/sphinx_toolbox_installation.css
@@ -0,0 +1 @@
+div[id*="installation"] .sphinx-tabs-tab{color:#2980b9}button.sphinx-tabs-tab,div.sphinx-tabs-panel{outline:None !important}
diff --git a/_static/sphinx_toolbox_installation.js b/_static/sphinx_toolbox_installation.js
new file mode 100644
index 0000000..a1950f4
--- /dev/null
+++ b/_static/sphinx_toolbox_installation.js
@@ -0,0 +1,41 @@
+// Based on https://github.com/executablebooks/sphinx-tabs/blob/master/sphinx_tabs/static/tabs.js
+// Copyright (c) 2017 djungelorm
+// MIT Licensed
+
+function deselectTabset(target) {
+  const parent = target.parentNode;
+  const grandparent = parent.parentNode;
+
+  if (parent.parentNode.parentNode.getAttribute("id").startsWith("installation")) {
+
+    // Hide all tabs in current tablist, but not nested
+    Array.from(parent.children).forEach(t => {
+      if (t.getAttribute("name") !== target.getAttribute("name")) {
+        t.setAttribute("aria-selected", "false");
+      }
+    });
+
+    // Hide all associated panels
+    Array.from(grandparent.children).slice(1).forEach(p => {  // Skip tablist
+      if (p.getAttribute("name") !== target.getAttribute("name")) {
+        p.setAttribute("hidden", "false")
+      }
+    });
+  }
+
+  else {
+    // Hide all tabs in current tablist, but not nested
+    Array.from(parent.children).forEach(t => {
+      t.setAttribute("aria-selected", "false");
+    });
+
+    // Hide all associated panels
+    Array.from(grandparent.children).slice(1).forEach(p => {  // Skip tablist
+      p.setAttribute("hidden", "true")
+    });
+  }
+
+}
+
+// Compatibility with sphinx-tabs 2.1.0 and later
+function deselectTabList(tab) {deselectTabset(tab)}
diff --git a/_static/style.css b/_static/style.css
new file mode 100644
index 0000000..38ab837
--- /dev/null
+++ b/_static/style.css
@@ -0,0 +1,38 @@
+.rst-content .objectives {
+    background: #fee0d2;
+}
+.rst-content .objectives > .admonition-title {
+    background: #fc9272;
+}
+
+
+.rst-content .prereq {
+    background: #fee0d2;
+}
+.rst-content .prereq > .admonition-title {
+    background: #fc9272;
+}
+
+
+.rst-content .instructor-note {
+    background: #f0f0f0;
+}
+.rst-content .instructor-note > .admonition-title {
+    background: #bdbdbd;
+}
+
+
+.rst-content .keypoints {
+    background: #e5f5e0;
+}
+.rst-content .keypoints > .admonition-title {
+    background: #a1d99b;
+}
+
+
+.rst-content .discussion {
+    background: #fee6ce;
+}
+.rst-content .discussion > .admonition-title {
+    background: #fdae6b;
+}
diff --git a/_static/styles/bootstrap.css b/_static/styles/bootstrap.css
new file mode 100644
index 0000000..82b03c0
--- /dev/null
+++ b/_static/styles/bootstrap.css
@@ -0,0 +1,6 @@
+/*!
+ * Bootstrap  v5.3.2 (https://getbootstrap.com/)
+ * Copyright 2011-2023 The Bootstrap Authors
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)
+ */:root,[data-bs-theme=light]{--bs-blue:#0d6efd;--bs-indigo:#6610f2;--bs-purple:#6f42c1;--bs-pink:#d63384;--bs-red:#dc3545;--bs-orange:#fd7e14;--bs-yellow:#ffc107;--bs-green:#198754;--bs-teal:#20c997;--bs-cyan:#0dcaf0;--bs-black:#000;--bs-white:#fff;--bs-gray:#6c757d;--bs-gray-dark:#343a40;--bs-gray-100:#f8f9fa;--bs-gray-200:#e9ecef;--bs-gray-300:#dee2e6;--bs-gray-400:#ced4da;--bs-gray-500:#adb5bd;--bs-gray-600:#6c757d;--bs-gray-700:#495057;--bs-gray-800:#343a40;--bs-gray-900:#212529;--bs-primary:#0d6efd;--bs-secondary:#6c757d;--bs-success:#198754;--bs-info:#0dcaf0;--bs-warning:#ffc107;--bs-danger:#dc3545;--bs-light:#f8f9fa;--bs-dark:#212529;--bs-primary-rgb:13,110,253;--bs-secondary-rgb:108,117,125;--bs-success-rgb:25,135,84;--bs-info-rgb:13,202,240;--bs-warning-rgb:255,193,7;--bs-danger-rgb:220,53,69;--bs-light-rgb:248,249,250;--bs-dark-rgb:33,37,41;--bs-primary-text-emphasis:#052c65;--bs-secondary-text-emphasis:#2b2f32;--bs-success-text-emphasis:#0a3622;--bs-info-text-emphasis:#055160;--bs-warning-text-emphasis:#664d03;--bs-danger-text-emphasis:#58151c;--bs-light-text-emphasis:#495057;--bs-dark-text-emphasis:#495057;--bs-primary-bg-subtle:#cfe2ff;--bs-secondary-bg-subtle:#e2e3e5;--bs-success-bg-subtle:#d1e7dd;--bs-info-bg-subtle:#cff4fc;--bs-warning-bg-subtle:#fff3cd;--bs-danger-bg-subtle:#f8d7da;--bs-light-bg-subtle:#fcfcfd;--bs-dark-bg-subtle:#ced4da;--bs-primary-border-subtle:#9ec5fe;--bs-secondary-border-subtle:#c4c8cb;--bs-success-border-subtle:#a3cfbb;--bs-info-border-subtle:#9eeaf9;--bs-warning-border-subtle:#ffe69c;--bs-danger-border-subtle:#f1aeb5;--bs-light-border-subtle:#e9ecef;--bs-dark-border-subtle:#adb5bd;--bs-white-rgb:255,255,255;--bs-black-rgb:0,0,0;--bs-font-sans-serif:system-ui,-apple-system,"Segoe UI",Roboto,"Helvetica Neue","Noto Sans","Liberation Sans",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol","Noto Color Emoji";--bs-font-monospace:SFMono-Regular,Menlo,Monaco,Consolas,"Liberation Mono","Courier 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.offcanvas{background-color:transparent!important;border:0!important;flex-grow:1;height:auto!important;position:static;transform:none!important;transition:none;visibility:visible!important;width:auto!important;z-index:auto}.navbar-expand .offcanvas .offcanvas-header{display:none}.navbar-expand .offcanvas .offcanvas-body{display:flex;flex-grow:0;overflow-y:visible;padding:0}.navbar-dark,.navbar[data-bs-theme=dark]{--bs-navbar-color:hsla(0,0%,100%,.55);--bs-navbar-hover-color:hsla(0,0%,100%,.75);--bs-navbar-disabled-color:hsla(0,0%,100%,.25);--bs-navbar-active-color:#fff;--bs-navbar-brand-color:#fff;--bs-navbar-brand-hover-color:#fff;--bs-navbar-toggler-border-color:hsla(0,0%,100%,.1)}.navbar-dark,.navbar[data-bs-theme=dark],[data-bs-theme=dark] .navbar-toggler-icon{--bs-navbar-toggler-icon-bg:url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3E%3Cpath stroke='rgba(255, 255, 255, 0.55)' stroke-linecap='round' stroke-miterlimit='10' 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xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23052c65'%3E%3Cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3E%3C/svg%3E");--bs-accordion-btn-focus-border-color:#86b7fe;--bs-accordion-btn-focus-box-shadow:0 0 0 0.25rem rgba(13,110,253,.25);--bs-accordion-body-padding-x:1.25rem;--bs-accordion-body-padding-y:1rem;--bs-accordion-active-color:var(--bs-primary-text-emphasis);--bs-accordion-active-bg:var(--bs-primary-bg-subtle)}.accordion-button{align-items:center;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;color:var(--bs-accordion-btn-color);display:flex;font-size:1rem;overflow-anchor:none;padding:var(--bs-accordion-btn-padding-y) 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var(--bs-accordion-border-color);color:var(--bs-accordion-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-left-radius:var(--bs-accordion-border-radius);border-bottom-right-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-left-radius:var(--bs-accordion-inner-border-radius);border-bottom-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-left-radius:var(--bs-accordion-border-radius);border-bottom-right-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-left:0;border-radius:0;border-right:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme=dark] .accordion-button:after{--bs-accordion-btn-icon:url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3E%3Cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3E%3C/svg%3E");--bs-accordion-btn-active-icon:url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3E%3Cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3E%3C/svg%3E")}.breadcrumb{--bs-breadcrumb-padding-x:0;--bs-breadcrumb-padding-y:0;--bs-breadcrumb-margin-bottom:1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color:var(--bs-secondary-color);--bs-breadcrumb-item-padding-x:0.5rem;--bs-breadcrumb-item-active-color:var(--bs-secondary-color);background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius);display:flex;flex-wrap:wrap;font-size:var(--bs-breadcrumb-font-size);list-style:none;margin-bottom:var(--bs-breadcrumb-margin-bottom);padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item:before{color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider,"/");float:left;padding-right:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x:0.75rem;--bs-pagination-padding-y:0.375rem;--bs-pagination-font-size:1rem;--bs-pagination-color:var(--bs-link-color);--bs-pagination-bg:var(--bs-body-bg);--bs-pagination-border-width:var(--bs-border-width);--bs-pagination-border-color:var(--bs-border-color);--bs-pagination-border-radius:var(--bs-border-radius);--bs-pagination-hover-color:var(--bs-link-hover-color);--bs-pagination-hover-bg:var(--bs-tertiary-bg);--bs-pagination-hover-border-color:var(--bs-border-color);--bs-pagination-focus-color:var(--bs-link-hover-color);--bs-pagination-focus-bg:var(--bs-secondary-bg);--bs-pagination-focus-box-shadow:0 0 0 0.25rem rgba(13,110,253,.25);--bs-pagination-active-color:#fff;--bs-pagination-active-bg:#0d6efd;--bs-pagination-active-border-color:#0d6efd;--bs-pagination-disabled-color:var(--bs-secondary-color);--bs-pagination-disabled-bg:var(--bs-secondary-bg);--bs-pagination-disabled-border-color:var(--bs-border-color);display:flex;list-style:none;padding-left:0}.page-link{background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);color:var(--bs-pagination-color);display:block;font-size:var(--bs-pagination-font-size);padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);position:relative;text-decoration:none;transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out}@media(prefers-reduced-motion:reduce){.page-link{transition:none}}.page-link:hover{background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color);color:var(--bs-pagination-hover-color);z-index:2}.page-link:focus{background-color:var(--bs-pagination-focus-bg);box-shadow:var(--bs-pagination-focus-box-shadow);color:var(--bs-pagination-focus-color);outline:0;z-index:3}.active>.page-link,.page-link.active{background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color);color:var(--bs-pagination-active-color);z-index:3}.disabled>.page-link,.page-link.disabled{background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color);color:var(--bs-pagination-disabled-color);pointer-events:none}.page-item:not(:first-child) .page-link{margin-left:calc(var(--bs-border-width)*-1)}.page-item:first-child .page-link{border-bottom-left-radius:var(--bs-pagination-border-radius);border-top-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-bottom-right-radius:var(--bs-pagination-border-radius);border-top-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x:1.5rem;--bs-pagination-padding-y:0.75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius:var(--bs-border-radius-lg)}.pagination-sm{--bs-pagination-padding-x:0.5rem;--bs-pagination-padding-y:0.25rem;--bs-pagination-font-size:0.875rem;--bs-pagination-border-radius:var(--bs-border-radius-sm)}.badge{--bs-badge-padding-x:0.65em;--bs-badge-padding-y:0.35em;--bs-badge-font-size:0.75em;--bs-badge-font-weight:700;--bs-badge-color:#fff;--bs-badge-border-radius:var(--bs-border-radius);border-radius:var(--bs-badge-border-radius);color:var(--bs-badge-color);display:inline-block;font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);text-align:center;vertical-align:baseline;white-space:nowrap}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg:transparent;--bs-alert-padding-x:1rem;--bs-alert-padding-y:1rem;--bs-alert-margin-bottom:1rem;--bs-alert-color:inherit;--bs-alert-border-color:transparent;--bs-alert-border:var(--bs-border-width) solid var(--bs-alert-border-color);--bs-alert-border-radius:var(--bs-border-radius);--bs-alert-link-color:inherit;background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius);color:var(--bs-alert-color);margin-bottom:var(--bs-alert-margin-bottom);padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);position:relative}.alert-heading{color:inherit}.alert-link{color:var(--bs-alert-link-color);font-weight:700}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{padding:1.25rem 1rem;position:absolute;right:0;top:0;z-index:2}.alert-primary{--bs-alert-color:var(--bs-primary-text-emphasis);--bs-alert-bg:var(--bs-primary-bg-subtle);--bs-alert-border-color:var(--bs-primary-border-subtle);--bs-alert-link-color:var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color:var(--bs-secondary-text-emphasis);--bs-alert-bg:var(--bs-secondary-bg-subtle);--bs-alert-border-color:var(--bs-secondary-border-subtle);--bs-alert-link-color:var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color:var(--bs-success-text-emphasis);--bs-alert-bg:var(--bs-success-bg-subtle);--bs-alert-border-color:var(--bs-success-border-subtle);--bs-alert-link-color:var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color:var(--bs-info-text-emphasis);--bs-alert-bg:var(--bs-info-bg-subtle);--bs-alert-border-color:var(--bs-info-border-subtle);--bs-alert-link-color:var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color:var(--bs-warning-text-emphasis);--bs-alert-bg:var(--bs-warning-bg-subtle);--bs-alert-border-color:var(--bs-warning-border-subtle);--bs-alert-link-color:var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color:var(--bs-danger-text-emphasis);--bs-alert-bg:var(--bs-danger-bg-subtle);--bs-alert-border-color:var(--bs-danger-border-subtle);--bs-alert-link-color:var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color:var(--bs-light-text-emphasis);--bs-alert-bg:var(--bs-light-bg-subtle);--bs-alert-border-color:var(--bs-light-border-subtle);--bs-alert-link-color:var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color:var(--bs-dark-text-emphasis);--bs-alert-bg:var(--bs-dark-bg-subtle);--bs-alert-border-color:var(--bs-dark-border-subtle);--bs-alert-link-color:var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height:1rem;--bs-progress-font-size:0.75rem;--bs-progress-bg:var(--bs-secondary-bg);--bs-progress-border-radius:var(--bs-border-radius);--bs-progress-box-shadow:var(--bs-box-shadow-inset);--bs-progress-bar-color:#fff;--bs-progress-bar-bg:#0d6efd;--bs-progress-bar-transition:width 0.6s ease;background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius);display:flex;font-size:var(--bs-progress-font-size);height:var(--bs-progress-height);overflow:hidden}.progress-bar{background-color:var(--bs-progress-bar-bg);color:var(--bs-progress-bar-color);display:flex;flex-direction:column;justify-content:center;overflow:hidden;text-align:center;transition:var(--bs-progress-bar-transition);white-space:nowrap}@media(prefers-reduced-motion:reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg,hsla(0,0%,100%,.15) 25%,transparent 0,transparent 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0)}.dropdown-item:hover,.dropdown-item:focus{color:var(--bs-dropdown-link-hover-color);background-color:var(--bs-dropdown-link-hover-bg)}.dropdown-item.active,.dropdown-item:active{color:var(--bs-dropdown-link-active-color);text-decoration:none;background-color:var(--bs-dropdown-link-active-bg)}.dropdown-item.disabled,.dropdown-item:disabled{color:var(--bs-dropdown-link-disabled-color);pointer-events:none;background-color:rgba(0,0,0,0)}.dropdown-menu.show{display:block}.dropdown-header{display:block;padding:var(--bs-dropdown-header-padding-y) var(--bs-dropdown-header-padding-x);margin-bottom:0;font-size:0.875rem;color:var(--bs-dropdown-header-color);white-space:nowrap}.dropdown-item-text{display:block;padding:var(--bs-dropdown-item-padding-y) var(--bs-dropdown-item-padding-x);color:var(--bs-dropdown-link-color)}.dropdown-menu-dark{--bs-dropdown-color: #dee2e6;--bs-dropdown-bg: #343a40;--bs-dropdown-border-color: var(--bs-border-color-translucent);--bs-dropdown-box-shadow: ;--bs-dropdown-link-color: #dee2e6;--bs-dropdown-link-hover-color: #fff;--bs-dropdown-divider-bg: var(--bs-border-color-translucent);--bs-dropdown-link-hover-bg: var(--pst-color-surface);--bs-dropdown-link-active-color: #fff;--bs-dropdown-link-active-bg: var(--pst-color-surface);--bs-dropdown-link-disabled-color: #adb5bd;--bs-dropdown-header-color: #adb5bd}.btn-group,.btn-group-vertical{position:relative;display:inline-flex;vertical-align:middle}.btn-group>.btn,.btn-group-vertical>.btn{position:relative;flex:1 1 auto}.btn-group>.btn-check:checked+.btn,.btn-group>.btn-check:focus+.btn,.btn-group>.btn:hover,.btn-group>.btn:focus,.btn-group>.btn:active,.btn-group>.btn.active,.btn-group-vertical>.btn-check:checked+.btn,.btn-group-vertical>.btn-check:focus+.btn,.btn-group-vertical>.btn:hover,.btn-group-vertical>.btn:focus,.btn-group-vertical>.btn:active,.btn-group-vertical>.btn.active{z-index:1}.btn-toolbar{display:flex;flex-wrap:wrap;justify-content:flex-start}.btn-toolbar .input-group{width:auto}.btn-group{border-radius:var(--bs-border-radius)}.btn-group>:not(.btn-check:first-child)+.btn,.btn-group>.btn-group:not(:first-child){margin-left:calc(var(--bs-border-width)*-1)}.btn-group>.btn:not(:last-child):not(.dropdown-toggle),.btn-group>.btn.dropdown-toggle-split:first-child,.btn-group>.btn-group:not(:last-child)>.btn{border-top-right-radius:0;border-bottom-right-radius:0}.btn-group>.btn:nth-child(n+3),.btn-group>:not(.btn-check)+.btn,.btn-group>.btn-group:not(:first-child)>.btn{border-top-left-radius:0;border-bottom-left-radius:0}.dropdown-toggle-split{padding-right:.5625rem;padding-left:.5625rem}.dropdown-toggle-split::after,.dropup .dropdown-toggle-split::after,.dropend .dropdown-toggle-split::after{margin-left:0}.dropstart .dropdown-toggle-split::before{margin-right:0}.btn-sm+.dropdown-toggle-split,.btn-group-sm>.btn+.dropdown-toggle-split{padding-right:.375rem;padding-left:.375rem}.btn-lg+.dropdown-toggle-split,.btn-group-lg>.btn+.dropdown-toggle-split{padding-right:.75rem;padding-left:.75rem}.btn-group-vertical{flex-direction:column;align-items:flex-start;justify-content:center}.btn-group-vertical>.btn,.btn-group-vertical>.btn-group{width:100%}.btn-group-vertical>.btn:not(:first-child),.btn-group-vertical>.btn-group:not(:first-child){margin-top:calc(var(--bs-border-width)*-1)}.btn-group-vertical>.btn:not(:last-child):not(.dropdown-toggle),.btn-group-vertical>.btn-group:not(:last-child)>.btn{border-bottom-right-radius:0;border-bottom-left-radius:0}.btn-group-vertical>.btn~.btn,.btn-group-vertical>.btn-group:not(:first-child)>.btn{border-top-left-radius:0;border-top-right-radius:0}.nav{--bs-nav-link-padding-x: 1rem;--bs-nav-link-padding-y: 0.5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: 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1.25rem;--bs-navbar-brand-color: rgba(var(--bs-emphasis-color-rgb), 1);--bs-navbar-brand-hover-color: rgba(var(--bs-emphasis-color-rgb), 1);--bs-navbar-nav-link-padding-x: 0.5rem;--bs-navbar-toggler-padding-y: 0.25rem;--bs-navbar-toggler-padding-x: 0.75rem;--bs-navbar-toggler-font-size: 1.25rem;--bs-navbar-toggler-icon-bg: url(\"data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%2833, 37, 41, 0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e\");--bs-navbar-toggler-border-color: rgba(var(--bs-emphasis-color-rgb), 0.15);--bs-navbar-toggler-border-radius: var(--bs-border-radius);--bs-navbar-toggler-focus-width: 0.25rem;--bs-navbar-toggler-transition: box-shadow 0.15s ease-in-out;position:relative;display:flex;flex-wrap:wrap;align-items:center;justify-content:space-between;padding:var(--bs-navbar-padding-y) 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.offcanvas-body{display:flex;flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;flex-basis:auto}.navbar-expand .navbar-toggler{display:none}.navbar-expand .offcanvas{position:static;z-index:auto;flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:rgba(0,0,0,0) !important;border:0 !important;transform:none !important;transition:none}.navbar-expand .offcanvas .offcanvas-header{display:none}.navbar-expand .offcanvas .offcanvas-body{display:flex;flex-grow:0;padding:0;overflow-y:visible}.navbar-dark,.navbar[data-bs-theme=dark]{--bs-navbar-color: rgba(255, 255, 255, 0.55);--bs-navbar-hover-color: rgba(255, 255, 255, 0.75);--bs-navbar-disabled-color: rgba(255, 255, 255, 0.25);--bs-navbar-active-color: #fff;--bs-navbar-brand-color: #fff;--bs-navbar-brand-hover-color: #fff;--bs-navbar-toggler-border-color: rgba(255, 255, 255, 0.1);--bs-navbar-toggler-icon-bg: url(\"data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255, 255, 255, 0.55%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e\")}[data-bs-theme=dark] .navbar-toggler-icon{--bs-navbar-toggler-icon-bg: url(\"data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255, 255, 255, 0.55%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e\")}.card{--bs-card-spacer-y: 1rem;--bs-card-spacer-x: 1rem;--bs-card-title-spacer-y: 0.5rem;--bs-card-title-color: ;--bs-card-subtitle-color: ;--bs-card-border-width: var(--bs-border-width);--bs-card-border-color: var(--bs-border-color-translucent);--bs-card-border-radius: var(--bs-border-radius);--bs-card-box-shadow: ;--bs-card-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-card-cap-padding-y: 0.5rem;--bs-card-cap-padding-x: 1rem;--bs-card-cap-bg: rgba(var(--bs-body-color-rgb), 0.03);--bs-card-cap-color: ;--bs-card-height: ;--bs-card-color: ;--bs-card-bg: var(--bs-body-bg);--bs-card-img-overlay-padding: 1rem;--bs-card-group-margin: 0.75rem;position:relative;display:flex;flex-direction:column;min-width:0;height:var(--bs-card-height);color:var(--bs-body-color);word-wrap:break-word;background-color:var(--bs-card-bg);background-clip:border-box;border:var(--bs-card-border-width) solid var(--bs-card-border-color);border-radius:var(--bs-card-border-radius)}.card>hr{margin-right:0;margin-left:0}.card>.list-group{border-top:inherit;border-bottom:inherit}.card>.list-group:first-child{border-top-width:0;border-top-left-radius:var(--bs-card-inner-border-radius);border-top-right-radius:var(--bs-card-inner-border-radius)}.card>.list-group:last-child{border-bottom-width:0;border-bottom-right-radius:var(--bs-card-inner-border-radius);border-bottom-left-radius:var(--bs-card-inner-border-radius)}.card>.card-header+.list-group,.card>.list-group+.card-footer{border-top:0}.card-body{flex:1 1 auto;padding:var(--bs-card-spacer-y) var(--bs-card-spacer-x);color:var(--bs-card-color)}.card-title{margin-bottom:var(--bs-card-title-spacer-y);color:var(--bs-card-title-color)}.card-subtitle{margin-top:calc(-0.5*var(--bs-card-title-spacer-y));margin-bottom:0;color:var(--bs-card-subtitle-color)}.card-text:last-child{margin-bottom:0}.card-link+.card-link{margin-left:var(--bs-card-spacer-x)}.card-header{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);margin-bottom:0;color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-bottom:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-header:first-child{border-radius:var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius) 0 0}.card-footer{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-top:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-footer:last-child{border-radius:0 0 var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius)}.card-header-tabs{margin-right:calc(-0.5*var(--bs-card-cap-padding-x));margin-bottom:calc(-1*var(--bs-card-cap-padding-y));margin-left:calc(-0.5*var(--bs-card-cap-padding-x));border-bottom:0}.card-header-tabs .nav-link.active{background-color:var(--bs-card-bg);border-bottom-color:var(--bs-card-bg)}.card-header-pills{margin-right:calc(-0.5*var(--bs-card-cap-padding-x));margin-left:calc(-0.5*var(--bs-card-cap-padding-x))}.card-img-overlay{position:absolute;top:0;right:0;bottom:0;left:0;padding:var(--bs-card-img-overlay-padding);border-radius:var(--bs-card-inner-border-radius)}.card-img,.card-img-top,.card-img-bottom{width:100%}.card-img,.card-img-top{border-top-left-radius:var(--bs-card-inner-border-radius);border-top-right-radius:var(--bs-card-inner-border-radius)}.card-img,.card-img-bottom{border-bottom-right-radius:var(--bs-card-inner-border-radius);border-bottom-left-radius:var(--bs-card-inner-border-radius)}.card-group>.card{margin-bottom:var(--bs-card-group-margin)}@media(min-width: 540px){.card-group{display:flex;flex-flow:row wrap}.card-group>.card{flex:1 0 0%;margin-bottom:0}.card-group>.card+.card{margin-left:0;border-left:0}.card-group>.card:not(:last-child){border-top-right-radius:0;border-bottom-right-radius:0}.card-group>.card:not(:last-child) .card-img-top,.card-group>.card:not(:last-child) .card-header{border-top-right-radius:0}.card-group>.card:not(:last-child) .card-img-bottom,.card-group>.card:not(:last-child) .card-footer{border-bottom-right-radius:0}.card-group>.card:not(:first-child){border-top-left-radius:0;border-bottom-left-radius:0}.card-group>.card:not(:first-child) .card-img-top,.card-group>.card:not(:first-child) .card-header{border-top-left-radius:0}.card-group>.card:not(:first-child) .card-img-bottom,.card-group>.card:not(:first-child) .card-footer{border-bottom-left-radius:0}}.accordion{--bs-accordion-color: var(--bs-body-color);--bs-accordion-bg: var(--bs-body-bg);--bs-accordion-transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out, border-radius 0.15s ease;--bs-accordion-border-color: var(--bs-border-color);--bs-accordion-border-width: var(--bs-border-width);--bs-accordion-border-radius: var(--bs-border-radius);--bs-accordion-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: var(--bs-body-color);--bs-accordion-btn-bg: var(--bs-accordion-bg);--bs-accordion-btn-icon: url(\"data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23212529'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e\");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url(\"data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23052c65'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e\");--bs-accordion-btn-focus-border-color: #86b7fe;--bs-accordion-btn-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: var(--bs-primary-text-emphasis);--bs-accordion-active-bg: var(--bs-primary-bg-subtle)}.accordion-button{position:relative;display:flex;align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media(prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1*var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:\"\";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media(prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme=dark] .accordion-button::after{--bs-accordion-btn-icon: url(\"data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e\");--bs-accordion-btn-active-icon: url(\"data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e\")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: var(--bs-secondary-color);--bs-breadcrumb-item-padding-x: 0.5rem;--bs-breadcrumb-item-active-color: var(--bs-secondary-color);display:flex;flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, \"/\") /* rtl: var(--bs-breadcrumb-divider, \"/\") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: 0.75rem;--bs-pagination-padding-y: 0.375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: var(--bs-link-color);--bs-pagination-bg: var(--bs-body-bg);--bs-pagination-border-width: var(--bs-border-width);--bs-pagination-border-color: var(--bs-border-color);--bs-pagination-border-radius: var(--bs-border-radius);--bs-pagination-hover-color: var(--bs-link-hover-color);--bs-pagination-hover-bg: var(--bs-tertiary-bg);--bs-pagination-hover-border-color: var(--bs-border-color);--bs-pagination-focus-color: var(--bs-link-hover-color);--bs-pagination-focus-bg: var(--bs-secondary-bg);--bs-pagination-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-pagination-active-color: #fff;--bs-pagination-active-bg: #0d6efd;--bs-pagination-active-border-color: #0d6efd;--bs-pagination-disabled-color: var(--bs-secondary-color);--bs-pagination-disabled-bg: var(--bs-secondary-bg);--bs-pagination-disabled-border-color: var(--bs-border-color);display:flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out}@media(prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(var(--bs-border-width)*-1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: 0.75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: var(--bs-border-radius-lg)}.pagination-sm{--bs-pagination-padding-x: 0.5rem;--bs-pagination-padding-y: 0.25rem;--bs-pagination-font-size:0.875rem;--bs-pagination-border-radius: var(--bs-border-radius-sm)}.badge{--bs-badge-padding-x: 0.65em;--bs-badge-padding-y: 0.35em;--bs-badge-font-size:0.75em;--bs-badge-font-weight: 700;--bs-badge-color: #fff;--bs-badge-border-radius: var(--bs-border-radius);display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: var(--bs-border-width) solid var(--bs-alert-border-color);--bs-alert-border-radius: var(--bs-border-radius);--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:0.75rem;--bs-progress-bg: var(--bs-secondary-bg);--bs-progress-border-radius: var(--bs-border-radius);--bs-progress-box-shadow: var(--bs-box-shadow-inset);--bs-progress-bar-color: #fff;--bs-progress-bar-bg: #0d6efd;--bs-progress-bar-transition: width 0.6s ease;display:flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;flex-direction:column;justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media(prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media(prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: var(--bs-body-color);--bs-list-group-bg: var(--bs-body-bg);--bs-list-group-border-color: var(--bs-border-color);--bs-list-group-border-width: var(--bs-border-width);--bs-list-group-border-radius: var(--bs-border-radius);--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: 0.5rem;--bs-list-group-action-color: var(--bs-secondary-color);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-tertiary-bg);--bs-list-group-action-active-color: var(--bs-body-color);--bs-list-group-action-active-bg: var(--bs-secondary-bg);--bs-list-group-disabled-color: var(--bs-secondary-color);--bs-list-group-disabled-bg: var(--bs-body-bg);--bs-list-group-active-color: #fff;--bs-list-group-active-bg: #0d6efd;--bs-list-group-active-border-color: 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var(--bs-list-group-border-color)}.list-group-item:first-child{border-top-left-radius:inherit;border-top-right-radius:inherit}.list-group-item:last-child{border-bottom-right-radius:inherit;border-bottom-left-radius:inherit}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1*var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row}.list-group-horizontal>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media(min-width: 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960px){.list-group-horizontal-lg{flex-direction:row}.list-group-horizontal-lg>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-lg>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1200px){.list-group-horizontal-xl{flex-direction:row}.list-group-horizontal-xl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush{border-radius:0}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url(\"data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/%3e%3c/svg%3e\");--bs-btn-close-opacity: 0.5;--bs-btn-close-hover-opacity: 0.75;--bs-btn-close-focus-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-btn-close-focus-opacity: 1;--bs-btn-close-disabled-opacity: 0.25;--bs-btn-close-white-filter: invert(1) grayscale(100%) brightness(200%);box-sizing:content-box;width:1em;height:1em;padding:.25em .25em;color:var(--bs-btn-close-color);background:rgba(0,0,0,0) var(--bs-btn-close-bg) center/1em auto 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calc(var(--bs-border-radius-lg) - (var(--bs-border-width)));--bs-modal-header-padding-x: 1rem;--bs-modal-header-padding-y: 1rem;--bs-modal-header-padding: 1rem 1rem;--bs-modal-header-border-color: var(--bs-border-color);--bs-modal-header-border-width: var(--bs-border-width);--bs-modal-title-line-height: 1.5;--bs-modal-footer-gap: 0.5rem;--bs-modal-footer-bg: ;--bs-modal-footer-border-color: var(--bs-border-color);--bs-modal-footer-border-width: var(--bs-border-width);position:fixed;top:0;left:0;z-index:var(--bs-modal-zindex);display:none;width:100%;height:100%;overflow-x:hidden;overflow-y:auto;outline:0}.modal-dialog{position:relative;width:auto;margin:var(--bs-modal-margin);pointer-events:none}.modal.fade .modal-dialog{transition:transform .3s ease-out;transform:translate(0, -50px)}@media(prefers-reduced-motion: reduce){.modal.fade .modal-dialog{transition:none}}.modal.show .modal-dialog{transform:none}.modal.modal-static 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!important}.pt-lg-0{padding-top:0 !important}.pt-lg-1{padding-top:.25rem !important}.pt-lg-2{padding-top:.5rem !important}.pt-lg-3{padding-top:1rem !important}.pt-lg-4{padding-top:1.5rem !important}.pt-lg-5{padding-top:3rem !important}.pe-lg-0{padding-right:0 !important}.pe-lg-1{padding-right:.25rem !important}.pe-lg-2{padding-right:.5rem !important}.pe-lg-3{padding-right:1rem !important}.pe-lg-4{padding-right:1.5rem !important}.pe-lg-5{padding-right:3rem !important}.pb-lg-0{padding-bottom:0 !important}.pb-lg-1{padding-bottom:.25rem !important}.pb-lg-2{padding-bottom:.5rem !important}.pb-lg-3{padding-bottom:1rem !important}.pb-lg-4{padding-bottom:1.5rem !important}.pb-lg-5{padding-bottom:3rem !important}.ps-lg-0{padding-left:0 !important}.ps-lg-1{padding-left:.25rem !important}.ps-lg-2{padding-left:.5rem !important}.ps-lg-3{padding-left:1rem !important}.ps-lg-4{padding-left:1.5rem !important}.ps-lg-5{padding-left:3rem !important}.gap-lg-0{gap:0 !important}.gap-lg-1{gap:.25rem !important}.gap-lg-2{gap:.5rem !important}.gap-lg-3{gap:1rem !important}.gap-lg-4{gap:1.5rem !important}.gap-lg-5{gap:3rem !important}.row-gap-lg-0{row-gap:0 !important}.row-gap-lg-1{row-gap:.25rem !important}.row-gap-lg-2{row-gap:.5rem !important}.row-gap-lg-3{row-gap:1rem !important}.row-gap-lg-4{row-gap:1.5rem !important}.row-gap-lg-5{row-gap:3rem !important}.column-gap-lg-0{column-gap:0 !important}.column-gap-lg-1{column-gap:.25rem !important}.column-gap-lg-2{column-gap:.5rem !important}.column-gap-lg-3{column-gap:1rem !important}.column-gap-lg-4{column-gap:1.5rem !important}.column-gap-lg-5{column-gap:3rem !important}.text-lg-start{text-align:left !important}.text-lg-end{text-align:right !important}.text-lg-center{text-align:center !important}}@media(min-width: 1200px){.float-xl-start{float:left !important}.float-xl-end{float:right !important}.float-xl-none{float:none !important}.object-fit-xl-contain{object-fit:contain !important}.object-fit-xl-cover{object-fit:cover !important}.object-fit-xl-fill{object-fit:fill !important}.object-fit-xl-scale{object-fit:scale-down !important}.object-fit-xl-none{object-fit:none !important}.d-xl-inline{display:inline !important}.d-xl-inline-block{display:inline-block !important}.d-xl-block{display:block !important}.d-xl-grid{display:grid !important}.d-xl-inline-grid{display:inline-grid !important}.d-xl-table{display:table !important}.d-xl-table-row{display:table-row !important}.d-xl-table-cell{display:table-cell !important}.d-xl-flex{display:flex !important}.d-xl-inline-flex{display:inline-flex !important}.d-xl-none{display:none !important}.flex-xl-fill{flex:1 1 auto !important}.flex-xl-row{flex-direction:row !important}.flex-xl-column{flex-direction:column !important}.flex-xl-row-reverse{flex-direction:row-reverse !important}.flex-xl-column-reverse{flex-direction:column-reverse !important}.flex-xl-grow-0{flex-grow:0 !important}.flex-xl-grow-1{flex-grow:1 !important}.flex-xl-shrink-0{flex-shrink:0 !important}.flex-xl-shrink-1{flex-shrink:1 !important}.flex-xl-wrap{flex-wrap:wrap !important}.flex-xl-nowrap{flex-wrap:nowrap !important}.flex-xl-wrap-reverse{flex-wrap:wrap-reverse !important}.justify-content-xl-start{justify-content:flex-start !important}.justify-content-xl-end{justify-content:flex-end !important}.justify-content-xl-center{justify-content:center !important}.justify-content-xl-between{justify-content:space-between !important}.justify-content-xl-around{justify-content:space-around !important}.justify-content-xl-evenly{justify-content:space-evenly !important}.align-items-xl-start{align-items:flex-start !important}.align-items-xl-end{align-items:flex-end !important}.align-items-xl-center{align-items:center !important}.align-items-xl-baseline{align-items:baseline !important}.align-items-xl-stretch{align-items:stretch !important}.align-content-xl-start{align-content:flex-start !important}.align-content-xl-end{align-content:flex-end !important}.align-content-xl-center{align-content:center !important}.align-content-xl-between{align-content:space-between !important}.align-content-xl-around{align-content:space-around !important}.align-content-xl-stretch{align-content:stretch !important}.align-self-xl-auto{align-self:auto !important}.align-self-xl-start{align-self:flex-start !important}.align-self-xl-end{align-self:flex-end !important}.align-self-xl-center{align-self:center !important}.align-self-xl-baseline{align-self:baseline !important}.align-self-xl-stretch{align-self:stretch !important}.order-xl-first{order:-1 !important}.order-xl-0{order:0 !important}.order-xl-1{order:1 !important}.order-xl-2{order:2 !important}.order-xl-3{order:3 !important}.order-xl-4{order:4 !important}.order-xl-5{order:5 !important}.order-xl-last{order:6 !important}.m-xl-0{margin:0 !important}.m-xl-1{margin:.25rem !important}.m-xl-2{margin:.5rem !important}.m-xl-3{margin:1rem !important}.m-xl-4{margin:1.5rem !important}.m-xl-5{margin:3rem !important}.m-xl-auto{margin:auto !important}.mx-xl-0{margin-right:0 !important;margin-left:0 !important}.mx-xl-1{margin-right:.25rem !important;margin-left:.25rem !important}.mx-xl-2{margin-right:.5rem !important;margin-left:.5rem !important}.mx-xl-3{margin-right:1rem !important;margin-left:1rem !important}.mx-xl-4{margin-right:1.5rem !important;margin-left:1.5rem !important}.mx-xl-5{margin-right:3rem !important;margin-left:3rem !important}.mx-xl-auto{margin-right:auto !important;margin-left:auto !important}.my-xl-0{margin-top:0 !important;margin-bottom:0 !important}.my-xl-1{margin-top:.25rem !important;margin-bottom:.25rem !important}.my-xl-2{margin-top:.5rem !important;margin-bottom:.5rem !important}.my-xl-3{margin-top:1rem !important;margin-bottom:1rem !important}.my-xl-4{margin-top:1.5rem !important;margin-bottom:1.5rem !important}.my-xl-5{margin-top:3rem !important;margin-bottom:3rem !important}.my-xl-auto{margin-top:auto !important;margin-bottom:auto !important}.mt-xl-0{margin-top:0 !important}.mt-xl-1{margin-top:.25rem !important}.mt-xl-2{margin-top:.5rem !important}.mt-xl-3{margin-top:1rem !important}.mt-xl-4{margin-top:1.5rem !important}.mt-xl-5{margin-top:3rem !important}.mt-xl-auto{margin-top:auto !important}.me-xl-0{margin-right:0 !important}.me-xl-1{margin-right:.25rem !important}.me-xl-2{margin-right:.5rem !important}.me-xl-3{margin-right:1rem !important}.me-xl-4{margin-right:1.5rem !important}.me-xl-5{margin-right:3rem !important}.me-xl-auto{margin-right:auto !important}.mb-xl-0{margin-bottom:0 !important}.mb-xl-1{margin-bottom:.25rem !important}.mb-xl-2{margin-bottom:.5rem !important}.mb-xl-3{margin-bottom:1rem !important}.mb-xl-4{margin-bottom:1.5rem !important}.mb-xl-5{margin-bottom:3rem !important}.mb-xl-auto{margin-bottom:auto !important}.ms-xl-0{margin-left:0 !important}.ms-xl-1{margin-left:.25rem !important}.ms-xl-2{margin-left:.5rem !important}.ms-xl-3{margin-left:1rem !important}.ms-xl-4{margin-left:1.5rem !important}.ms-xl-5{margin-left:3rem !important}.ms-xl-auto{margin-left:auto !important}.p-xl-0{padding:0 !important}.p-xl-1{padding:.25rem !important}.p-xl-2{padding:.5rem !important}.p-xl-3{padding:1rem !important}.p-xl-4{padding:1.5rem !important}.p-xl-5{padding:3rem !important}.px-xl-0{padding-right:0 !important;padding-left:0 !important}.px-xl-1{padding-right:.25rem !important;padding-left:.25rem !important}.px-xl-2{padding-right:.5rem !important;padding-left:.5rem !important}.px-xl-3{padding-right:1rem !important;padding-left:1rem !important}.px-xl-4{padding-right:1.5rem !important;padding-left:1.5rem !important}.px-xl-5{padding-right:3rem !important;padding-left:3rem !important}.py-xl-0{padding-top:0 !important;padding-bottom:0 !important}.py-xl-1{padding-top:.25rem !important;padding-bottom:.25rem !important}.py-xl-2{padding-top:.5rem !important;padding-bottom:.5rem !important}.py-xl-3{padding-top:1rem !important;padding-bottom:1rem !important}.py-xl-4{padding-top:1.5rem !important;padding-bottom:1.5rem !important}.py-xl-5{padding-top:3rem !important;padding-bottom:3rem !important}.pt-xl-0{padding-top:0 !important}.pt-xl-1{padding-top:.25rem !important}.pt-xl-2{padding-top:.5rem !important}.pt-xl-3{padding-top:1rem !important}.pt-xl-4{padding-top:1.5rem !important}.pt-xl-5{padding-top:3rem !important}.pe-xl-0{padding-right:0 !important}.pe-xl-1{padding-right:.25rem !important}.pe-xl-2{padding-right:.5rem !important}.pe-xl-3{padding-right:1rem !important}.pe-xl-4{padding-right:1.5rem !important}.pe-xl-5{padding-right:3rem !important}.pb-xl-0{padding-bottom:0 !important}.pb-xl-1{padding-bottom:.25rem !important}.pb-xl-2{padding-bottom:.5rem !important}.pb-xl-3{padding-bottom:1rem !important}.pb-xl-4{padding-bottom:1.5rem !important}.pb-xl-5{padding-bottom:3rem !important}.ps-xl-0{padding-left:0 !important}.ps-xl-1{padding-left:.25rem !important}.ps-xl-2{padding-left:.5rem !important}.ps-xl-3{padding-left:1rem !important}.ps-xl-4{padding-left:1.5rem !important}.ps-xl-5{padding-left:3rem !important}.gap-xl-0{gap:0 !important}.gap-xl-1{gap:.25rem !important}.gap-xl-2{gap:.5rem !important}.gap-xl-3{gap:1rem !important}.gap-xl-4{gap:1.5rem !important}.gap-xl-5{gap:3rem !important}.row-gap-xl-0{row-gap:0 !important}.row-gap-xl-1{row-gap:.25rem !important}.row-gap-xl-2{row-gap:.5rem !important}.row-gap-xl-3{row-gap:1rem !important}.row-gap-xl-4{row-gap:1.5rem !important}.row-gap-xl-5{row-gap:3rem !important}.column-gap-xl-0{column-gap:0 !important}.column-gap-xl-1{column-gap:.25rem !important}.column-gap-xl-2{column-gap:.5rem !important}.column-gap-xl-3{column-gap:1rem !important}.column-gap-xl-4{column-gap:1.5rem !important}.column-gap-xl-5{column-gap:3rem !important}.text-xl-start{text-align:left !important}.text-xl-end{text-align:right !important}.text-xl-center{text-align:center !important}}@media(min-width: 1200px){.fs-1{font-size:2.5rem !important}.fs-2{font-size:2rem !important}.fs-3{font-size:1.75rem !important}.fs-4{font-size:1.5rem !important}}@media print{.d-print-inline{display:inline !important}.d-print-inline-block{display:inline-block !important}.d-print-block{display:block !important}.d-print-grid{display:grid !important}.d-print-inline-grid{display:inline-grid !important}.d-print-table{display:table !important}.d-print-table-row{display:table-row !important}.d-print-table-cell{display:table-cell !important}.d-print-flex{display:flex !important}.d-print-inline-flex{display:inline-flex !important}.d-print-none{display:none !important}}","@mixin bsBanner($file) {\n  /*!\n   * Bootstrap #{$file} v5.3.2 (https://getbootstrap.com/)\n   * Copyright 2011-2023 The Bootstrap Authors\n   * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n   */\n}\n",":root,\n[data-bs-theme=\"light\"] {\n  // Note: Custom variable values only support SassScript inside `#{}`.\n\n  // Colors\n  //\n  // Generate palettes for full colors, grays, and theme colors.\n\n  @each $color, $value in $colors {\n    --#{$prefix}#{$color}: #{$value};\n  }\n\n  @each $color, $value in $grays {\n    --#{$prefix}gray-#{$color}: #{$value};\n  }\n\n  @each $color, $value in $theme-colors {\n    --#{$prefix}#{$color}: #{$value};\n  }\n\n  @each $color, $value in $theme-colors-rgb {\n    --#{$prefix}#{$color}-rgb: #{$value};\n  }\n\n  @each $color, $value in $theme-colors-text {\n    --#{$prefix}#{$color}-text-emphasis: #{$value};\n  }\n\n  @each $color, $value in $theme-colors-bg-subtle {\n    --#{$prefix}#{$color}-bg-subtle: #{$value};\n  }\n\n  @each $color, $value in $theme-colors-border-subtle {\n    --#{$prefix}#{$color}-border-subtle: #{$value};\n  }\n\n  --#{$prefix}white-rgb: #{to-rgb($white)};\n  --#{$prefix}black-rgb: #{to-rgb($black)};\n\n  // Fonts\n\n  // Note: Use `inspect` for lists so that quoted items keep the quotes.\n  // See https://github.com/sass/sass/issues/2383#issuecomment-336349172\n  --#{$prefix}font-sans-serif: #{inspect($font-family-sans-serif)};\n  --#{$prefix}font-monospace: #{inspect($font-family-monospace)};\n  --#{$prefix}gradient: #{$gradient};\n\n  // Root and body\n  // scss-docs-start root-body-variables\n  @if $font-size-root != null {\n    --#{$prefix}root-font-size: #{$font-size-root};\n  }\n  --#{$prefix}body-font-family: #{inspect($font-family-base)};\n  @include rfs($font-size-base, --#{$prefix}body-font-size);\n  --#{$prefix}body-font-weight: #{$font-weight-base};\n  --#{$prefix}body-line-height: #{$line-height-base};\n  @if $body-text-align != null {\n    --#{$prefix}body-text-align: #{$body-text-align};\n  }\n\n  --#{$prefix}body-color: #{$body-color};\n  --#{$prefix}body-color-rgb: #{to-rgb($body-color)};\n  --#{$prefix}body-bg: #{$body-bg};\n  --#{$prefix}body-bg-rgb: #{to-rgb($body-bg)};\n\n  --#{$prefix}emphasis-color: #{$body-emphasis-color};\n  --#{$prefix}emphasis-color-rgb: #{to-rgb($body-emphasis-color)};\n\n  --#{$prefix}secondary-color: #{$body-secondary-color};\n  --#{$prefix}secondary-color-rgb: #{to-rgb($body-secondary-color)};\n  --#{$prefix}secondary-bg: #{$body-secondary-bg};\n  --#{$prefix}secondary-bg-rgb: #{to-rgb($body-secondary-bg)};\n\n  --#{$prefix}tertiary-color: #{$body-tertiary-color};\n  --#{$prefix}tertiary-color-rgb: #{to-rgb($body-tertiary-color)};\n  --#{$prefix}tertiary-bg: #{$body-tertiary-bg};\n  --#{$prefix}tertiary-bg-rgb: #{to-rgb($body-tertiary-bg)};\n  // scss-docs-end root-body-variables\n\n  --#{$prefix}heading-color: #{$headings-color};\n\n  --#{$prefix}link-color: #{$link-color};\n  --#{$prefix}link-color-rgb: #{to-rgb($link-color)};\n  --#{$prefix}link-decoration: #{$link-decoration};\n\n  --#{$prefix}link-hover-color: #{$link-hover-color};\n  --#{$prefix}link-hover-color-rgb: #{to-rgb($link-hover-color)};\n\n  @if $link-hover-decoration != null {\n    --#{$prefix}link-hover-decoration: #{$link-hover-decoration};\n  }\n\n  --#{$prefix}code-color: #{$code-color};\n  --#{$prefix}highlight-color: #{$mark-color};\n  --#{$prefix}highlight-bg: #{$mark-bg};\n\n  // scss-docs-start root-border-var\n  --#{$prefix}border-width: #{$border-width};\n  --#{$prefix}border-style: #{$border-style};\n  --#{$prefix}border-color: #{$border-color};\n  --#{$prefix}border-color-translucent: #{$border-color-translucent};\n\n  --#{$prefix}border-radius: #{$border-radius};\n  --#{$prefix}border-radius-sm: #{$border-radius-sm};\n  --#{$prefix}border-radius-lg: #{$border-radius-lg};\n  --#{$prefix}border-radius-xl: #{$border-radius-xl};\n  --#{$prefix}border-radius-xxl: #{$border-radius-xxl};\n  --#{$prefix}border-radius-2xl: var(--#{$prefix}border-radius-xxl); // Deprecated in v5.3.0 for consistency\n  --#{$prefix}border-radius-pill: #{$border-radius-pill};\n  // scss-docs-end root-border-var\n\n  --#{$prefix}box-shadow: #{$box-shadow};\n  --#{$prefix}box-shadow-sm: #{$box-shadow-sm};\n  --#{$prefix}box-shadow-lg: #{$box-shadow-lg};\n  --#{$prefix}box-shadow-inset: #{$box-shadow-inset};\n\n  // Focus styles\n  // scss-docs-start root-focus-variables\n  --#{$prefix}focus-ring-width: #{$focus-ring-width};\n  --#{$prefix}focus-ring-opacity: #{$focus-ring-opacity};\n  --#{$prefix}focus-ring-color: #{$focus-ring-color};\n  // scss-docs-end root-focus-variables\n\n  // scss-docs-start root-form-validation-variables\n  --#{$prefix}form-valid-color: #{$form-valid-color};\n  --#{$prefix}form-valid-border-color: #{$form-valid-border-color};\n  --#{$prefix}form-invalid-color: #{$form-invalid-color};\n  --#{$prefix}form-invalid-border-color: #{$form-invalid-border-color};\n  // scss-docs-end root-form-validation-variables\n}\n\n@if $enable-dark-mode {\n  @include color-mode(dark, true) {\n    color-scheme: dark;\n\n    // scss-docs-start root-dark-mode-vars\n    --#{$prefix}body-color: #{$body-color-dark};\n    --#{$prefix}body-color-rgb: #{to-rgb($body-color-dark)};\n    --#{$prefix}body-bg: #{$body-bg-dark};\n    --#{$prefix}body-bg-rgb: #{to-rgb($body-bg-dark)};\n\n    --#{$prefix}emphasis-color: #{$body-emphasis-color-dark};\n    --#{$prefix}emphasis-color-rgb: #{to-rgb($body-emphasis-color-dark)};\n\n    --#{$prefix}secondary-color: #{$body-secondary-color-dark};\n    --#{$prefix}secondary-color-rgb: #{to-rgb($body-secondary-color-dark)};\n    --#{$prefix}secondary-bg: #{$body-secondary-bg-dark};\n    --#{$prefix}secondary-bg-rgb: #{to-rgb($body-secondary-bg-dark)};\n\n    --#{$prefix}tertiary-color: #{$body-tertiary-color-dark};\n    --#{$prefix}tertiary-color-rgb: #{to-rgb($body-tertiary-color-dark)};\n    --#{$prefix}tertiary-bg: #{$body-tertiary-bg-dark};\n    --#{$prefix}tertiary-bg-rgb: #{to-rgb($body-tertiary-bg-dark)};\n\n    @each $color, $value in $theme-colors-text-dark {\n      --#{$prefix}#{$color}-text-emphasis: #{$value};\n    }\n\n    @each $color, $value in $theme-colors-bg-subtle-dark {\n      --#{$prefix}#{$color}-bg-subtle: #{$value};\n    }\n\n    @each $color, $value in $theme-colors-border-subtle-dark {\n      --#{$prefix}#{$color}-border-subtle: #{$value};\n    }\n\n    --#{$prefix}heading-color: #{$headings-color-dark};\n\n    --#{$prefix}link-color: #{$link-color-dark};\n    --#{$prefix}link-hover-color: #{$link-hover-color-dark};\n    --#{$prefix}link-color-rgb: #{to-rgb($link-color-dark)};\n    --#{$prefix}link-hover-color-rgb: #{to-rgb($link-hover-color-dark)};\n\n    --#{$prefix}code-color: #{$code-color-dark};\n    --#{$prefix}highlight-color: #{$mark-color-dark};\n    --#{$prefix}highlight-bg: #{$mark-bg-dark};\n\n    --#{$prefix}border-color: #{$border-color-dark};\n    --#{$prefix}border-color-translucent: #{$border-color-translucent-dark};\n\n    --#{$prefix}form-valid-color: #{$form-valid-color-dark};\n    --#{$prefix}form-valid-border-color: #{$form-valid-border-color-dark};\n    --#{$prefix}form-invalid-color: #{$form-invalid-color-dark};\n    --#{$prefix}form-invalid-border-color: #{$form-invalid-border-color-dark};\n    // scss-docs-end root-dark-mode-vars\n  }\n}\n","// stylelint-disable scss/dimension-no-non-numeric-values\n\n// SCSS RFS mixin\n//\n// Automated responsive values for font sizes, paddings, margins and much more\n//\n// Licensed under MIT (https://github.com/twbs/rfs/blob/main/LICENSE)\n\n// Configuration\n\n// Base value\n$rfs-base-value: 1.25rem !default;\n$rfs-unit: rem !default;\n\n@if $rfs-unit != rem and $rfs-unit != px {\n  @error \"`#{$rfs-unit}` is not a valid unit for $rfs-unit. Use `px` or `rem`.\";\n}\n\n// Breakpoint at where values start decreasing if screen width is smaller\n$rfs-breakpoint: 1200px !default;\n$rfs-breakpoint-unit: px !default;\n\n@if $rfs-breakpoint-unit != px and $rfs-breakpoint-unit != em and $rfs-breakpoint-unit != rem {\n  @error \"`#{$rfs-breakpoint-unit}` is not a valid unit for $rfs-breakpoint-unit. Use `px`, `em` or `rem`.\";\n}\n\n// Resize values based on screen height and width\n$rfs-two-dimensional: false !default;\n\n// Factor of decrease\n$rfs-factor: 10 !default;\n\n@if type-of($rfs-factor) != number or $rfs-factor <= 1 {\n  @error \"`#{$rfs-factor}` is not a valid  $rfs-factor, it must be greater than 1.\";\n}\n\n// Mode. Possibilities: \"min-media-query\", \"max-media-query\"\n$rfs-mode: min-media-query !default;\n\n// Generate enable or disable classes. Possibilities: false, \"enable\" or \"disable\"\n$rfs-class: false !default;\n\n// 1 rem = $rfs-rem-value px\n$rfs-rem-value: 16 !default;\n\n// Safari iframe resize bug: https://github.com/twbs/rfs/issues/14\n$rfs-safari-iframe-resize-bug-fix: false !default;\n\n// Disable RFS by setting $enable-rfs to false\n$enable-rfs: true !default;\n\n// Cache $rfs-base-value unit\n$rfs-base-value-unit: unit($rfs-base-value);\n\n@function divide($dividend, $divisor, $precision: 10) {\n  $sign: if($dividend > 0 and $divisor > 0 or $dividend < 0 and $divisor < 0, 1, -1);\n  $dividend: abs($dividend);\n  $divisor: abs($divisor);\n  @if $dividend == 0 {\n    @return 0;\n  }\n  @if $divisor == 0 {\n    @error \"Cannot divide by 0\";\n  }\n  $remainder: $dividend;\n  $result: 0;\n  $factor: 10;\n  @while ($remainder > 0 and $precision >= 0) {\n    $quotient: 0;\n    @while ($remainder >= $divisor) {\n      $remainder: $remainder - $divisor;\n      $quotient: $quotient + 1;\n    }\n    $result: $result * 10 + $quotient;\n    $factor: $factor * .1;\n    $remainder: $remainder * 10;\n    $precision: $precision - 1;\n    @if ($precision < 0 and $remainder >= $divisor * 5) {\n      $result: $result + 1;\n    }\n  }\n  $result: $result * $factor * $sign;\n  $dividend-unit: unit($dividend);\n  $divisor-unit: unit($divisor);\n  $unit-map: (\n    \"px\": 1px,\n    \"rem\": 1rem,\n    \"em\": 1em,\n    \"%\": 1%\n  );\n  @if ($dividend-unit != $divisor-unit and map-has-key($unit-map, $dividend-unit)) {\n    $result: $result * map-get($unit-map, $dividend-unit);\n  }\n  @return $result;\n}\n\n// Remove px-unit from $rfs-base-value for calculations\n@if $rfs-base-value-unit == px {\n  $rfs-base-value: divide($rfs-base-value, $rfs-base-value * 0 + 1);\n}\n@else if $rfs-base-value-unit == rem {\n  $rfs-base-value: divide($rfs-base-value, divide($rfs-base-value * 0 + 1, $rfs-rem-value));\n}\n\n// Cache $rfs-breakpoint unit to prevent multiple calls\n$rfs-breakpoint-unit-cache: unit($rfs-breakpoint);\n\n// Remove unit from $rfs-breakpoint for calculations\n@if $rfs-breakpoint-unit-cache == px {\n  $rfs-breakpoint: divide($rfs-breakpoint, $rfs-breakpoint * 0 + 1);\n}\n@else if $rfs-breakpoint-unit-cache == rem or $rfs-breakpoint-unit-cache == \"em\" {\n  $rfs-breakpoint: divide($rfs-breakpoint, divide($rfs-breakpoint * 0 + 1, $rfs-rem-value));\n}\n\n// Calculate the media query value\n$rfs-mq-value: if($rfs-breakpoint-unit == px, #{$rfs-breakpoint}px, #{divide($rfs-breakpoint, $rfs-rem-value)}#{$rfs-breakpoint-unit});\n$rfs-mq-property-width: if($rfs-mode == max-media-query, max-width, min-width);\n$rfs-mq-property-height: if($rfs-mode == max-media-query, max-height, min-height);\n\n// Internal mixin used to determine which media query needs to be used\n@mixin _rfs-media-query {\n  @if $rfs-two-dimensional {\n    @if $rfs-mode == max-media-query {\n      @media (#{$rfs-mq-property-width}: #{$rfs-mq-value}), (#{$rfs-mq-property-height}: #{$rfs-mq-value}) {\n        @content;\n      }\n    }\n    @else {\n      @media (#{$rfs-mq-property-width}: #{$rfs-mq-value}) and (#{$rfs-mq-property-height}: #{$rfs-mq-value}) {\n        @content;\n      }\n    }\n  }\n  @else {\n    @media (#{$rfs-mq-property-width}: #{$rfs-mq-value}) {\n      @content;\n    }\n  }\n}\n\n// Internal mixin that adds disable classes to the selector if needed.\n@mixin _rfs-rule {\n  @if $rfs-class == disable and $rfs-mode == max-media-query {\n    // Adding an extra class increases specificity, which prevents the media query to override the property\n    &,\n    .disable-rfs &,\n    &.disable-rfs {\n      @content;\n    }\n  }\n  @else if $rfs-class == enable and $rfs-mode == min-media-query {\n    .enable-rfs &,\n    &.enable-rfs {\n      @content;\n    }\n  } @else {\n    @content;\n  }\n}\n\n// Internal mixin that adds enable classes to the selector if needed.\n@mixin _rfs-media-query-rule {\n\n  @if $rfs-class == enable {\n    @if $rfs-mode == min-media-query {\n      @content;\n    }\n\n    @include _rfs-media-query () {\n      .enable-rfs &,\n      &.enable-rfs {\n        @content;\n      }\n    }\n  }\n  @else {\n    @if $rfs-class == disable and $rfs-mode == min-media-query {\n      .disable-rfs &,\n      &.disable-rfs {\n        @content;\n      }\n    }\n    @include _rfs-media-query () {\n      @content;\n    }\n  }\n}\n\n// Helper function to get the formatted non-responsive value\n@function rfs-value($values) {\n  // Convert to list\n  $values: if(type-of($values) != list, ($values,), $values);\n\n  $val: \"\";\n\n  // Loop over each value and calculate value\n  @each $value in $values {\n    @if $value == 0 {\n      $val: $val + \" 0\";\n    }\n    @else {\n      // Cache $value unit\n      $unit: if(type-of($value) == \"number\", unit($value), false);\n\n      @if $unit == px {\n        // Convert to rem if needed\n        $val: $val + \" \" + if($rfs-unit == rem, #{divide($value, $value * 0 + $rfs-rem-value)}rem, $value);\n      }\n      @else if $unit == rem {\n        // Convert to px if needed\n        $val: $val + \" \" + if($rfs-unit == px, #{divide($value, $value * 0 + 1) * $rfs-rem-value}px, $value);\n      } @else {\n        // If $value isn't a number (like inherit) or $value has a unit (not px or rem, like 1.5em) or $ is 0, just print the value\n        $val: $val + \" \" + $value;\n      }\n    }\n  }\n\n  // Remove first space\n  @return unquote(str-slice($val, 2));\n}\n\n// Helper function to get the responsive value calculated by RFS\n@function rfs-fluid-value($values) {\n  // Convert to list\n  $values: if(type-of($values) != list, ($values,), $values);\n\n  $val: \"\";\n\n  // Loop over each value and calculate value\n  @each $value in $values {\n    @if $value == 0 {\n      $val: $val + \" 0\";\n    } @else {\n      // Cache $value unit\n      $unit: if(type-of($value) == \"number\", unit($value), false);\n\n      // If $value isn't a number (like inherit) or $value has a unit (not px or rem, like 1.5em) or $ is 0, just print the value\n      @if not $unit or $unit != px and $unit != rem {\n        $val: $val + \" \" + $value;\n      } @else {\n        // Remove unit from $value for calculations\n        $value: divide($value, $value * 0 + if($unit == px, 1, divide(1, $rfs-rem-value)));\n\n        // Only add the media query if the value is greater than the minimum value\n        @if abs($value) <= $rfs-base-value or not $enable-rfs {\n          $val: $val + \" \" + if($rfs-unit == rem, #{divide($value, $rfs-rem-value)}rem, #{$value}px);\n        }\n        @else {\n          // Calculate the minimum value\n          $value-min: $rfs-base-value + divide(abs($value) - $rfs-base-value, $rfs-factor);\n\n          // Calculate difference between $value and the minimum value\n          $value-diff: abs($value) - $value-min;\n\n          // Base value formatting\n          $min-width: if($rfs-unit == rem, #{divide($value-min, $rfs-rem-value)}rem, #{$value-min}px);\n\n          // Use negative value if needed\n          $min-width: if($value < 0, -$min-width, $min-width);\n\n          // Use `vmin` if two-dimensional is enabled\n          $variable-unit: if($rfs-two-dimensional, vmin, vw);\n\n          // Calculate the variable width between 0 and $rfs-breakpoint\n          $variable-width: #{divide($value-diff * 100, $rfs-breakpoint)}#{$variable-unit};\n\n          // Return the calculated value\n          $val: $val + \" calc(\" + $min-width + if($value < 0, \" - \", \" + \") + $variable-width + \")\";\n        }\n      }\n    }\n  }\n\n  // Remove first space\n  @return unquote(str-slice($val, 2));\n}\n\n// RFS mixin\n@mixin rfs($values, $property: font-size) {\n  @if $values != null {\n    $val: rfs-value($values);\n    $fluid-val: rfs-fluid-value($values);\n\n    // Do not print the media query if responsive & non-responsive values are the same\n    @if $val == $fluid-val {\n      #{$property}: $val;\n    }\n    @else {\n      @include _rfs-rule () {\n        #{$property}: if($rfs-mode == max-media-query, $val, $fluid-val);\n\n        // Include safari iframe resize fix if needed\n        min-width: if($rfs-safari-iframe-resize-bug-fix, (0 * 1vw), null);\n      }\n\n      @include _rfs-media-query-rule () {\n        #{$property}: if($rfs-mode == max-media-query, $fluid-val, $val);\n      }\n    }\n  }\n}\n\n// Shorthand helper mixins\n@mixin font-size($value) {\n  @include rfs($value);\n}\n\n@mixin padding($value) {\n  @include rfs($value, padding);\n}\n\n@mixin padding-top($value) {\n  @include rfs($value, padding-top);\n}\n\n@mixin padding-right($value) {\n  @include rfs($value, padding-right);\n}\n\n@mixin padding-bottom($value) {\n  @include rfs($value, padding-bottom);\n}\n\n@mixin padding-left($value) {\n  @include rfs($value, padding-left);\n}\n\n@mixin margin($value) {\n  @include rfs($value, margin);\n}\n\n@mixin margin-top($value) {\n  @include rfs($value, margin-top);\n}\n\n@mixin margin-right($value) {\n  @include rfs($value, margin-right);\n}\n\n@mixin margin-bottom($value) {\n  @include rfs($value, margin-bottom);\n}\n\n@mixin margin-left($value) {\n  @include rfs($value, margin-left);\n}\n","// scss-docs-start color-mode-mixin\n@mixin color-mode($mode: light, $root: false) {\n  @if $color-mode-type == \"media-query\" {\n    @if $root == true {\n      @media (prefers-color-scheme: $mode) {\n        :root {\n          @content;\n        }\n      }\n    } @else {\n      @media (prefers-color-scheme: $mode) {\n        @content;\n      }\n    }\n  } @else {\n    [data-bs-theme=\"#{$mode}\"] {\n      @content;\n    }\n  }\n}\n// scss-docs-end color-mode-mixin\n","// stylelint-disable declaration-no-important, selector-no-qualifying-type, property-no-vendor-prefix\n\n\n// Reboot\n//\n// Normalization of HTML elements, manually forked from Normalize.css to remove\n// styles targeting irrelevant browsers while applying new styles.\n//\n// Normalize is licensed MIT. https://github.com/necolas/normalize.css\n\n\n// Document\n//\n// Change from `box-sizing: content-box` so that `width` is not affected by `padding` or `border`.\n\n*,\n*::before,\n*::after {\n  box-sizing: border-box;\n}\n\n\n// Root\n//\n// Ability to the value of the root font sizes, affecting the value of `rem`.\n// null by default, thus nothing is generated.\n\n:root {\n  @if $font-size-root != null {\n    @include font-size(var(--#{$prefix}root-font-size));\n  }\n\n  @if $enable-smooth-scroll {\n    @media (prefers-reduced-motion: no-preference) {\n      scroll-behavior: smooth;\n    }\n  }\n}\n\n\n// Body\n//\n// 1. Remove the margin in all browsers.\n// 2. As a best practice, apply a default `background-color`.\n// 3. Prevent adjustments of font size after orientation changes in iOS.\n// 4. Change the default tap highlight to be completely transparent in iOS.\n\n// scss-docs-start reboot-body-rules\nbody {\n  margin: 0; // 1\n  font-family: var(--#{$prefix}body-font-family);\n  @include font-size(var(--#{$prefix}body-font-size));\n  font-weight: var(--#{$prefix}body-font-weight);\n  line-height: var(--#{$prefix}body-line-height);\n  color: var(--#{$prefix}body-color);\n  text-align: var(--#{$prefix}body-text-align);\n  background-color: var(--#{$prefix}body-bg); // 2\n  -webkit-text-size-adjust: 100%; // 3\n  -webkit-tap-highlight-color: rgba($black, 0); // 4\n}\n// scss-docs-end reboot-body-rules\n\n\n// Content grouping\n//\n// 1. Reset Firefox's gray color\n\nhr {\n  margin: $hr-margin-y 0;\n  color: $hr-color; // 1\n  border: 0;\n  border-top: $hr-border-width solid $hr-border-color;\n  opacity: $hr-opacity;\n}\n\n\n// Typography\n//\n// 1. Remove top margins from headings\n//    By default, `<h1>`-`<h6>` all receive top and bottom margins. We nuke the top\n//    margin for easier control within type scales as it avoids margin collapsing.\n\n%heading {\n  margin-top: 0; // 1\n  margin-bottom: $headings-margin-bottom;\n  font-family: $headings-font-family;\n  font-style: $headings-font-style;\n  font-weight: $headings-font-weight;\n  line-height: $headings-line-height;\n  color: var(--#{$prefix}heading-color);\n}\n\nh1 {\n  @extend %heading;\n  @include font-size($h1-font-size);\n}\n\nh2 {\n  @extend %heading;\n  @include font-size($h2-font-size);\n}\n\nh3 {\n  @extend %heading;\n  @include font-size($h3-font-size);\n}\n\nh4 {\n  @extend %heading;\n  @include font-size($h4-font-size);\n}\n\nh5 {\n  @extend %heading;\n  @include font-size($h5-font-size);\n}\n\nh6 {\n  @extend %heading;\n  @include font-size($h6-font-size);\n}\n\n\n// Reset margins on paragraphs\n//\n// Similarly, the top margin on `<p>`s get reset. However, we also reset the\n// bottom margin to use `rem` units instead of `em`.\n\np {\n  margin-top: 0;\n  margin-bottom: $paragraph-margin-bottom;\n}\n\n\n// Abbreviations\n//\n// 1. Add the correct text decoration in Chrome, Edge, Opera, and Safari.\n// 2. Add explicit cursor to indicate changed behavior.\n// 3. Prevent the text-decoration to be skipped.\n\nabbr[title] {\n  text-decoration: underline dotted; // 1\n  cursor: help; // 2\n  text-decoration-skip-ink: none; // 3\n}\n\n\n// Address\n\naddress {\n  margin-bottom: 1rem;\n  font-style: normal;\n  line-height: inherit;\n}\n\n\n// Lists\n\nol,\nul {\n  padding-left: 2rem;\n}\n\nol,\nul,\ndl {\n  margin-top: 0;\n  margin-bottom: 1rem;\n}\n\nol ol,\nul ul,\nol ul,\nul ol {\n  margin-bottom: 0;\n}\n\ndt {\n  font-weight: $dt-font-weight;\n}\n\n// 1. Undo browser default\n\ndd {\n  margin-bottom: .5rem;\n  margin-left: 0; // 1\n}\n\n\n// Blockquote\n\nblockquote {\n  margin: 0 0 1rem;\n}\n\n\n// Strong\n//\n// Add the correct font weight in Chrome, Edge, and Safari\n\nb,\nstrong {\n  font-weight: $font-weight-bolder;\n}\n\n\n// Small\n//\n// Add the correct font size in all browsers\n\nsmall {\n  @include font-size($small-font-size);\n}\n\n\n// Mark\n\nmark {\n  padding: $mark-padding;\n  color: var(--#{$prefix}highlight-color);\n  background-color: var(--#{$prefix}highlight-bg);\n}\n\n\n// Sub and Sup\n//\n// Prevent `sub` and `sup` elements from affecting the line height in\n// all browsers.\n\nsub,\nsup {\n  position: relative;\n  @include font-size($sub-sup-font-size);\n  line-height: 0;\n  vertical-align: baseline;\n}\n\nsub { bottom: -.25em; }\nsup { top: -.5em; }\n\n\n// Links\n\na {\n  color: rgba(var(--#{$prefix}link-color-rgb), var(--#{$prefix}link-opacity, 1));\n  text-decoration: $link-decoration;\n\n  &:hover {\n    --#{$prefix}link-color-rgb: var(--#{$prefix}link-hover-color-rgb);\n    text-decoration: $link-hover-decoration;\n  }\n}\n\n// And undo these styles for placeholder links/named anchors (without href).\n// It would be more straightforward to just use a[href] in previous block, but that\n// causes specificity issues in many other styles that are too complex to fix.\n// See https://github.com/twbs/bootstrap/issues/19402\n\na:not([href]):not([class]) {\n  &,\n  &:hover {\n    color: inherit;\n    text-decoration: none;\n  }\n}\n\n\n// Code\n\npre,\ncode,\nkbd,\nsamp {\n  font-family: $font-family-code;\n  @include font-size(1em); // Correct the odd `em` font sizing in all browsers.\n}\n\n// 1. Remove browser default top margin\n// 2. Reset browser default of `1em` to use `rem`s\n// 3. Don't allow content to break outside\n\npre {\n  display: block;\n  margin-top: 0; // 1\n  margin-bottom: 1rem; // 2\n  overflow: auto; // 3\n  @include font-size($code-font-size);\n  color: $pre-color;\n\n  // Account for some code outputs that place code tags in pre tags\n  code {\n    @include font-size(inherit);\n    color: inherit;\n    word-break: normal;\n  }\n}\n\ncode {\n  @include font-size($code-font-size);\n  color: var(--#{$prefix}code-color);\n  word-wrap: break-word;\n\n  // Streamline the style when inside anchors to avoid broken underline and more\n  a > & {\n    color: inherit;\n  }\n}\n\nkbd {\n  padding: $kbd-padding-y $kbd-padding-x;\n  @include font-size($kbd-font-size);\n  color: $kbd-color;\n  background-color: $kbd-bg;\n  @include border-radius($border-radius-sm);\n\n  kbd {\n    padding: 0;\n    @include font-size(1em);\n    font-weight: $nested-kbd-font-weight;\n  }\n}\n\n\n// Figures\n//\n// Apply a consistent margin strategy (matches our type styles).\n\nfigure {\n  margin: 0 0 1rem;\n}\n\n\n// Images and content\n\nimg,\nsvg {\n  vertical-align: middle;\n}\n\n\n// Tables\n//\n// Prevent double borders\n\ntable {\n  caption-side: bottom;\n  border-collapse: collapse;\n}\n\ncaption {\n  padding-top: $table-cell-padding-y;\n  padding-bottom: $table-cell-padding-y;\n  color: $table-caption-color;\n  text-align: left;\n}\n\n// 1. Removes font-weight bold by inheriting\n// 2. Matches default `<td>` alignment by inheriting `text-align`.\n// 3. Fix alignment for Safari\n\nth {\n  font-weight: $table-th-font-weight; // 1\n  text-align: inherit; // 2\n  text-align: -webkit-match-parent; // 3\n}\n\nthead,\ntbody,\ntfoot,\ntr,\ntd,\nth {\n  border-color: inherit;\n  border-style: solid;\n  border-width: 0;\n}\n\n\n// Forms\n//\n// 1. Allow labels to use `margin` for spacing.\n\nlabel {\n  display: inline-block; // 1\n}\n\n// Remove the default `border-radius` that macOS Chrome adds.\n// See https://github.com/twbs/bootstrap/issues/24093\n\nbutton {\n  // stylelint-disable-next-line property-disallowed-list\n  border-radius: 0;\n}\n\n// Explicitly remove focus outline in Chromium when it shouldn't be\n// visible (e.g. as result of mouse click or touch tap). It already\n// should be doing this automatically, but seems to currently be\n// confused and applies its very visible two-tone outline anyway.\n\nbutton:focus:not(:focus-visible) {\n  outline: 0;\n}\n\n// 1. Remove the margin in Firefox and Safari\n\ninput,\nbutton,\nselect,\noptgroup,\ntextarea {\n  margin: 0; // 1\n  font-family: inherit;\n  @include font-size(inherit);\n  line-height: inherit;\n}\n\n// Remove the inheritance of text transform in Firefox\nbutton,\nselect {\n  text-transform: none;\n}\n// Set the cursor for non-`<button>` buttons\n//\n// Details at https://github.com/twbs/bootstrap/pull/30562\n[role=\"button\"] {\n  cursor: pointer;\n}\n\nselect {\n  // Remove the inheritance of word-wrap in Safari.\n  // See https://github.com/twbs/bootstrap/issues/24990\n  word-wrap: normal;\n\n  // Undo the opacity change from Chrome\n  &:disabled {\n    opacity: 1;\n  }\n}\n\n// Remove the dropdown arrow only from text type inputs built with datalists in Chrome.\n// See https://stackoverflow.com/a/54997118\n\n[list]:not([type=\"date\"]):not([type=\"datetime-local\"]):not([type=\"month\"]):not([type=\"week\"]):not([type=\"time\"])::-webkit-calendar-picker-indicator {\n  display: none !important;\n}\n\n// 1. Prevent a WebKit bug where (2) destroys native `audio` and `video`\n//    controls in Android 4.\n// 2. Correct the inability to style clickable types in iOS and Safari.\n// 3. Opinionated: add \"hand\" cursor to non-disabled button elements.\n\nbutton,\n[type=\"button\"], // 1\n[type=\"reset\"],\n[type=\"submit\"] {\n  -webkit-appearance: button; // 2\n\n  @if $enable-button-pointers {\n    &:not(:disabled) {\n      cursor: pointer; // 3\n    }\n  }\n}\n\n// Remove inner border and padding from Firefox, but don't restore the outline like Normalize.\n\n::-moz-focus-inner {\n  padding: 0;\n  border-style: none;\n}\n\n// 1. Textareas should really only resize vertically so they don't break their (horizontal) containers.\n\ntextarea {\n  resize: vertical; // 1\n}\n\n// 1. Browsers set a default `min-width: min-content;` on fieldsets,\n//    unlike e.g. `<div>`s, which have `min-width: 0;` by default.\n//    So we reset that to ensure fieldsets behave more like a standard block element.\n//    See https://github.com/twbs/bootstrap/issues/12359\n//    and https://html.spec.whatwg.org/multipage/#the-fieldset-and-legend-elements\n// 2. Reset the default outline behavior of fieldsets so they don't affect page layout.\n\nfieldset {\n  min-width: 0; // 1\n  padding: 0; // 2\n  margin: 0; // 2\n  border: 0; // 2\n}\n\n// 1. By using `float: left`, the legend will behave like a block element.\n//    This way the border of a fieldset wraps around the legend if present.\n// 2. Fix wrapping bug.\n//    See https://github.com/twbs/bootstrap/issues/29712\n\nlegend {\n  float: left; // 1\n  width: 100%;\n  padding: 0;\n  margin-bottom: $legend-margin-bottom;\n  @include font-size($legend-font-size);\n  font-weight: $legend-font-weight;\n  line-height: inherit;\n\n  + * {\n    clear: left; // 2\n  }\n}\n\n// Fix height of inputs with a type of datetime-local, date, month, week, or time\n// See https://github.com/twbs/bootstrap/issues/18842\n\n::-webkit-datetime-edit-fields-wrapper,\n::-webkit-datetime-edit-text,\n::-webkit-datetime-edit-minute,\n::-webkit-datetime-edit-hour-field,\n::-webkit-datetime-edit-day-field,\n::-webkit-datetime-edit-month-field,\n::-webkit-datetime-edit-year-field {\n  padding: 0;\n}\n\n::-webkit-inner-spin-button {\n  height: auto;\n}\n\n// 1. This overrides the extra rounded corners on search inputs in iOS so that our\n//    `.form-control` class can properly style them. Note that this cannot simply\n//    be added to `.form-control` as it's not specific enough. For details, see\n//    https://github.com/twbs/bootstrap/issues/11586.\n// 2. Correct the outline style in Safari.\n\n[type=\"search\"] {\n  -webkit-appearance: textfield; // 1\n  outline-offset: -2px; // 2\n}\n\n// 1. A few input types should stay LTR\n// See https://rtlstyling.com/posts/rtl-styling#form-inputs\n// 2. RTL only output\n// See https://rtlcss.com/learn/usage-guide/control-directives/#raw\n\n/* rtl:raw:\n[type=\"tel\"],\n[type=\"url\"],\n[type=\"email\"],\n[type=\"number\"] {\n  direction: ltr;\n}\n*/\n\n// Remove the inner padding in Chrome and Safari on macOS.\n\n::-webkit-search-decoration {\n  -webkit-appearance: none;\n}\n\n// Remove padding around color pickers in webkit browsers\n\n::-webkit-color-swatch-wrapper {\n  padding: 0;\n}\n\n\n// 1. Inherit font family and line height for file input buttons\n// 2. Correct the inability to style clickable types in iOS and Safari.\n\n::file-selector-button {\n  font: inherit; // 1\n  -webkit-appearance: button; // 2\n}\n\n// Correct element displays\n\noutput {\n  display: inline-block;\n}\n\n// Remove border from iframe\n\niframe {\n  border: 0;\n}\n\n// Summary\n//\n// 1. Add the correct display in all browsers\n\nsummary {\n  display: list-item; // 1\n  cursor: pointer;\n}\n\n\n// Progress\n//\n// Add the correct vertical alignment in Chrome, Firefox, and Opera.\n\nprogress {\n  vertical-align: baseline;\n}\n\n\n// Hidden attribute\n//\n// Always hide an element with the `hidden` HTML attribute.\n\n[hidden] {\n  display: none !important;\n}\n","// Variables\n//\n// Variables should follow the `$component-state-property-size` formula for\n// consistent naming. Ex: $nav-link-disabled-color and $modal-content-box-shadow-xs.\n\n// Color system\n\n// scss-docs-start gray-color-variables\n$white:    #fff !default;\n$gray-100: #f8f9fa !default;\n$gray-200: #e9ecef !default;\n$gray-300: #dee2e6 !default;\n$gray-400: #ced4da !default;\n$gray-500: #adb5bd !default;\n$gray-600: #6c757d !default;\n$gray-700: #495057 !default;\n$gray-800: #343a40 !default;\n$gray-900: #212529 !default;\n$black:    #000 !default;\n// scss-docs-end gray-color-variables\n\n// fusv-disable\n// scss-docs-start gray-colors-map\n$grays: (\n  \"100\": $gray-100,\n  \"200\": $gray-200,\n  \"300\": $gray-300,\n  \"400\": $gray-400,\n  \"500\": $gray-500,\n  \"600\": $gray-600,\n  \"700\": $gray-700,\n  \"800\": $gray-800,\n  \"900\": $gray-900\n) !default;\n// scss-docs-end gray-colors-map\n// fusv-enable\n\n// scss-docs-start color-variables\n$blue:    #0d6efd !default;\n$indigo:  #6610f2 !default;\n$purple:  #6f42c1 !default;\n$pink:    #d63384 !default;\n$red:     #dc3545 !default;\n$orange:  #fd7e14 !default;\n$yellow:  #ffc107 !default;\n$green:   #198754 !default;\n$teal:    #20c997 !default;\n$cyan:    #0dcaf0 !default;\n// scss-docs-end color-variables\n\n// scss-docs-start colors-map\n$colors: (\n  \"blue\":       $blue,\n  \"indigo\":     $indigo,\n  \"purple\":     $purple,\n  \"pink\":       $pink,\n  \"red\":        $red,\n  \"orange\":     $orange,\n  \"yellow\":     $yellow,\n  \"green\":      $green,\n  \"teal\":       $teal,\n  \"cyan\":       $cyan,\n  \"black\":      $black,\n  \"white\":      $white,\n  \"gray\":       $gray-600,\n  \"gray-dark\":  $gray-800\n) !default;\n// scss-docs-end colors-map\n\n// The contrast ratio to reach against white, to determine if color changes from \"light\" to \"dark\". Acceptable values for WCAG 2.0 are 3, 4.5 and 7.\n// See https://www.w3.org/TR/WCAG20/#visual-audio-contrast-contrast\n$min-contrast-ratio:   4.5 !default;\n\n// Customize the light and dark text colors for use in our color contrast function.\n$color-contrast-dark:      $black !default;\n$color-contrast-light:     $white !default;\n\n// fusv-disable\n$blue-100: tint-color($blue, 80%) !default;\n$blue-200: tint-color($blue, 60%) !default;\n$blue-300: tint-color($blue, 40%) !default;\n$blue-400: tint-color($blue, 20%) !default;\n$blue-500: $blue !default;\n$blue-600: shade-color($blue, 20%) !default;\n$blue-700: shade-color($blue, 40%) !default;\n$blue-800: shade-color($blue, 60%) !default;\n$blue-900: shade-color($blue, 80%) !default;\n\n$indigo-100: tint-color($indigo, 80%) !default;\n$indigo-200: tint-color($indigo, 60%) !default;\n$indigo-300: tint-color($indigo, 40%) !default;\n$indigo-400: tint-color($indigo, 20%) !default;\n$indigo-500: $indigo !default;\n$indigo-600: shade-color($indigo, 20%) !default;\n$indigo-700: shade-color($indigo, 40%) !default;\n$indigo-800: shade-color($indigo, 60%) !default;\n$indigo-900: shade-color($indigo, 80%) !default;\n\n$purple-100: tint-color($purple, 80%) !default;\n$purple-200: tint-color($purple, 60%) !default;\n$purple-300: tint-color($purple, 40%) !default;\n$purple-400: tint-color($purple, 20%) !default;\n$purple-500: $purple !default;\n$purple-600: shade-color($purple, 20%) !default;\n$purple-700: shade-color($purple, 40%) !default;\n$purple-800: shade-color($purple, 60%) !default;\n$purple-900: shade-color($purple, 80%) !default;\n\n$pink-100: tint-color($pink, 80%) !default;\n$pink-200: tint-color($pink, 60%) !default;\n$pink-300: tint-color($pink, 40%) !default;\n$pink-400: tint-color($pink, 20%) !default;\n$pink-500: $pink !default;\n$pink-600: shade-color($pink, 20%) !default;\n$pink-700: shade-color($pink, 40%) !default;\n$pink-800: shade-color($pink, 60%) !default;\n$pink-900: shade-color($pink, 80%) !default;\n\n$red-100: tint-color($red, 80%) !default;\n$red-200: tint-color($red, 60%) !default;\n$red-300: tint-color($red, 40%) !default;\n$red-400: tint-color($red, 20%) !default;\n$red-500: $red !default;\n$red-600: shade-color($red, 20%) !default;\n$red-700: shade-color($red, 40%) !default;\n$red-800: shade-color($red, 60%) !default;\n$red-900: shade-color($red, 80%) !default;\n\n$orange-100: tint-color($orange, 80%) !default;\n$orange-200: tint-color($orange, 60%) !default;\n$orange-300: tint-color($orange, 40%) !default;\n$orange-400: tint-color($orange, 20%) !default;\n$orange-500: $orange !default;\n$orange-600: shade-color($orange, 20%) !default;\n$orange-700: shade-color($orange, 40%) !default;\n$orange-800: shade-color($orange, 60%) !default;\n$orange-900: shade-color($orange, 80%) !default;\n\n$yellow-100: tint-color($yellow, 80%) !default;\n$yellow-200: tint-color($yellow, 60%) !default;\n$yellow-300: tint-color($yellow, 40%) !default;\n$yellow-400: tint-color($yellow, 20%) !default;\n$yellow-500: $yellow !default;\n$yellow-600: shade-color($yellow, 20%) !default;\n$yellow-700: shade-color($yellow, 40%) !default;\n$yellow-800: shade-color($yellow, 60%) !default;\n$yellow-900: shade-color($yellow, 80%) !default;\n\n$green-100: tint-color($green, 80%) !default;\n$green-200: tint-color($green, 60%) !default;\n$green-300: tint-color($green, 40%) !default;\n$green-400: tint-color($green, 20%) !default;\n$green-500: $green !default;\n$green-600: shade-color($green, 20%) !default;\n$green-700: shade-color($green, 40%) !default;\n$green-800: shade-color($green, 60%) !default;\n$green-900: shade-color($green, 80%) !default;\n\n$teal-100: tint-color($teal, 80%) !default;\n$teal-200: tint-color($teal, 60%) !default;\n$teal-300: tint-color($teal, 40%) !default;\n$teal-400: tint-color($teal, 20%) !default;\n$teal-500: $teal !default;\n$teal-600: shade-color($teal, 20%) !default;\n$teal-700: shade-color($teal, 40%) !default;\n$teal-800: shade-color($teal, 60%) !default;\n$teal-900: shade-color($teal, 80%) !default;\n\n$cyan-100: tint-color($cyan, 80%) !default;\n$cyan-200: tint-color($cyan, 60%) !default;\n$cyan-300: tint-color($cyan, 40%) !default;\n$cyan-400: tint-color($cyan, 20%) !default;\n$cyan-500: $cyan !default;\n$cyan-600: shade-color($cyan, 20%) !default;\n$cyan-700: shade-color($cyan, 40%) !default;\n$cyan-800: shade-color($cyan, 60%) !default;\n$cyan-900: shade-color($cyan, 80%) !default;\n\n$blues: (\n  \"blue-100\": $blue-100,\n  \"blue-200\": $blue-200,\n  \"blue-300\": $blue-300,\n  \"blue-400\": $blue-400,\n  \"blue-500\": $blue-500,\n  \"blue-600\": $blue-600,\n  \"blue-700\": $blue-700,\n  \"blue-800\": $blue-800,\n  \"blue-900\": $blue-900\n) !default;\n\n$indigos: (\n  \"indigo-100\": $indigo-100,\n  \"indigo-200\": $indigo-200,\n  \"indigo-300\": $indigo-300,\n  \"indigo-400\": $indigo-400,\n  \"indigo-500\": $indigo-500,\n  \"indigo-600\": $indigo-600,\n  \"indigo-700\": $indigo-700,\n  \"indigo-800\": $indigo-800,\n  \"indigo-900\": $indigo-900\n) !default;\n\n$purples: (\n  \"purple-100\": $purple-100,\n  \"purple-200\": $purple-200,\n  \"purple-300\": $purple-300,\n  \"purple-400\": $purple-400,\n  \"purple-500\": $purple-500,\n  \"purple-600\": $purple-600,\n  \"purple-700\": $purple-700,\n  \"purple-800\": $purple-800,\n  \"purple-900\": $purple-900\n) !default;\n\n$pinks: (\n  \"pink-100\": $pink-100,\n  \"pink-200\": $pink-200,\n  \"pink-300\": $pink-300,\n  \"pink-400\": $pink-400,\n  \"pink-500\": $pink-500,\n  \"pink-600\": $pink-600,\n  \"pink-700\": $pink-700,\n  \"pink-800\": $pink-800,\n  \"pink-900\": $pink-900\n) !default;\n\n$reds: (\n  \"red-100\": $red-100,\n  \"red-200\": $red-200,\n  \"red-300\": $red-300,\n  \"red-400\": $red-400,\n  \"red-500\": $red-500,\n  \"red-600\": $red-600,\n  \"red-700\": $red-700,\n  \"red-800\": $red-800,\n  \"red-900\": $red-900\n) !default;\n\n$oranges: (\n  \"orange-100\": $orange-100,\n  \"orange-200\": $orange-200,\n  \"orange-300\": $orange-300,\n  \"orange-400\": $orange-400,\n  \"orange-500\": $orange-500,\n  \"orange-600\": $orange-600,\n  \"orange-700\": $orange-700,\n  \"orange-800\": $orange-800,\n  \"orange-900\": $orange-900\n) !default;\n\n$yellows: (\n  \"yellow-100\": $yellow-100,\n  \"yellow-200\": $yellow-200,\n  \"yellow-300\": $yellow-300,\n  \"yellow-400\": $yellow-400,\n  \"yellow-500\": $yellow-500,\n  \"yellow-600\": $yellow-600,\n  \"yellow-700\": $yellow-700,\n  \"yellow-800\": $yellow-800,\n  \"yellow-900\": $yellow-900\n) !default;\n\n$greens: (\n  \"green-100\": $green-100,\n  \"green-200\": $green-200,\n  \"green-300\": $green-300,\n  \"green-400\": $green-400,\n  \"green-500\": $green-500,\n  \"green-600\": $green-600,\n  \"green-700\": $green-700,\n  \"green-800\": $green-800,\n  \"green-900\": $green-900\n) !default;\n\n$teals: (\n  \"teal-100\": $teal-100,\n  \"teal-200\": $teal-200,\n  \"teal-300\": $teal-300,\n  \"teal-400\": $teal-400,\n  \"teal-500\": $teal-500,\n  \"teal-600\": $teal-600,\n  \"teal-700\": $teal-700,\n  \"teal-800\": $teal-800,\n  \"teal-900\": $teal-900\n) !default;\n\n$cyans: (\n  \"cyan-100\": $cyan-100,\n  \"cyan-200\": $cyan-200,\n  \"cyan-300\": $cyan-300,\n  \"cyan-400\": $cyan-400,\n  \"cyan-500\": $cyan-500,\n  \"cyan-600\": $cyan-600,\n  \"cyan-700\": $cyan-700,\n  \"cyan-800\": $cyan-800,\n  \"cyan-900\": $cyan-900\n) !default;\n// fusv-enable\n\n// scss-docs-start theme-color-variables\n$primary:       $blue !default;\n$secondary:     $gray-600 !default;\n$success:       $green !default;\n$info:          $cyan !default;\n$warning:       $yellow !default;\n$danger:        $red !default;\n$light:         $gray-100 !default;\n$dark:          $gray-900 !default;\n// scss-docs-end theme-color-variables\n\n// scss-docs-start theme-colors-map\n$theme-colors: (\n  \"primary\":    $primary,\n  \"secondary\":  $secondary,\n  \"success\":    $success,\n  \"info\":       $info,\n  \"warning\":    $warning,\n  \"danger\":     $danger,\n  \"light\":      $light,\n  \"dark\":       $dark\n) !default;\n// scss-docs-end theme-colors-map\n\n// scss-docs-start theme-text-variables\n$primary-text-emphasis:   shade-color($primary, 60%) !default;\n$secondary-text-emphasis: shade-color($secondary, 60%) !default;\n$success-text-emphasis:   shade-color($success, 60%) !default;\n$info-text-emphasis:      shade-color($info, 60%) !default;\n$warning-text-emphasis:   shade-color($warning, 60%) !default;\n$danger-text-emphasis:    shade-color($danger, 60%) !default;\n$light-text-emphasis:     $gray-700 !default;\n$dark-text-emphasis:      $gray-700 !default;\n// scss-docs-end theme-text-variables\n\n// scss-docs-start theme-bg-subtle-variables\n$primary-bg-subtle:       tint-color($primary, 80%) !default;\n$secondary-bg-subtle:     tint-color($secondary, 80%) !default;\n$success-bg-subtle:       tint-color($success, 80%) !default;\n$info-bg-subtle:          tint-color($info, 80%) !default;\n$warning-bg-subtle:       tint-color($warning, 80%) !default;\n$danger-bg-subtle:        tint-color($danger, 80%) !default;\n$light-bg-subtle:         mix($gray-100, $white) !default;\n$dark-bg-subtle:          $gray-400 !default;\n// scss-docs-end theme-bg-subtle-variables\n\n// scss-docs-start theme-border-subtle-variables\n$primary-border-subtle:   tint-color($primary, 60%) !default;\n$secondary-border-subtle: tint-color($secondary, 60%) !default;\n$success-border-subtle:   tint-color($success, 60%) !default;\n$info-border-subtle:      tint-color($info, 60%) !default;\n$warning-border-subtle:   tint-color($warning, 60%) !default;\n$danger-border-subtle:    tint-color($danger, 60%) !default;\n$light-border-subtle:     $gray-200 !default;\n$dark-border-subtle:      $gray-500 !default;\n// scss-docs-end theme-border-subtle-variables\n\n// Characters which are escaped by the escape-svg function\n$escaped-characters: (\n  (\"<\", \"%3c\"),\n  (\">\", \"%3e\"),\n  (\"#\", \"%23\"),\n  (\"(\", \"%28\"),\n  (\")\", \"%29\"),\n) !default;\n\n// Options\n//\n// Quickly modify global styling by enabling or disabling optional features.\n\n$enable-caret:                true !default;\n$enable-rounded:              true !default;\n$enable-shadows:              false !default;\n$enable-gradients:            false !default;\n$enable-transitions:          true !default;\n$enable-reduced-motion:       true !default;\n$enable-smooth-scroll:        true !default;\n$enable-grid-classes:         true !default;\n$enable-container-classes:    true !default;\n$enable-cssgrid:              false !default;\n$enable-button-pointers:      true !default;\n$enable-rfs:                  true !default;\n$enable-validation-icons:     true !default;\n$enable-negative-margins:     false !default;\n$enable-deprecation-messages: true !default;\n$enable-important-utilities:  true !default;\n\n$enable-dark-mode:            true !default;\n$color-mode-type:             data !default; // `data` or `media-query`\n\n// Prefix for :root CSS variables\n\n$variable-prefix:             bs- !default; // Deprecated in v5.2.0 for the shorter `$prefix`\n$prefix:                      $variable-prefix !default;\n\n// Gradient\n//\n// The gradient which is added to components if `$enable-gradients` is `true`\n// This gradient is also added to elements with `.bg-gradient`\n// scss-docs-start variable-gradient\n$gradient: linear-gradient(180deg, rgba($white, .15), rgba($white, 0)) !default;\n// scss-docs-end variable-gradient\n\n// Spacing\n//\n// Control the default styling of most Bootstrap elements by modifying these\n// variables. Mostly focused on spacing.\n// You can add more entries to the $spacers map, should you need more variation.\n\n// scss-docs-start spacer-variables-maps\n$spacer: 1rem !default;\n$spacers: (\n  0: 0,\n  1: $spacer * .25,\n  2: $spacer * .5,\n  3: $spacer,\n  4: $spacer * 1.5,\n  5: $spacer * 3,\n) !default;\n// scss-docs-end spacer-variables-maps\n\n// Position\n//\n// Define the edge positioning anchors of the position utilities.\n\n// scss-docs-start position-map\n$position-values: (\n  0: 0,\n  50: 50%,\n  100: 100%\n) !default;\n// scss-docs-end position-map\n\n// Body\n//\n// Settings for the `<body>` element.\n\n$body-text-align:           null !default;\n$body-color:                $gray-900 !default;\n$body-bg:                   $white !default;\n\n$body-secondary-color:      rgba($body-color, .75) !default;\n$body-secondary-bg:         $gray-200 !default;\n\n$body-tertiary-color:       rgba($body-color, .5) !default;\n$body-tertiary-bg:          $gray-100 !default;\n\n$body-emphasis-color:       $black !default;\n\n// Links\n//\n// Style anchor elements.\n\n$link-color:                              $primary !default;\n$link-decoration:                         underline !default;\n$link-shade-percentage:                   20% !default;\n$link-hover-color:                        shift-color($link-color, $link-shade-percentage) !default;\n$link-hover-decoration:                   null !default;\n\n$stretched-link-pseudo-element:           after !default;\n$stretched-link-z-index:                  1 !default;\n\n// Icon links\n// scss-docs-start icon-link-variables\n$icon-link-gap:               .375rem !default;\n$icon-link-underline-offset:  .25em !default;\n$icon-link-icon-size:         1em !default;\n$icon-link-icon-transition:   .2s ease-in-out transform !default;\n$icon-link-icon-transform:    translate3d(.25em, 0, 0) !default;\n// scss-docs-end icon-link-variables\n\n// Paragraphs\n//\n// Style p element.\n\n$paragraph-margin-bottom:   1rem !default;\n\n\n// Grid breakpoints\n//\n// Define the minimum dimensions at which your layout will change,\n// adapting to different screen sizes, for use in media queries.\n\n// scss-docs-start grid-breakpoints\n$grid-breakpoints: (\n  xs: 0,\n  sm: 576px,\n  md: 768px,\n  lg: 992px,\n  xl: 1200px,\n  xxl: 1400px\n) !default;\n// scss-docs-end grid-breakpoints\n\n@include _assert-ascending($grid-breakpoints, \"$grid-breakpoints\");\n@include _assert-starts-at-zero($grid-breakpoints, \"$grid-breakpoints\");\n\n\n// Grid containers\n//\n// Define the maximum width of `.container` for different screen sizes.\n\n// scss-docs-start container-max-widths\n$container-max-widths: (\n  sm: 540px,\n  md: 720px,\n  lg: 960px,\n  xl: 1140px,\n  xxl: 1320px\n) !default;\n// scss-docs-end container-max-widths\n\n@include _assert-ascending($container-max-widths, \"$container-max-widths\");\n\n\n// Grid columns\n//\n// Set the number of columns and specify the width of the gutters.\n\n$grid-columns:                12 !default;\n$grid-gutter-width:           1.5rem !default;\n$grid-row-columns:            6 !default;\n\n// Container padding\n\n$container-padding-x: $grid-gutter-width !default;\n\n\n// Components\n//\n// Define common padding and border radius sizes and more.\n\n// scss-docs-start border-variables\n$border-width:                1px !default;\n$border-widths: (\n  1: 1px,\n  2: 2px,\n  3: 3px,\n  4: 4px,\n  5: 5px\n) !default;\n$border-style:                solid !default;\n$border-color:                $gray-300 !default;\n$border-color-translucent:    rgba($black, .175) !default;\n// scss-docs-end border-variables\n\n// scss-docs-start border-radius-variables\n$border-radius:               .375rem !default;\n$border-radius-sm:            .25rem !default;\n$border-radius-lg:            .5rem !default;\n$border-radius-xl:            1rem !default;\n$border-radius-xxl:           2rem !default;\n$border-radius-pill:          50rem !default;\n// scss-docs-end border-radius-variables\n// fusv-disable\n$border-radius-2xl:           $border-radius-xxl !default; // Deprecated in v5.3.0\n// fusv-enable\n\n// scss-docs-start box-shadow-variables\n$box-shadow:                  0 .5rem 1rem rgba($black, .15) !default;\n$box-shadow-sm:               0 .125rem .25rem rgba($black, .075) !default;\n$box-shadow-lg:               0 1rem 3rem rgba($black, .175) !default;\n$box-shadow-inset:            inset 0 1px 2px rgba($black, .075) !default;\n// scss-docs-end box-shadow-variables\n\n$component-active-color:      $white !default;\n$component-active-bg:         $primary !default;\n\n// scss-docs-start focus-ring-variables\n$focus-ring-width:      .25rem !default;\n$focus-ring-opacity:    .25 !default;\n$focus-ring-color:      rgba($primary, $focus-ring-opacity) !default;\n$focus-ring-blur:       0 !default;\n$focus-ring-box-shadow: 0 0 $focus-ring-blur $focus-ring-width $focus-ring-color !default;\n// scss-docs-end focus-ring-variables\n\n// scss-docs-start caret-variables\n$caret-width:                 .3em !default;\n$caret-vertical-align:        $caret-width * .85 !default;\n$caret-spacing:               $caret-width * .85 !default;\n// scss-docs-end caret-variables\n\n$transition-base:             all .2s ease-in-out !default;\n$transition-fade:             opacity .15s linear !default;\n// scss-docs-start collapse-transition\n$transition-collapse:         height .35s ease !default;\n$transition-collapse-width:   width .35s ease !default;\n// scss-docs-end collapse-transition\n\n// stylelint-disable function-disallowed-list\n// scss-docs-start aspect-ratios\n$aspect-ratios: (\n  \"1x1\": 100%,\n  \"4x3\": calc(3 / 4 * 100%),\n  \"16x9\": calc(9 / 16 * 100%),\n  \"21x9\": calc(9 / 21 * 100%)\n) !default;\n// scss-docs-end aspect-ratios\n// stylelint-enable function-disallowed-list\n\n// Typography\n//\n// Font, line-height, and color for body text, headings, and more.\n\n// scss-docs-start font-variables\n// stylelint-disable value-keyword-case\n$font-family-sans-serif:      system-ui, -apple-system, \"Segoe UI\", Roboto, \"Helvetica Neue\", \"Noto Sans\", \"Liberation Sans\", Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\", \"Noto Color Emoji\" !default;\n$font-family-monospace:       SFMono-Regular, Menlo, Monaco, Consolas, \"Liberation Mono\", \"Courier New\", monospace !default;\n// stylelint-enable value-keyword-case\n$font-family-base:            var(--#{$prefix}font-sans-serif) !default;\n$font-family-code:            var(--#{$prefix}font-monospace) !default;\n\n// $font-size-root affects the value of `rem`, which is used for as well font sizes, paddings, and margins\n// $font-size-base affects the font size of the body text\n$font-size-root:              null !default;\n$font-size-base:              1rem !default; // Assumes the browser default, typically `16px`\n$font-size-sm:                $font-size-base * .875 !default;\n$font-size-lg:                $font-size-base * 1.25 !default;\n\n$font-weight-lighter:         lighter !default;\n$font-weight-light:           300 !default;\n$font-weight-normal:          400 !default;\n$font-weight-medium:          500 !default;\n$font-weight-semibold:        600 !default;\n$font-weight-bold:            700 !default;\n$font-weight-bolder:          bolder !default;\n\n$font-weight-base:            $font-weight-normal !default;\n\n$line-height-base:            1.5 !default;\n$line-height-sm:              1.25 !default;\n$line-height-lg:              2 !default;\n\n$h1-font-size:                $font-size-base * 2.5 !default;\n$h2-font-size:                $font-size-base * 2 !default;\n$h3-font-size:                $font-size-base * 1.75 !default;\n$h4-font-size:                $font-size-base * 1.5 !default;\n$h5-font-size:                $font-size-base * 1.25 !default;\n$h6-font-size:                $font-size-base !default;\n// scss-docs-end font-variables\n\n// scss-docs-start font-sizes\n$font-sizes: (\n  1: $h1-font-size,\n  2: $h2-font-size,\n  3: $h3-font-size,\n  4: $h4-font-size,\n  5: $h5-font-size,\n  6: $h6-font-size\n) !default;\n// scss-docs-end font-sizes\n\n// scss-docs-start headings-variables\n$headings-margin-bottom:      $spacer * .5 !default;\n$headings-font-family:        null !default;\n$headings-font-style:         null !default;\n$headings-font-weight:        500 !default;\n$headings-line-height:        1.2 !default;\n$headings-color:              inherit !default;\n// scss-docs-end headings-variables\n\n// scss-docs-start display-headings\n$display-font-sizes: (\n  1: 5rem,\n  2: 4.5rem,\n  3: 4rem,\n  4: 3.5rem,\n  5: 3rem,\n  6: 2.5rem\n) !default;\n\n$display-font-family: null !default;\n$display-font-style:  null !default;\n$display-font-weight: 300 !default;\n$display-line-height: $headings-line-height !default;\n// scss-docs-end display-headings\n\n// scss-docs-start type-variables\n$lead-font-size:              $font-size-base * 1.25 !default;\n$lead-font-weight:            300 !default;\n\n$small-font-size:             .875em !default;\n\n$sub-sup-font-size:           .75em !default;\n\n// fusv-disable\n$text-muted:                  var(--#{$prefix}secondary-color) !default; // Deprecated in 5.3.0\n// fusv-enable\n\n$initialism-font-size:        $small-font-size !default;\n\n$blockquote-margin-y:         $spacer !default;\n$blockquote-font-size:        $font-size-base * 1.25 !default;\n$blockquote-footer-color:     $gray-600 !default;\n$blockquote-footer-font-size: $small-font-size !default;\n\n$hr-margin-y:                 $spacer !default;\n$hr-color:                    inherit !default;\n\n// fusv-disable\n$hr-bg-color:                 null !default; // Deprecated in v5.2.0\n$hr-height:                   null !default; // Deprecated in v5.2.0\n// fusv-enable\n\n$hr-border-color:             null !default; // Allows for inherited colors\n$hr-border-width:             var(--#{$prefix}border-width) !default;\n$hr-opacity:                  .25 !default;\n\n// scss-docs-start vr-variables\n$vr-border-width:             var(--#{$prefix}border-width) !default;\n// scss-docs-end vr-variables\n\n$legend-margin-bottom:        .5rem !default;\n$legend-font-size:            1.5rem !default;\n$legend-font-weight:          null !default;\n\n$dt-font-weight:              $font-weight-bold !default;\n\n$list-inline-padding:         .5rem !default;\n\n$mark-padding:                .1875em !default;\n$mark-color:                  $body-color !default;\n$mark-bg:                     $yellow-100 !default;\n// scss-docs-end type-variables\n\n\n// Tables\n//\n// Customizes the `.table` component with basic values, each used across all table variations.\n\n// scss-docs-start table-variables\n$table-cell-padding-y:        .5rem !default;\n$table-cell-padding-x:        .5rem !default;\n$table-cell-padding-y-sm:     .25rem !default;\n$table-cell-padding-x-sm:     .25rem !default;\n\n$table-cell-vertical-align:   top !default;\n\n$table-color:                 var(--#{$prefix}emphasis-color) !default;\n$table-bg:                    var(--#{$prefix}body-bg) !default;\n$table-accent-bg:             transparent !default;\n\n$table-th-font-weight:        null !default;\n\n$table-striped-color:         $table-color !default;\n$table-striped-bg-factor:     .05 !default;\n$table-striped-bg:            rgba(var(--#{$prefix}emphasis-color-rgb), $table-striped-bg-factor) !default;\n\n$table-active-color:          $table-color !default;\n$table-active-bg-factor:      .1 !default;\n$table-active-bg:             rgba(var(--#{$prefix}emphasis-color-rgb), $table-active-bg-factor) !default;\n\n$table-hover-color:           $table-color !default;\n$table-hover-bg-factor:       .075 !default;\n$table-hover-bg:              rgba(var(--#{$prefix}emphasis-color-rgb), $table-hover-bg-factor) !default;\n\n$table-border-factor:         .2 !default;\n$table-border-width:          var(--#{$prefix}border-width) !default;\n$table-border-color:          var(--#{$prefix}border-color) !default;\n\n$table-striped-order:         odd !default;\n$table-striped-columns-order: even !default;\n\n$table-group-separator-color: currentcolor !default;\n\n$table-caption-color:         var(--#{$prefix}secondary-color) !default;\n\n$table-bg-scale:              -80% !default;\n// scss-docs-end table-variables\n\n// scss-docs-start table-loop\n$table-variants: (\n  \"primary\":    shift-color($primary, $table-bg-scale),\n  \"secondary\":  shift-color($secondary, $table-bg-scale),\n  \"success\":    shift-color($success, $table-bg-scale),\n  \"info\":       shift-color($info, $table-bg-scale),\n  \"warning\":    shift-color($warning, $table-bg-scale),\n  \"danger\":     shift-color($danger, $table-bg-scale),\n  \"light\":      $light,\n  \"dark\":       $dark,\n) !default;\n// scss-docs-end table-loop\n\n\n// Buttons + Forms\n//\n// Shared variables that are reassigned to `$input-` and `$btn-` specific variables.\n\n// scss-docs-start input-btn-variables\n$input-btn-padding-y:         .375rem !default;\n$input-btn-padding-x:         .75rem !default;\n$input-btn-font-family:       null !default;\n$input-btn-font-size:         $font-size-base !default;\n$input-btn-line-height:       $line-height-base !default;\n\n$input-btn-focus-width:         $focus-ring-width !default;\n$input-btn-focus-color-opacity: $focus-ring-opacity !default;\n$input-btn-focus-color:         $focus-ring-color !default;\n$input-btn-focus-blur:          $focus-ring-blur !default;\n$input-btn-focus-box-shadow:    $focus-ring-box-shadow !default;\n\n$input-btn-padding-y-sm:      .25rem !default;\n$input-btn-padding-x-sm:      .5rem !default;\n$input-btn-font-size-sm:      $font-size-sm !default;\n\n$input-btn-padding-y-lg:      .5rem !default;\n$input-btn-padding-x-lg:      1rem !default;\n$input-btn-font-size-lg:      $font-size-lg !default;\n\n$input-btn-border-width:      var(--#{$prefix}border-width) !default;\n// scss-docs-end input-btn-variables\n\n\n// Buttons\n//\n// For each of Bootstrap's buttons, define text, background, and border color.\n\n// scss-docs-start btn-variables\n$btn-color:                   var(--#{$prefix}body-color) !default;\n$btn-padding-y:               $input-btn-padding-y !default;\n$btn-padding-x:               $input-btn-padding-x !default;\n$btn-font-family:             $input-btn-font-family !default;\n$btn-font-size:               $input-btn-font-size !default;\n$btn-line-height:             $input-btn-line-height !default;\n$btn-white-space:             null !default; // Set to `nowrap` to prevent text wrapping\n\n$btn-padding-y-sm:            $input-btn-padding-y-sm !default;\n$btn-padding-x-sm:            $input-btn-padding-x-sm !default;\n$btn-font-size-sm:            $input-btn-font-size-sm !default;\n\n$btn-padding-y-lg:            $input-btn-padding-y-lg !default;\n$btn-padding-x-lg:            $input-btn-padding-x-lg !default;\n$btn-font-size-lg:            $input-btn-font-size-lg !default;\n\n$btn-border-width:            $input-btn-border-width !default;\n\n$btn-font-weight:             $font-weight-normal !default;\n$btn-box-shadow:              inset 0 1px 0 rgba($white, .15), 0 1px 1px rgba($black, .075) !default;\n$btn-focus-width:             $input-btn-focus-width !default;\n$btn-focus-box-shadow:        $input-btn-focus-box-shadow !default;\n$btn-disabled-opacity:        .65 !default;\n$btn-active-box-shadow:       inset 0 3px 5px rgba($black, .125) !default;\n\n$btn-link-color:              var(--#{$prefix}link-color) !default;\n$btn-link-hover-color:        var(--#{$prefix}link-hover-color) !default;\n$btn-link-disabled-color:     $gray-600 !default;\n$btn-link-focus-shadow-rgb:   to-rgb(mix(color-contrast($link-color), $link-color, 15%)) !default;\n\n// Allows for customizing button radius independently from global border radius\n$btn-border-radius:           var(--#{$prefix}border-radius) !default;\n$btn-border-radius-sm:        var(--#{$prefix}border-radius-sm) !default;\n$btn-border-radius-lg:        var(--#{$prefix}border-radius-lg) !default;\n\n$btn-transition:              color .15s ease-in-out, background-color .15s ease-in-out, border-color .15s ease-in-out, box-shadow .15s ease-in-out !default;\n\n$btn-hover-bg-shade-amount:       15% !default;\n$btn-hover-bg-tint-amount:        15% !default;\n$btn-hover-border-shade-amount:   20% !default;\n$btn-hover-border-tint-amount:    10% !default;\n$btn-active-bg-shade-amount:      20% !default;\n$btn-active-bg-tint-amount:       20% !default;\n$btn-active-border-shade-amount:  25% !default;\n$btn-active-border-tint-amount:   10% !default;\n// scss-docs-end btn-variables\n\n\n// Forms\n\n// scss-docs-start form-text-variables\n$form-text-margin-top:                  .25rem !default;\n$form-text-font-size:                   $small-font-size !default;\n$form-text-font-style:                  null !default;\n$form-text-font-weight:                 null !default;\n$form-text-color:                       var(--#{$prefix}secondary-color) !default;\n// scss-docs-end form-text-variables\n\n// scss-docs-start form-label-variables\n$form-label-margin-bottom:              .5rem !default;\n$form-label-font-size:                  null !default;\n$form-label-font-style:                 null !default;\n$form-label-font-weight:                null !default;\n$form-label-color:                      null !default;\n// scss-docs-end form-label-variables\n\n// scss-docs-start form-input-variables\n$input-padding-y:                       $input-btn-padding-y !default;\n$input-padding-x:                       $input-btn-padding-x !default;\n$input-font-family:                     $input-btn-font-family !default;\n$input-font-size:                       $input-btn-font-size !default;\n$input-font-weight:                     $font-weight-base !default;\n$input-line-height:                     $input-btn-line-height !default;\n\n$input-padding-y-sm:                    $input-btn-padding-y-sm !default;\n$input-padding-x-sm:                    $input-btn-padding-x-sm !default;\n$input-font-size-sm:                    $input-btn-font-size-sm !default;\n\n$input-padding-y-lg:                    $input-btn-padding-y-lg !default;\n$input-padding-x-lg:                    $input-btn-padding-x-lg !default;\n$input-font-size-lg:                    $input-btn-font-size-lg !default;\n\n$input-bg:                              var(--#{$prefix}body-bg) !default;\n$input-disabled-color:                  null !default;\n$input-disabled-bg:                     var(--#{$prefix}secondary-bg) !default;\n$input-disabled-border-color:           null !default;\n\n$input-color:                           var(--#{$prefix}body-color) !default;\n$input-border-color:                    var(--#{$prefix}border-color) !default;\n$input-border-width:                    $input-btn-border-width !default;\n$input-box-shadow:                      var(--#{$prefix}box-shadow-inset) !default;\n\n$input-border-radius:                   var(--#{$prefix}border-radius) !default;\n$input-border-radius-sm:                var(--#{$prefix}border-radius-sm) !default;\n$input-border-radius-lg:                var(--#{$prefix}border-radius-lg) !default;\n\n$input-focus-bg:                        $input-bg !default;\n$input-focus-border-color:              tint-color($component-active-bg, 50%) !default;\n$input-focus-color:                     $input-color !default;\n$input-focus-width:                     $input-btn-focus-width !default;\n$input-focus-box-shadow:                $input-btn-focus-box-shadow !default;\n\n$input-placeholder-color:               var(--#{$prefix}secondary-color) !default;\n$input-plaintext-color:                 var(--#{$prefix}body-color) !default;\n\n$input-height-border:                   calc(#{$input-border-width} * 2) !default; // stylelint-disable-line function-disallowed-list\n\n$input-height-inner:                    add($input-line-height * 1em, $input-padding-y * 2) !default;\n$input-height-inner-half:               add($input-line-height * .5em, $input-padding-y) !default;\n$input-height-inner-quarter:            add($input-line-height * .25em, $input-padding-y * .5) !default;\n\n$input-height:                          add($input-line-height * 1em, add($input-padding-y * 2, $input-height-border, false)) !default;\n$input-height-sm:                       add($input-line-height * 1em, add($input-padding-y-sm * 2, $input-height-border, false)) !default;\n$input-height-lg:                       add($input-line-height * 1em, add($input-padding-y-lg * 2, $input-height-border, false)) !default;\n\n$input-transition:                      border-color .15s ease-in-out, box-shadow .15s ease-in-out !default;\n\n$form-color-width:                      3rem !default;\n// scss-docs-end form-input-variables\n\n// scss-docs-start form-check-variables\n$form-check-input-width:                  1em !default;\n$form-check-min-height:                   $font-size-base * $line-height-base !default;\n$form-check-padding-start:                $form-check-input-width + .5em !default;\n$form-check-margin-bottom:                .125rem !default;\n$form-check-label-color:                  null !default;\n$form-check-label-cursor:                 null !default;\n$form-check-transition:                   null !default;\n\n$form-check-input-active-filter:          brightness(90%) !default;\n\n$form-check-input-bg:                     $input-bg !default;\n$form-check-input-border:                 var(--#{$prefix}border-width) solid var(--#{$prefix}border-color) !default;\n$form-check-input-border-radius:          .25em !default;\n$form-check-radio-border-radius:          50% !default;\n$form-check-input-focus-border:           $input-focus-border-color !default;\n$form-check-input-focus-box-shadow:       $focus-ring-box-shadow !default;\n\n$form-check-input-checked-color:          $component-active-color !default;\n$form-check-input-checked-bg-color:       $component-active-bg !default;\n$form-check-input-checked-border-color:   $form-check-input-checked-bg-color !default;\n$form-check-input-checked-bg-image:       url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 20 20'><path fill='none' stroke='#{$form-check-input-checked-color}' stroke-linecap='round' stroke-linejoin='round' stroke-width='3' d='m6 10 3 3 6-6'/></svg>\") !default;\n$form-check-radio-checked-bg-image:       url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'><circle r='2' fill='#{$form-check-input-checked-color}'/></svg>\") !default;\n\n$form-check-input-indeterminate-color:          $component-active-color !default;\n$form-check-input-indeterminate-bg-color:       $component-active-bg !default;\n$form-check-input-indeterminate-border-color:   $form-check-input-indeterminate-bg-color !default;\n$form-check-input-indeterminate-bg-image:       url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 20 20'><path fill='none' stroke='#{$form-check-input-indeterminate-color}' stroke-linecap='round' stroke-linejoin='round' stroke-width='3' d='M6 10h8'/></svg>\") !default;\n\n$form-check-input-disabled-opacity:        .5 !default;\n$form-check-label-disabled-opacity:        $form-check-input-disabled-opacity !default;\n$form-check-btn-check-disabled-opacity:    $btn-disabled-opacity !default;\n\n$form-check-inline-margin-end:    1rem !default;\n// scss-docs-end form-check-variables\n\n// scss-docs-start form-switch-variables\n$form-switch-color:               rgba($black, .25) !default;\n$form-switch-width:               2em !default;\n$form-switch-padding-start:       $form-switch-width + .5em !default;\n$form-switch-bg-image:            url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'><circle r='3' fill='#{$form-switch-color}'/></svg>\") !default;\n$form-switch-border-radius:       $form-switch-width !default;\n$form-switch-transition:          background-position .15s ease-in-out !default;\n\n$form-switch-focus-color:         $input-focus-border-color !default;\n$form-switch-focus-bg-image:      url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'><circle r='3' fill='#{$form-switch-focus-color}'/></svg>\") !default;\n\n$form-switch-checked-color:       $component-active-color !default;\n$form-switch-checked-bg-image:    url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'><circle r='3' fill='#{$form-switch-checked-color}'/></svg>\") !default;\n$form-switch-checked-bg-position: right center !default;\n// scss-docs-end form-switch-variables\n\n// scss-docs-start input-group-variables\n$input-group-addon-padding-y:           $input-padding-y !default;\n$input-group-addon-padding-x:           $input-padding-x !default;\n$input-group-addon-font-weight:         $input-font-weight !default;\n$input-group-addon-color:               $input-color !default;\n$input-group-addon-bg:                  var(--#{$prefix}tertiary-bg) !default;\n$input-group-addon-border-color:        $input-border-color !default;\n// scss-docs-end input-group-variables\n\n// scss-docs-start form-select-variables\n$form-select-padding-y:             $input-padding-y !default;\n$form-select-padding-x:             $input-padding-x !default;\n$form-select-font-family:           $input-font-family !default;\n$form-select-font-size:             $input-font-size !default;\n$form-select-indicator-padding:     $form-select-padding-x * 3 !default; // Extra padding for background-image\n$form-select-font-weight:           $input-font-weight !default;\n$form-select-line-height:           $input-line-height !default;\n$form-select-color:                 $input-color !default;\n$form-select-bg:                    $input-bg !default;\n$form-select-disabled-color:        null !default;\n$form-select-disabled-bg:           $input-disabled-bg !default;\n$form-select-disabled-border-color: $input-disabled-border-color !default;\n$form-select-bg-position:           right $form-select-padding-x center !default;\n$form-select-bg-size:               16px 12px !default; // In pixels because image dimensions\n$form-select-indicator-color:       $gray-800 !default;\n$form-select-indicator:             url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'><path fill='none' stroke='#{$form-select-indicator-color}' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' d='m2 5 6 6 6-6'/></svg>\") !default;\n\n$form-select-feedback-icon-padding-end: $form-select-padding-x * 2.5 + $form-select-indicator-padding !default;\n$form-select-feedback-icon-position:    center right $form-select-indicator-padding !default;\n$form-select-feedback-icon-size:        $input-height-inner-half $input-height-inner-half !default;\n\n$form-select-border-width:        $input-border-width !default;\n$form-select-border-color:        $input-border-color !default;\n$form-select-border-radius:       $input-border-radius !default;\n$form-select-box-shadow:          var(--#{$prefix}box-shadow-inset) !default;\n\n$form-select-focus-border-color:  $input-focus-border-color !default;\n$form-select-focus-width:         $input-focus-width !default;\n$form-select-focus-box-shadow:    0 0 0 $form-select-focus-width $input-btn-focus-color !default;\n\n$form-select-padding-y-sm:        $input-padding-y-sm !default;\n$form-select-padding-x-sm:        $input-padding-x-sm !default;\n$form-select-font-size-sm:        $input-font-size-sm !default;\n$form-select-border-radius-sm:    $input-border-radius-sm !default;\n\n$form-select-padding-y-lg:        $input-padding-y-lg !default;\n$form-select-padding-x-lg:        $input-padding-x-lg !default;\n$form-select-font-size-lg:        $input-font-size-lg !default;\n$form-select-border-radius-lg:    $input-border-radius-lg !default;\n\n$form-select-transition:          $input-transition !default;\n// scss-docs-end form-select-variables\n\n// scss-docs-start form-range-variables\n$form-range-track-width:          100% !default;\n$form-range-track-height:         .5rem !default;\n$form-range-track-cursor:         pointer !default;\n$form-range-track-bg:             var(--#{$prefix}secondary-bg) !default;\n$form-range-track-border-radius:  1rem !default;\n$form-range-track-box-shadow:     var(--#{$prefix}box-shadow-inset) !default;\n\n$form-range-thumb-width:                   1rem !default;\n$form-range-thumb-height:                  $form-range-thumb-width !default;\n$form-range-thumb-bg:                      $component-active-bg !default;\n$form-range-thumb-border:                  0 !default;\n$form-range-thumb-border-radius:           1rem !default;\n$form-range-thumb-box-shadow:              0 .1rem .25rem rgba($black, .1) !default;\n$form-range-thumb-focus-box-shadow:        0 0 0 1px $body-bg, $input-focus-box-shadow !default;\n$form-range-thumb-focus-box-shadow-width:  $input-focus-width !default; // For focus box shadow issue in Edge\n$form-range-thumb-active-bg:               tint-color($component-active-bg, 70%) !default;\n$form-range-thumb-disabled-bg:             var(--#{$prefix}secondary-color) !default;\n$form-range-thumb-transition:              background-color .15s ease-in-out, border-color .15s ease-in-out, box-shadow .15s ease-in-out !default;\n// scss-docs-end form-range-variables\n\n// scss-docs-start form-file-variables\n$form-file-button-color:          $input-color !default;\n$form-file-button-bg:             var(--#{$prefix}tertiary-bg) !default;\n$form-file-button-hover-bg:       var(--#{$prefix}secondary-bg) !default;\n// scss-docs-end form-file-variables\n\n// scss-docs-start form-floating-variables\n$form-floating-height:                  add(3.5rem, $input-height-border) !default;\n$form-floating-line-height:             1.25 !default;\n$form-floating-padding-x:               $input-padding-x !default;\n$form-floating-padding-y:               1rem !default;\n$form-floating-input-padding-t:         1.625rem !default;\n$form-floating-input-padding-b:         .625rem !default;\n$form-floating-label-height:            1.5em !default;\n$form-floating-label-opacity:           .65 !default;\n$form-floating-label-transform:         scale(.85) translateY(-.5rem) translateX(.15rem) !default;\n$form-floating-label-disabled-color:    $gray-600 !default;\n$form-floating-transition:              opacity .1s ease-in-out, transform .1s ease-in-out !default;\n// scss-docs-end form-floating-variables\n\n// Form validation\n\n// scss-docs-start form-feedback-variables\n$form-feedback-margin-top:          $form-text-margin-top !default;\n$form-feedback-font-size:           $form-text-font-size !default;\n$form-feedback-font-style:          $form-text-font-style !default;\n$form-feedback-valid-color:         $success !default;\n$form-feedback-invalid-color:       $danger !default;\n\n$form-feedback-icon-valid-color:    $form-feedback-valid-color !default;\n$form-feedback-icon-valid:          url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 8 8'><path fill='#{$form-feedback-icon-valid-color}' d='M2.3 6.73.6 4.53c-.4-1.04.46-1.4 1.1-.8l1.1 1.4 3.4-3.8c.6-.63 1.6-.27 1.2.7l-4 4.6c-.43.5-.8.4-1.1.1z'/></svg>\") !default;\n$form-feedback-icon-invalid-color:  $form-feedback-invalid-color !default;\n$form-feedback-icon-invalid:        url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 12 12' width='12' height='12' fill='none' stroke='#{$form-feedback-icon-invalid-color}'><circle cx='6' cy='6' r='4.5'/><path stroke-linejoin='round' d='M5.8 3.6h.4L6 6.5z'/><circle cx='6' cy='8.2' r='.6' fill='#{$form-feedback-icon-invalid-color}' stroke='none'/></svg>\") !default;\n// scss-docs-end form-feedback-variables\n\n// scss-docs-start form-validation-colors\n$form-valid-color:                  $form-feedback-valid-color !default;\n$form-valid-border-color:           $form-feedback-valid-color !default;\n$form-invalid-color:                $form-feedback-invalid-color !default;\n$form-invalid-border-color:         $form-feedback-invalid-color !default;\n// scss-docs-end form-validation-colors\n\n// scss-docs-start form-validation-states\n$form-validation-states: (\n  \"valid\": (\n    \"color\": var(--#{$prefix}form-valid-color),\n    \"icon\": $form-feedback-icon-valid,\n    \"tooltip-color\": #fff,\n    \"tooltip-bg-color\": var(--#{$prefix}success),\n    \"focus-box-shadow\": 0 0 $input-btn-focus-blur $input-focus-width rgba(var(--#{$prefix}success-rgb), $input-btn-focus-color-opacity),\n    \"border-color\": var(--#{$prefix}form-valid-border-color),\n  ),\n  \"invalid\": (\n    \"color\": var(--#{$prefix}form-invalid-color),\n    \"icon\": $form-feedback-icon-invalid,\n    \"tooltip-color\": #fff,\n    \"tooltip-bg-color\": var(--#{$prefix}danger),\n    \"focus-box-shadow\": 0 0 $input-btn-focus-blur $input-focus-width rgba(var(--#{$prefix}danger-rgb), $input-btn-focus-color-opacity),\n    \"border-color\": var(--#{$prefix}form-invalid-border-color),\n  )\n) !default;\n// scss-docs-end form-validation-states\n\n// Z-index master list\n//\n// Warning: Avoid customizing these values. They're used for a bird's eye view\n// of components dependent on the z-axis and are designed to all work together.\n\n// scss-docs-start zindex-stack\n$zindex-dropdown:                   1000 !default;\n$zindex-sticky:                     1020 !default;\n$zindex-fixed:                      1030 !default;\n$zindex-offcanvas-backdrop:         1040 !default;\n$zindex-offcanvas:                  1045 !default;\n$zindex-modal-backdrop:             1050 !default;\n$zindex-modal:                      1055 !default;\n$zindex-popover:                    1070 !default;\n$zindex-tooltip:                    1080 !default;\n$zindex-toast:                      1090 !default;\n// scss-docs-end zindex-stack\n\n// scss-docs-start zindex-levels-map\n$zindex-levels: (\n  n1: -1,\n  0: 0,\n  1: 1,\n  2: 2,\n  3: 3\n) !default;\n// scss-docs-end zindex-levels-map\n\n\n// Navs\n\n// scss-docs-start nav-variables\n$nav-link-padding-y:                .5rem !default;\n$nav-link-padding-x:                1rem !default;\n$nav-link-font-size:                null !default;\n$nav-link-font-weight:              null !default;\n$nav-link-color:                    var(--#{$prefix}link-color) !default;\n$nav-link-hover-color:              var(--#{$prefix}link-hover-color) !default;\n$nav-link-transition:               color .15s ease-in-out, background-color .15s ease-in-out, border-color .15s ease-in-out !default;\n$nav-link-disabled-color:           var(--#{$prefix}secondary-color) !default;\n$nav-link-focus-box-shadow:         $focus-ring-box-shadow !default;\n\n$nav-tabs-border-color:             var(--#{$prefix}border-color) !default;\n$nav-tabs-border-width:             var(--#{$prefix}border-width) !default;\n$nav-tabs-border-radius:            var(--#{$prefix}border-radius) !default;\n$nav-tabs-link-hover-border-color:  var(--#{$prefix}secondary-bg) var(--#{$prefix}secondary-bg) $nav-tabs-border-color !default;\n$nav-tabs-link-active-color:        var(--#{$prefix}emphasis-color) !default;\n$nav-tabs-link-active-bg:           var(--#{$prefix}body-bg) !default;\n$nav-tabs-link-active-border-color: var(--#{$prefix}border-color) var(--#{$prefix}border-color) $nav-tabs-link-active-bg !default;\n\n$nav-pills-border-radius:           var(--#{$prefix}border-radius) !default;\n$nav-pills-link-active-color:       $component-active-color !default;\n$nav-pills-link-active-bg:          $component-active-bg !default;\n\n$nav-underline-gap:                 1rem !default;\n$nav-underline-border-width:        .125rem !default;\n$nav-underline-link-active-color:   var(--#{$prefix}emphasis-color) !default;\n// scss-docs-end nav-variables\n\n\n// Navbar\n\n// scss-docs-start navbar-variables\n$navbar-padding-y:                  $spacer * .5 !default;\n$navbar-padding-x:                  null !default;\n\n$navbar-nav-link-padding-x:         .5rem !default;\n\n$navbar-brand-font-size:            $font-size-lg !default;\n// Compute the navbar-brand padding-y so the navbar-brand will have the same height as navbar-text and nav-link\n$nav-link-height:                   $font-size-base * $line-height-base + $nav-link-padding-y * 2 !default;\n$navbar-brand-height:               $navbar-brand-font-size * $line-height-base !default;\n$navbar-brand-padding-y:            ($nav-link-height - $navbar-brand-height) * .5 !default;\n$navbar-brand-margin-end:           1rem !default;\n\n$navbar-toggler-padding-y:          .25rem !default;\n$navbar-toggler-padding-x:          .75rem !default;\n$navbar-toggler-font-size:          $font-size-lg !default;\n$navbar-toggler-border-radius:      $btn-border-radius !default;\n$navbar-toggler-focus-width:        $btn-focus-width !default;\n$navbar-toggler-transition:         box-shadow .15s ease-in-out !default;\n\n$navbar-light-color:                rgba(var(--#{$prefix}emphasis-color-rgb), .65) !default;\n$navbar-light-hover-color:          rgba(var(--#{$prefix}emphasis-color-rgb), .8) !default;\n$navbar-light-active-color:         rgba(var(--#{$prefix}emphasis-color-rgb), 1) !default;\n$navbar-light-disabled-color:       rgba(var(--#{$prefix}emphasis-color-rgb), .3) !default;\n$navbar-light-icon-color:           rgba($body-color, .75) !default;\n$navbar-light-toggler-icon-bg:      url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'><path stroke='#{$navbar-light-icon-color}' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/></svg>\") !default;\n$navbar-light-toggler-border-color: rgba(var(--#{$prefix}emphasis-color-rgb), .15) !default;\n$navbar-light-brand-color:          $navbar-light-active-color !default;\n$navbar-light-brand-hover-color:    $navbar-light-active-color !default;\n// scss-docs-end navbar-variables\n\n// scss-docs-start navbar-dark-variables\n$navbar-dark-color:                 rgba($white, .55) !default;\n$navbar-dark-hover-color:           rgba($white, .75) !default;\n$navbar-dark-active-color:          $white !default;\n$navbar-dark-disabled-color:        rgba($white, .25) !default;\n$navbar-dark-icon-color:            $navbar-dark-color !default;\n$navbar-dark-toggler-icon-bg:       url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'><path stroke='#{$navbar-dark-icon-color}' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/></svg>\") !default;\n$navbar-dark-toggler-border-color:  rgba($white, .1) !default;\n$navbar-dark-brand-color:           $navbar-dark-active-color !default;\n$navbar-dark-brand-hover-color:     $navbar-dark-active-color !default;\n// scss-docs-end navbar-dark-variables\n\n\n// Dropdowns\n//\n// Dropdown menu container and contents.\n\n// scss-docs-start dropdown-variables\n$dropdown-min-width:                10rem !default;\n$dropdown-padding-x:                0 !default;\n$dropdown-padding-y:                .5rem !default;\n$dropdown-spacer:                   .125rem !default;\n$dropdown-font-size:                $font-size-base !default;\n$dropdown-color:                    var(--#{$prefix}body-color) !default;\n$dropdown-bg:                       var(--#{$prefix}body-bg) !default;\n$dropdown-border-color:             var(--#{$prefix}border-color-translucent) !default;\n$dropdown-border-radius:            var(--#{$prefix}border-radius) !default;\n$dropdown-border-width:             var(--#{$prefix}border-width) !default;\n$dropdown-inner-border-radius:      calc(#{$dropdown-border-radius} - #{$dropdown-border-width}) !default; // stylelint-disable-line function-disallowed-list\n$dropdown-divider-bg:               $dropdown-border-color !default;\n$dropdown-divider-margin-y:         $spacer * .5 !default;\n$dropdown-box-shadow:               var(--#{$prefix}box-shadow) !default;\n\n$dropdown-link-color:               var(--#{$prefix}body-color) !default;\n$dropdown-link-hover-color:         $dropdown-link-color !default;\n$dropdown-link-hover-bg:            var(--#{$prefix}tertiary-bg) !default;\n\n$dropdown-link-active-color:        $component-active-color !default;\n$dropdown-link-active-bg:           $component-active-bg !default;\n\n$dropdown-link-disabled-color:      var(--#{$prefix}tertiary-color) !default;\n\n$dropdown-item-padding-y:           $spacer * .25 !default;\n$dropdown-item-padding-x:           $spacer !default;\n\n$dropdown-header-color:             $gray-600 !default;\n$dropdown-header-padding-x:         $dropdown-item-padding-x !default;\n$dropdown-header-padding-y:         $dropdown-padding-y !default;\n// fusv-disable\n$dropdown-header-padding:           $dropdown-header-padding-y $dropdown-header-padding-x !default; // Deprecated in v5.2.0\n// fusv-enable\n// scss-docs-end dropdown-variables\n\n// scss-docs-start dropdown-dark-variables\n$dropdown-dark-color:               $gray-300 !default;\n$dropdown-dark-bg:                  $gray-800 !default;\n$dropdown-dark-border-color:        $dropdown-border-color !default;\n$dropdown-dark-divider-bg:          $dropdown-divider-bg !default;\n$dropdown-dark-box-shadow:          null !default;\n$dropdown-dark-link-color:          $dropdown-dark-color !default;\n$dropdown-dark-link-hover-color:    $white !default;\n$dropdown-dark-link-hover-bg:       rgba($white, .15) !default;\n$dropdown-dark-link-active-color:   $dropdown-link-active-color !default;\n$dropdown-dark-link-active-bg:      $dropdown-link-active-bg !default;\n$dropdown-dark-link-disabled-color: $gray-500 !default;\n$dropdown-dark-header-color:        $gray-500 !default;\n// scss-docs-end dropdown-dark-variables\n\n\n// Pagination\n\n// scss-docs-start pagination-variables\n$pagination-padding-y:              .375rem !default;\n$pagination-padding-x:              .75rem !default;\n$pagination-padding-y-sm:           .25rem !default;\n$pagination-padding-x-sm:           .5rem !default;\n$pagination-padding-y-lg:           .75rem !default;\n$pagination-padding-x-lg:           1.5rem !default;\n\n$pagination-font-size:              $font-size-base !default;\n\n$pagination-color:                  var(--#{$prefix}link-color) !default;\n$pagination-bg:                     var(--#{$prefix}body-bg) !default;\n$pagination-border-radius:          var(--#{$prefix}border-radius) !default;\n$pagination-border-width:           var(--#{$prefix}border-width) !default;\n$pagination-margin-start:           calc(#{$pagination-border-width} * -1) !default; // stylelint-disable-line function-disallowed-list\n$pagination-border-color:           var(--#{$prefix}border-color) !default;\n\n$pagination-focus-color:            var(--#{$prefix}link-hover-color) !default;\n$pagination-focus-bg:               var(--#{$prefix}secondary-bg) !default;\n$pagination-focus-box-shadow:       $focus-ring-box-shadow !default;\n$pagination-focus-outline:          0 !default;\n\n$pagination-hover-color:            var(--#{$prefix}link-hover-color) !default;\n$pagination-hover-bg:               var(--#{$prefix}tertiary-bg) !default;\n$pagination-hover-border-color:     var(--#{$prefix}border-color) !default; // Todo in v6: remove this?\n\n$pagination-active-color:           $component-active-color !default;\n$pagination-active-bg:              $component-active-bg !default;\n$pagination-active-border-color:    $component-active-bg !default;\n\n$pagination-disabled-color:         var(--#{$prefix}secondary-color) !default;\n$pagination-disabled-bg:            var(--#{$prefix}secondary-bg) !default;\n$pagination-disabled-border-color:  var(--#{$prefix}border-color) !default;\n\n$pagination-transition:              color .15s ease-in-out, background-color .15s ease-in-out, border-color .15s ease-in-out, box-shadow .15s ease-in-out !default;\n\n$pagination-border-radius-sm:       var(--#{$prefix}border-radius-sm) !default;\n$pagination-border-radius-lg:       var(--#{$prefix}border-radius-lg) !default;\n// scss-docs-end pagination-variables\n\n\n// Placeholders\n\n// scss-docs-start placeholders\n$placeholder-opacity-max:           .5 !default;\n$placeholder-opacity-min:           .2 !default;\n// scss-docs-end placeholders\n\n// Cards\n\n// scss-docs-start card-variables\n$card-spacer-y:                     $spacer !default;\n$card-spacer-x:                     $spacer !default;\n$card-title-spacer-y:               $spacer * .5 !default;\n$card-title-color:                  null !default;\n$card-subtitle-color:               null !default;\n$card-border-width:                 var(--#{$prefix}border-width) !default;\n$card-border-color:                 var(--#{$prefix}border-color-translucent) !default;\n$card-border-radius:                var(--#{$prefix}border-radius) !default;\n$card-box-shadow:                   null !default;\n$card-inner-border-radius:          subtract($card-border-radius, $card-border-width) !default;\n$card-cap-padding-y:                $card-spacer-y * .5 !default;\n$card-cap-padding-x:                $card-spacer-x !default;\n$card-cap-bg:                       rgba(var(--#{$prefix}body-color-rgb), .03) !default;\n$card-cap-color:                    null !default;\n$card-height:                       null !default;\n$card-color:                        null !default;\n$card-bg:                           var(--#{$prefix}body-bg) !default;\n$card-img-overlay-padding:          $spacer !default;\n$card-group-margin:                 $grid-gutter-width * .5 !default;\n// scss-docs-end card-variables\n\n// Accordion\n\n// scss-docs-start accordion-variables\n$accordion-padding-y:                     1rem !default;\n$accordion-padding-x:                     1.25rem !default;\n$accordion-color:                         var(--#{$prefix}body-color) !default;\n$accordion-bg:                            var(--#{$prefix}body-bg) !default;\n$accordion-border-width:                  var(--#{$prefix}border-width) !default;\n$accordion-border-color:                  var(--#{$prefix}border-color) !default;\n$accordion-border-radius:                 var(--#{$prefix}border-radius) !default;\n$accordion-inner-border-radius:           subtract($accordion-border-radius, $accordion-border-width) !default;\n\n$accordion-body-padding-y:                $accordion-padding-y !default;\n$accordion-body-padding-x:                $accordion-padding-x !default;\n\n$accordion-button-padding-y:              $accordion-padding-y !default;\n$accordion-button-padding-x:              $accordion-padding-x !default;\n$accordion-button-color:                  var(--#{$prefix}body-color) !default;\n$accordion-button-bg:                     var(--#{$prefix}accordion-bg) !default;\n$accordion-transition:                    $btn-transition, border-radius .15s ease !default;\n$accordion-button-active-bg:              var(--#{$prefix}primary-bg-subtle) !default;\n$accordion-button-active-color:           var(--#{$prefix}primary-text-emphasis) !default;\n\n$accordion-button-focus-border-color:     $input-focus-border-color !default;\n$accordion-button-focus-box-shadow:       $btn-focus-box-shadow !default;\n\n$accordion-icon-width:                    1.25rem !default;\n$accordion-icon-color:                    $body-color !default;\n$accordion-icon-active-color:             $primary-text-emphasis !default;\n$accordion-icon-transition:               transform .2s ease-in-out !default;\n$accordion-icon-transform:                rotate(-180deg) !default;\n\n$accordion-button-icon:         url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$accordion-icon-color}'><path fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/></svg>\") !default;\n$accordion-button-active-icon:  url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$accordion-icon-active-color}'><path fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/></svg>\") !default;\n// scss-docs-end accordion-variables\n\n// Tooltips\n\n// scss-docs-start tooltip-variables\n$tooltip-font-size:                 $font-size-sm !default;\n$tooltip-max-width:                 200px !default;\n$tooltip-color:                     var(--#{$prefix}body-bg) !default;\n$tooltip-bg:                        var(--#{$prefix}emphasis-color) !default;\n$tooltip-border-radius:             var(--#{$prefix}border-radius) !default;\n$tooltip-opacity:                   .9 !default;\n$tooltip-padding-y:                 $spacer * .25 !default;\n$tooltip-padding-x:                 $spacer * .5 !default;\n$tooltip-margin:                    null !default; // TODO: remove this in v6\n\n$tooltip-arrow-width:               .8rem !default;\n$tooltip-arrow-height:              .4rem !default;\n// fusv-disable\n$tooltip-arrow-color:               null !default; // Deprecated in Bootstrap 5.2.0 for CSS variables\n// fusv-enable\n// scss-docs-end tooltip-variables\n\n// Form tooltips must come after regular tooltips\n// scss-docs-start tooltip-feedback-variables\n$form-feedback-tooltip-padding-y:     $tooltip-padding-y !default;\n$form-feedback-tooltip-padding-x:     $tooltip-padding-x !default;\n$form-feedback-tooltip-font-size:     $tooltip-font-size !default;\n$form-feedback-tooltip-line-height:   null !default;\n$form-feedback-tooltip-opacity:       $tooltip-opacity !default;\n$form-feedback-tooltip-border-radius: $tooltip-border-radius !default;\n// scss-docs-end tooltip-feedback-variables\n\n\n// Popovers\n\n// scss-docs-start popover-variables\n$popover-font-size:                 $font-size-sm !default;\n$popover-bg:                        var(--#{$prefix}body-bg) !default;\n$popover-max-width:                 276px !default;\n$popover-border-width:              var(--#{$prefix}border-width) !default;\n$popover-border-color:              var(--#{$prefix}border-color-translucent) !default;\n$popover-border-radius:             var(--#{$prefix}border-radius-lg) !default;\n$popover-inner-border-radius:       calc(#{$popover-border-radius} - #{$popover-border-width}) !default; // stylelint-disable-line function-disallowed-list\n$popover-box-shadow:                var(--#{$prefix}box-shadow) !default;\n\n$popover-header-font-size:          $font-size-base !default;\n$popover-header-bg:                 var(--#{$prefix}secondary-bg) !default;\n$popover-header-color:              $headings-color !default;\n$popover-header-padding-y:          .5rem !default;\n$popover-header-padding-x:          $spacer !default;\n\n$popover-body-color:                var(--#{$prefix}body-color) !default;\n$popover-body-padding-y:            $spacer !default;\n$popover-body-padding-x:            $spacer !default;\n\n$popover-arrow-width:               1rem !default;\n$popover-arrow-height:              .5rem !default;\n// scss-docs-end popover-variables\n\n// fusv-disable\n// Deprecated in Bootstrap 5.2.0 for CSS variables\n$popover-arrow-color:               $popover-bg !default;\n$popover-arrow-outer-color:         var(--#{$prefix}border-color-translucent) !default;\n// fusv-enable\n\n\n// Toasts\n\n// scss-docs-start toast-variables\n$toast-max-width:                   350px !default;\n$toast-padding-x:                   .75rem !default;\n$toast-padding-y:                   .5rem !default;\n$toast-font-size:                   .875rem !default;\n$toast-color:                       null !default;\n$toast-background-color:            rgba(var(--#{$prefix}body-bg-rgb), .85) !default;\n$toast-border-width:                var(--#{$prefix}border-width) !default;\n$toast-border-color:                var(--#{$prefix}border-color-translucent) !default;\n$toast-border-radius:               var(--#{$prefix}border-radius) !default;\n$toast-box-shadow:                  var(--#{$prefix}box-shadow) !default;\n$toast-spacing:                     $container-padding-x !default;\n\n$toast-header-color:                var(--#{$prefix}secondary-color) !default;\n$toast-header-background-color:     rgba(var(--#{$prefix}body-bg-rgb), .85) !default;\n$toast-header-border-color:         $toast-border-color !default;\n// scss-docs-end toast-variables\n\n\n// Badges\n\n// scss-docs-start badge-variables\n$badge-font-size:                   .75em !default;\n$badge-font-weight:                 $font-weight-bold !default;\n$badge-color:                       $white !default;\n$badge-padding-y:                   .35em !default;\n$badge-padding-x:                   .65em !default;\n$badge-border-radius:               var(--#{$prefix}border-radius) !default;\n// scss-docs-end badge-variables\n\n\n// Modals\n\n// scss-docs-start modal-variables\n$modal-inner-padding:               $spacer !default;\n\n$modal-footer-margin-between:       .5rem !default;\n\n$modal-dialog-margin:               .5rem !default;\n$modal-dialog-margin-y-sm-up:       1.75rem !default;\n\n$modal-title-line-height:           $line-height-base !default;\n\n$modal-content-color:               null !default;\n$modal-content-bg:                  var(--#{$prefix}body-bg) !default;\n$modal-content-border-color:        var(--#{$prefix}border-color-translucent) !default;\n$modal-content-border-width:        var(--#{$prefix}border-width) !default;\n$modal-content-border-radius:       var(--#{$prefix}border-radius-lg) !default;\n$modal-content-inner-border-radius: subtract($modal-content-border-radius, $modal-content-border-width) !default;\n$modal-content-box-shadow-xs:       var(--#{$prefix}box-shadow-sm) !default;\n$modal-content-box-shadow-sm-up:    var(--#{$prefix}box-shadow) !default;\n\n$modal-backdrop-bg:                 $black !default;\n$modal-backdrop-opacity:            .5 !default;\n\n$modal-header-border-color:         var(--#{$prefix}border-color) !default;\n$modal-header-border-width:         $modal-content-border-width !default;\n$modal-header-padding-y:            $modal-inner-padding !default;\n$modal-header-padding-x:            $modal-inner-padding !default;\n$modal-header-padding:              $modal-header-padding-y $modal-header-padding-x !default; // Keep this for backwards compatibility\n\n$modal-footer-bg:                   null !default;\n$modal-footer-border-color:         $modal-header-border-color !default;\n$modal-footer-border-width:         $modal-header-border-width !default;\n\n$modal-sm:                          300px !default;\n$modal-md:                          500px !default;\n$modal-lg:                          800px !default;\n$modal-xl:                          1140px !default;\n\n$modal-fade-transform:              translate(0, -50px) !default;\n$modal-show-transform:              none !default;\n$modal-transition:                  transform .3s ease-out !default;\n$modal-scale-transform:             scale(1.02) !default;\n// scss-docs-end modal-variables\n\n\n// Alerts\n//\n// Define alert colors, border radius, and padding.\n\n// scss-docs-start alert-variables\n$alert-padding-y:               $spacer !default;\n$alert-padding-x:               $spacer !default;\n$alert-margin-bottom:           1rem !default;\n$alert-border-radius:           var(--#{$prefix}border-radius) !default;\n$alert-link-font-weight:        $font-weight-bold !default;\n$alert-border-width:            var(--#{$prefix}border-width) !default;\n$alert-dismissible-padding-r:   $alert-padding-x * 3 !default; // 3x covers width of x plus default padding on either side\n// scss-docs-end alert-variables\n\n// fusv-disable\n$alert-bg-scale:                -80% !default; // Deprecated in v5.2.0, to be removed in v6\n$alert-border-scale:            -70% !default; // Deprecated in v5.2.0, to be removed in v6\n$alert-color-scale:             40% !default; // Deprecated in v5.2.0, to be removed in v6\n// fusv-enable\n\n// Progress bars\n\n// scss-docs-start progress-variables\n$progress-height:                   1rem !default;\n$progress-font-size:                $font-size-base * .75 !default;\n$progress-bg:                       var(--#{$prefix}secondary-bg) !default;\n$progress-border-radius:            var(--#{$prefix}border-radius) !default;\n$progress-box-shadow:               var(--#{$prefix}box-shadow-inset) !default;\n$progress-bar-color:                $white !default;\n$progress-bar-bg:                   $primary !default;\n$progress-bar-animation-timing:     1s linear infinite !default;\n$progress-bar-transition:           width .6s ease !default;\n// scss-docs-end progress-variables\n\n\n// List group\n\n// scss-docs-start list-group-variables\n$list-group-color:                  var(--#{$prefix}body-color) !default;\n$list-group-bg:                     var(--#{$prefix}body-bg) !default;\n$list-group-border-color:           var(--#{$prefix}border-color) !default;\n$list-group-border-width:           var(--#{$prefix}border-width) !default;\n$list-group-border-radius:          var(--#{$prefix}border-radius) !default;\n\n$list-group-item-padding-y:         $spacer * .5 !default;\n$list-group-item-padding-x:         $spacer !default;\n// fusv-disable\n$list-group-item-bg-scale:          -80% !default; // Deprecated in v5.3.0\n$list-group-item-color-scale:       40% !default; // Deprecated in v5.3.0\n// fusv-enable\n\n$list-group-hover-bg:               var(--#{$prefix}tertiary-bg) !default;\n$list-group-active-color:           $component-active-color !default;\n$list-group-active-bg:              $component-active-bg !default;\n$list-group-active-border-color:    $list-group-active-bg !default;\n\n$list-group-disabled-color:         var(--#{$prefix}secondary-color) !default;\n$list-group-disabled-bg:            $list-group-bg !default;\n\n$list-group-action-color:           var(--#{$prefix}secondary-color) !default;\n$list-group-action-hover-color:     var(--#{$prefix}emphasis-color) !default;\n\n$list-group-action-active-color:    var(--#{$prefix}body-color) !default;\n$list-group-action-active-bg:       var(--#{$prefix}secondary-bg) !default;\n// scss-docs-end list-group-variables\n\n\n// Image thumbnails\n\n// scss-docs-start thumbnail-variables\n$thumbnail-padding:                 .25rem !default;\n$thumbnail-bg:                      var(--#{$prefix}body-bg) !default;\n$thumbnail-border-width:            var(--#{$prefix}border-width) !default;\n$thumbnail-border-color:            var(--#{$prefix}border-color) !default;\n$thumbnail-border-radius:           var(--#{$prefix}border-radius) !default;\n$thumbnail-box-shadow:              var(--#{$prefix}box-shadow-sm) !default;\n// scss-docs-end thumbnail-variables\n\n\n// Figures\n\n// scss-docs-start figure-variables\n$figure-caption-font-size:          $small-font-size !default;\n$figure-caption-color:              var(--#{$prefix}secondary-color) !default;\n// scss-docs-end figure-variables\n\n\n// Breadcrumbs\n\n// scss-docs-start breadcrumb-variables\n$breadcrumb-font-size:              null !default;\n$breadcrumb-padding-y:              0 !default;\n$breadcrumb-padding-x:              0 !default;\n$breadcrumb-item-padding-x:         .5rem !default;\n$breadcrumb-margin-bottom:          1rem !default;\n$breadcrumb-bg:                     null !default;\n$breadcrumb-divider-color:          var(--#{$prefix}secondary-color) !default;\n$breadcrumb-active-color:           var(--#{$prefix}secondary-color) !default;\n$breadcrumb-divider:                quote(\"/\") !default;\n$breadcrumb-divider-flipped:        $breadcrumb-divider !default;\n$breadcrumb-border-radius:          null !default;\n// scss-docs-end breadcrumb-variables\n\n// Carousel\n\n// scss-docs-start carousel-variables\n$carousel-control-color:             $white !default;\n$carousel-control-width:             15% !default;\n$carousel-control-opacity:           .5 !default;\n$carousel-control-hover-opacity:     .9 !default;\n$carousel-control-transition:        opacity .15s ease !default;\n\n$carousel-indicator-width:           30px !default;\n$carousel-indicator-height:          3px !default;\n$carousel-indicator-hit-area-height: 10px !default;\n$carousel-indicator-spacer:          3px !default;\n$carousel-indicator-opacity:         .5 !default;\n$carousel-indicator-active-bg:       $white !default;\n$carousel-indicator-active-opacity:  1 !default;\n$carousel-indicator-transition:      opacity .6s ease !default;\n\n$carousel-caption-width:             70% !default;\n$carousel-caption-color:             $white !default;\n$carousel-caption-padding-y:         1.25rem !default;\n$carousel-caption-spacer:            1.25rem !default;\n\n$carousel-control-icon-width:        2rem !default;\n\n$carousel-control-prev-icon-bg:      url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$carousel-control-color}'><path d='M11.354 1.646a.5.5 0 0 1 0 .708L5.707 8l5.647 5.646a.5.5 0 0 1-.708.708l-6-6a.5.5 0 0 1 0-.708l6-6a.5.5 0 0 1 .708 0z'/></svg>\") !default;\n$carousel-control-next-icon-bg:      url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$carousel-control-color}'><path d='M4.646 1.646a.5.5 0 0 1 .708 0l6 6a.5.5 0 0 1 0 .708l-6 6a.5.5 0 0 1-.708-.708L10.293 8 4.646 2.354a.5.5 0 0 1 0-.708z'/></svg>\") !default;\n\n$carousel-transition-duration:       .6s !default;\n$carousel-transition:                transform $carousel-transition-duration ease-in-out !default; // Define transform transition first if using multiple transitions (e.g., `transform 2s ease, opacity .5s ease-out`)\n// scss-docs-end carousel-variables\n\n// scss-docs-start carousel-dark-variables\n$carousel-dark-indicator-active-bg:  $black !default;\n$carousel-dark-caption-color:        $black !default;\n$carousel-dark-control-icon-filter:  invert(1) grayscale(100) !default;\n// scss-docs-end carousel-dark-variables\n\n\n// Spinners\n\n// scss-docs-start spinner-variables\n$spinner-width:           2rem !default;\n$spinner-height:          $spinner-width !default;\n$spinner-vertical-align:  -.125em !default;\n$spinner-border-width:    .25em !default;\n$spinner-animation-speed: .75s !default;\n\n$spinner-width-sm:        1rem !default;\n$spinner-height-sm:       $spinner-width-sm !default;\n$spinner-border-width-sm: .2em !default;\n// scss-docs-end spinner-variables\n\n\n// Close\n\n// scss-docs-start close-variables\n$btn-close-width:            1em !default;\n$btn-close-height:           $btn-close-width !default;\n$btn-close-padding-x:        .25em !default;\n$btn-close-padding-y:        $btn-close-padding-x !default;\n$btn-close-color:            $black !default;\n$btn-close-bg:               url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$btn-close-color}'><path d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/></svg>\") !default;\n$btn-close-focus-shadow:     $focus-ring-box-shadow !default;\n$btn-close-opacity:          .5 !default;\n$btn-close-hover-opacity:    .75 !default;\n$btn-close-focus-opacity:    1 !default;\n$btn-close-disabled-opacity: .25 !default;\n$btn-close-white-filter:     invert(1) grayscale(100%) brightness(200%) !default;\n// scss-docs-end close-variables\n\n\n// Offcanvas\n\n// scss-docs-start offcanvas-variables\n$offcanvas-padding-y:               $modal-inner-padding !default;\n$offcanvas-padding-x:               $modal-inner-padding !default;\n$offcanvas-horizontal-width:        400px !default;\n$offcanvas-vertical-height:         30vh !default;\n$offcanvas-transition-duration:     .3s !default;\n$offcanvas-border-color:            $modal-content-border-color !default;\n$offcanvas-border-width:            $modal-content-border-width !default;\n$offcanvas-title-line-height:       $modal-title-line-height !default;\n$offcanvas-bg-color:                var(--#{$prefix}body-bg) !default;\n$offcanvas-color:                   var(--#{$prefix}body-color) !default;\n$offcanvas-box-shadow:              $modal-content-box-shadow-xs !default;\n$offcanvas-backdrop-bg:             $modal-backdrop-bg !default;\n$offcanvas-backdrop-opacity:        $modal-backdrop-opacity !default;\n// scss-docs-end offcanvas-variables\n\n// Code\n\n$code-font-size:                    $small-font-size !default;\n$code-color:                        $pink !default;\n\n$kbd-padding-y:                     .1875rem !default;\n$kbd-padding-x:                     .375rem !default;\n$kbd-font-size:                     $code-font-size !default;\n$kbd-color:                         var(--#{$prefix}body-bg) !default;\n$kbd-bg:                            var(--#{$prefix}body-color) !default;\n$nested-kbd-font-weight:            null !default; // Deprecated in v5.2.0, removing in v6\n\n$pre-color:                         null !default;\n","// stylelint-disable property-disallowed-list\n// Single side border-radius\n\n// Helper function to replace negative values with 0\n@function valid-radius($radius) {\n  $return: ();\n  @each $value in $radius {\n    @if type-of($value) == number {\n      $return: append($return, max($value, 0));\n    } @else {\n      $return: append($return, $value);\n    }\n  }\n  @return $return;\n}\n\n// scss-docs-start border-radius-mixins\n@mixin border-radius($radius: $border-radius, $fallback-border-radius: false) {\n  @if $enable-rounded {\n    border-radius: valid-radius($radius);\n  }\n  @else if $fallback-border-radius != false {\n    border-radius: $fallback-border-radius;\n  }\n}\n\n@mixin border-top-radius($radius: $border-radius) {\n  @if $enable-rounded {\n    border-top-left-radius: valid-radius($radius);\n    border-top-right-radius: valid-radius($radius);\n  }\n}\n\n@mixin border-end-radius($radius: $border-radius) {\n  @if $enable-rounded {\n    border-top-right-radius: valid-radius($radius);\n    border-bottom-right-radius: valid-radius($radius);\n  }\n}\n\n@mixin border-bottom-radius($radius: $border-radius) {\n  @if $enable-rounded {\n    border-bottom-right-radius: valid-radius($radius);\n    border-bottom-left-radius: valid-radius($radius);\n  }\n}\n\n@mixin border-start-radius($radius: $border-radius) {\n  @if $enable-rounded {\n    border-top-left-radius: valid-radius($radius);\n    border-bottom-left-radius: valid-radius($radius);\n  }\n}\n\n@mixin border-top-start-radius($radius: $border-radius) {\n  @if $enable-rounded {\n    border-top-left-radius: valid-radius($radius);\n  }\n}\n\n@mixin border-top-end-radius($radius: $border-radius) {\n  @if $enable-rounded {\n    border-top-right-radius: valid-radius($radius);\n  }\n}\n\n@mixin border-bottom-end-radius($radius: $border-radius) {\n  @if $enable-rounded {\n    border-bottom-right-radius: valid-radius($radius);\n  }\n}\n\n@mixin border-bottom-start-radius($radius: $border-radius) {\n  @if $enable-rounded {\n    border-bottom-left-radius: valid-radius($radius);\n  }\n}\n// scss-docs-end border-radius-mixins\n","//\n// Headings\n//\n.h1 {\n  @extend h1;\n}\n\n.h2 {\n  @extend h2;\n}\n\n.h3 {\n  @extend h3;\n}\n\n.h4 {\n  @extend h4;\n}\n\n.h5 {\n  @extend h5;\n}\n\n.h6 {\n  @extend h6;\n}\n\n\n.lead {\n  @include font-size($lead-font-size);\n  font-weight: $lead-font-weight;\n}\n\n// Type display classes\n@each $display, $font-size in $display-font-sizes {\n  .display-#{$display} {\n    @include font-size($font-size);\n    font-family: $display-font-family;\n    font-style: $display-font-style;\n    font-weight: $display-font-weight;\n    line-height: $display-line-height;\n  }\n}\n\n//\n// Emphasis\n//\n.small {\n  @extend small;\n}\n\n.mark {\n  @extend mark;\n}\n\n//\n// Lists\n//\n\n.list-unstyled {\n  @include list-unstyled();\n}\n\n// Inline turns list items into inline-block\n.list-inline {\n  @include list-unstyled();\n}\n.list-inline-item {\n  display: inline-block;\n\n  &:not(:last-child) {\n    margin-right: $list-inline-padding;\n  }\n}\n\n\n//\n// Misc\n//\n\n// Builds on `abbr`\n.initialism {\n  @include font-size($initialism-font-size);\n  text-transform: uppercase;\n}\n\n// Blockquotes\n.blockquote {\n  margin-bottom: $blockquote-margin-y;\n  @include font-size($blockquote-font-size);\n\n  > :last-child {\n    margin-bottom: 0;\n  }\n}\n\n.blockquote-footer {\n  margin-top: -$blockquote-margin-y;\n  margin-bottom: $blockquote-margin-y;\n  @include font-size($blockquote-footer-font-size);\n  color: $blockquote-footer-color;\n\n  &::before {\n    content: \"\\2014\\00A0\"; // em dash, nbsp\n  }\n}\n","// Lists\n\n// Unstyled keeps list items block level, just removes default browser padding and list-style\n@mixin list-unstyled {\n  padding-left: 0;\n  list-style: none;\n}\n","// Override bootstrap variables\n$spacer: 1rem;\n\n$container-max-widths: (\n  sm: 540px,\n  md: 720px,\n  lg: 960px,\n  xl: 1400px,\n);\n\n$grid-breakpoints: (\n  xs: 0,\n  sm: 540px,\n  md: 720px,\n  lg: 960px,\n  xl: 1200px,\n);\n\n$dropdown-link-hover-bg: var(--pst-color-surface);\n// --pst-color-surface can also be assigned to the dark variant because it is\n// scoped to different values depending on light/dark theme\n$dropdown-dark-link-hover-bg: var(--pst-color-surface);\n$dropdown-link-active-bg: var(--pst-color-surface);\n$dropdown-dark-link-active-bg: var(--pst-color-surface);\n","// Responsive images (ensure images don't scale beyond their parents)\n//\n// This is purposefully opt-in via an explicit class rather than being the default for all `<img>`s.\n// We previously tried the \"images are responsive by default\" approach in Bootstrap v2,\n// and abandoned it in Bootstrap v3 because it breaks lots of third-party widgets (including Google Maps)\n// which weren't expecting the images within themselves to be involuntarily resized.\n// See also https://github.com/twbs/bootstrap/issues/18178\n.img-fluid {\n  @include img-fluid();\n}\n\n\n// Image thumbnails\n.img-thumbnail {\n  padding: $thumbnail-padding;\n  background-color: $thumbnail-bg;\n  border: $thumbnail-border-width solid $thumbnail-border-color;\n  @include border-radius($thumbnail-border-radius);\n  @include box-shadow($thumbnail-box-shadow);\n\n  // Keep them at most 100% wide\n  @include img-fluid();\n}\n\n//\n// Figures\n//\n\n.figure {\n  // Ensures the caption's text aligns with the image.\n  display: inline-block;\n}\n\n.figure-img {\n  margin-bottom: $spacer * .5;\n  line-height: 1;\n}\n\n.figure-caption {\n  @include font-size($figure-caption-font-size);\n  color: $figure-caption-color;\n}\n","// Image Mixins\n// - Responsive image\n// - Retina image\n\n\n// Responsive image\n//\n// Keep images from scaling beyond the width of their parents.\n\n@mixin img-fluid {\n  // Part 1: Set a maximum relative to the parent\n  max-width: 100%;\n  // Part 2: Override the height to auto, otherwise images will be stretched\n  // when setting a width and height attribute on the img element.\n  height: auto;\n}\n","// Container widths\n//\n// Set the container width, and override it for fixed navbars in media queries.\n\n@if $enable-container-classes {\n  // Single container class with breakpoint max-widths\n  .container,\n  // 100% wide container at all breakpoints\n  .container-fluid {\n    @include make-container();\n  }\n\n  // Responsive containers that are 100% wide until a breakpoint\n  @each $breakpoint, $container-max-width in $container-max-widths {\n    .container-#{$breakpoint} {\n      @extend .container-fluid;\n    }\n\n    @include media-breakpoint-up($breakpoint, $grid-breakpoints) {\n      %responsive-container-#{$breakpoint} {\n        max-width: $container-max-width;\n      }\n\n      // Extend each breakpoint which is smaller or equal to the current breakpoint\n      $extend-breakpoint: true;\n\n      @each $name, $width in $grid-breakpoints {\n        @if ($extend-breakpoint) {\n          .container#{breakpoint-infix($name, $grid-breakpoints)} {\n            @extend %responsive-container-#{$breakpoint};\n          }\n\n          // Once the current breakpoint is reached, stop extending\n          @if ($breakpoint == $name) {\n            $extend-breakpoint: false;\n          }\n        }\n      }\n    }\n  }\n}\n","// Container mixins\n\n@mixin make-container($gutter: $container-padding-x) {\n  --#{$prefix}gutter-x: #{$gutter};\n  --#{$prefix}gutter-y: 0;\n  width: 100%;\n  padding-right: calc(var(--#{$prefix}gutter-x) * .5); // stylelint-disable-line function-disallowed-list\n  padding-left: calc(var(--#{$prefix}gutter-x) * .5); // stylelint-disable-line function-disallowed-list\n  margin-right: auto;\n  margin-left: auto;\n}\n","// Breakpoint viewport sizes and media queries.\n//\n// Breakpoints are defined as a map of (name: minimum width), order from small to large:\n//\n//    (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px)\n//\n// The map defined in the `$grid-breakpoints` global variable is used as the `$breakpoints` argument by default.\n\n// Name of the next breakpoint, or null for the last breakpoint.\n//\n//    >> breakpoint-next(sm)\n//    md\n//    >> breakpoint-next(sm, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    md\n//    >> breakpoint-next(sm, $breakpoint-names: (xs sm md lg xl xxl))\n//    md\n@function breakpoint-next($name, $breakpoints: $grid-breakpoints, $breakpoint-names: map-keys($breakpoints)) {\n  $n: index($breakpoint-names, $name);\n  @if not $n {\n    @error \"breakpoint `#{$name}` not found in `#{$breakpoints}`\";\n  }\n  @return if($n < length($breakpoint-names), nth($breakpoint-names, $n + 1), null);\n}\n\n// Minimum breakpoint width. Null for the smallest (first) breakpoint.\n//\n//    >> breakpoint-min(sm, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    576px\n@function breakpoint-min($name, $breakpoints: $grid-breakpoints) {\n  $min: map-get($breakpoints, $name);\n  @return if($min != 0, $min, null);\n}\n\n// Maximum breakpoint width.\n// The maximum value is reduced by 0.02px to work around the limitations of\n// `min-` and `max-` prefixes and viewports with fractional widths.\n// See https://www.w3.org/TR/mediaqueries-4/#mq-min-max\n// Uses 0.02px rather than 0.01px to work around a current rounding bug in Safari.\n// See https://bugs.webkit.org/show_bug.cgi?id=178261\n//\n//    >> breakpoint-max(md, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    767.98px\n@function breakpoint-max($name, $breakpoints: $grid-breakpoints) {\n  $max: map-get($breakpoints, $name);\n  @return if($max and $max > 0, $max - .02, null);\n}\n\n// Returns a blank string if smallest breakpoint, otherwise returns the name with a dash in front.\n// Useful for making responsive utilities.\n//\n//    >> breakpoint-infix(xs, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    \"\"  (Returns a blank string)\n//    >> breakpoint-infix(sm, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    \"-sm\"\n@function breakpoint-infix($name, $breakpoints: $grid-breakpoints) {\n  @return if(breakpoint-min($name, $breakpoints) == null, \"\", \"-#{$name}\");\n}\n\n// Media of at least the minimum breakpoint width. No query for the smallest breakpoint.\n// Makes the @content apply to the given breakpoint and wider.\n@mixin media-breakpoint-up($name, $breakpoints: $grid-breakpoints) {\n  $min: breakpoint-min($name, $breakpoints);\n  @if $min {\n    @media (min-width: $min) {\n      @content;\n    }\n  } @else {\n    @content;\n  }\n}\n\n// Media of at most the maximum breakpoint width. No query for the largest breakpoint.\n// Makes the @content apply to the given breakpoint and narrower.\n@mixin media-breakpoint-down($name, $breakpoints: $grid-breakpoints) {\n  $max: breakpoint-max($name, $breakpoints);\n  @if $max {\n    @media (max-width: $max) {\n      @content;\n    }\n  } @else {\n    @content;\n  }\n}\n\n// Media that spans multiple breakpoint widths.\n// Makes the @content apply between the min and max breakpoints\n@mixin media-breakpoint-between($lower, $upper, $breakpoints: $grid-breakpoints) {\n  $min: breakpoint-min($lower, $breakpoints);\n  $max: breakpoint-max($upper, $breakpoints);\n\n  @if $min != null and $max != null {\n    @media (min-width: $min) and (max-width: $max) {\n      @content;\n    }\n  } @else if $max == null {\n    @include media-breakpoint-up($lower, $breakpoints) {\n      @content;\n    }\n  } @else if $min == null {\n    @include media-breakpoint-down($upper, $breakpoints) {\n      @content;\n    }\n  }\n}\n\n// Media between the breakpoint's minimum and maximum widths.\n// No minimum for the smallest breakpoint, and no maximum for the largest one.\n// Makes the @content apply only to the given breakpoint, not viewports any wider or narrower.\n@mixin media-breakpoint-only($name, $breakpoints: $grid-breakpoints) {\n  $min:  breakpoint-min($name, $breakpoints);\n  $next: breakpoint-next($name, $breakpoints);\n  $max:  breakpoint-max($next, $breakpoints);\n\n  @if $min != null and $max != null {\n    @media (min-width: $min) and (max-width: $max) {\n      @content;\n    }\n  } @else if $max == null {\n    @include media-breakpoint-up($name, $breakpoints) {\n      @content;\n    }\n  } @else if $min == null {\n    @include media-breakpoint-down($next, $breakpoints) {\n      @content;\n    }\n  }\n}\n","// Row\n//\n// Rows contain your columns.\n\n:root {\n  @each $name, $value in $grid-breakpoints {\n    --#{$prefix}breakpoint-#{$name}: #{$value};\n  }\n}\n\n@if $enable-grid-classes {\n  .row {\n    @include make-row();\n\n    > * {\n      @include make-col-ready();\n    }\n  }\n}\n\n@if $enable-cssgrid {\n  .grid {\n    display: grid;\n    grid-template-rows: repeat(var(--#{$prefix}rows, 1), 1fr);\n    grid-template-columns: repeat(var(--#{$prefix}columns, #{$grid-columns}), 1fr);\n    gap: var(--#{$prefix}gap, #{$grid-gutter-width});\n\n    @include make-cssgrid();\n  }\n}\n\n\n// Columns\n//\n// Common styles for small and large grid columns\n\n@if $enable-grid-classes {\n  @include make-grid-columns();\n}\n","// Grid system\n//\n// Generate semantic grid columns with these mixins.\n\n@mixin make-row($gutter: $grid-gutter-width) {\n  --#{$prefix}gutter-x: #{$gutter};\n  --#{$prefix}gutter-y: 0;\n  display: flex;\n  flex-wrap: wrap;\n  // TODO: Revisit calc order after https://github.com/react-bootstrap/react-bootstrap/issues/6039 is fixed\n  margin-top: calc(-1 * var(--#{$prefix}gutter-y)); // stylelint-disable-line function-disallowed-list\n  margin-right: calc(-.5 * var(--#{$prefix}gutter-x)); // stylelint-disable-line function-disallowed-list\n  margin-left: calc(-.5 * var(--#{$prefix}gutter-x)); // stylelint-disable-line function-disallowed-list\n}\n\n@mixin make-col-ready() {\n  // Add box sizing if only the grid is loaded\n  box-sizing: if(variable-exists(include-column-box-sizing) and $include-column-box-sizing, border-box, null);\n  // Prevent columns from becoming too narrow when at smaller grid tiers by\n  // always setting `width: 100%;`. This works because we set the width\n  // later on to override this initial width.\n  flex-shrink: 0;\n  width: 100%;\n  max-width: 100%; // Prevent `.col-auto`, `.col` (& responsive variants) from breaking out the grid\n  padding-right: calc(var(--#{$prefix}gutter-x) * .5); // stylelint-disable-line function-disallowed-list\n  padding-left: calc(var(--#{$prefix}gutter-x) * .5); // stylelint-disable-line function-disallowed-list\n  margin-top: var(--#{$prefix}gutter-y);\n}\n\n@mixin make-col($size: false, $columns: $grid-columns) {\n  @if $size {\n    flex: 0 0 auto;\n    width: percentage(divide($size, $columns));\n\n  } @else {\n    flex: 1 1 0;\n    max-width: 100%;\n  }\n}\n\n@mixin make-col-auto() {\n  flex: 0 0 auto;\n  width: auto;\n}\n\n@mixin make-col-offset($size, $columns: $grid-columns) {\n  $num: divide($size, $columns);\n  margin-left: if($num == 0, 0, percentage($num));\n}\n\n// Row columns\n//\n// Specify on a parent element(e.g., .row) to force immediate children into NN\n// number of columns. Supports wrapping to new lines, but does not do a Masonry\n// style grid.\n@mixin row-cols($count) {\n  > * {\n    flex: 0 0 auto;\n    width: percentage(divide(1, $count));\n  }\n}\n\n// Framework grid generation\n//\n// Used only by Bootstrap to generate the correct number of grid classes given\n// any value of `$grid-columns`.\n\n@mixin make-grid-columns($columns: $grid-columns, $gutter: $grid-gutter-width, $breakpoints: $grid-breakpoints) {\n  @each $breakpoint in map-keys($breakpoints) {\n    $infix: breakpoint-infix($breakpoint, $breakpoints);\n\n    @include media-breakpoint-up($breakpoint, $breakpoints) {\n      // Provide basic `.col-{bp}` classes for equal-width flexbox columns\n      .col#{$infix} {\n        flex: 1 0 0%; // Flexbugs #4: https://github.com/philipwalton/flexbugs#flexbug-4\n      }\n\n      .row-cols#{$infix}-auto > * {\n        @include make-col-auto();\n      }\n\n      @if $grid-row-columns > 0 {\n        @for $i from 1 through $grid-row-columns {\n          .row-cols#{$infix}-#{$i} {\n            @include row-cols($i);\n          }\n        }\n      }\n\n      .col#{$infix}-auto {\n        @include make-col-auto();\n      }\n\n      @if $columns > 0 {\n        @for $i from 1 through $columns {\n          .col#{$infix}-#{$i} {\n            @include make-col($i, $columns);\n          }\n        }\n\n        // `$columns - 1` because offsetting by the width of an entire row isn't possible\n        @for $i from 0 through ($columns - 1) {\n          @if not ($infix == \"\" and $i == 0) { // Avoid emitting useless .offset-0\n            .offset#{$infix}-#{$i} {\n              @include make-col-offset($i, $columns);\n            }\n          }\n        }\n      }\n\n      // Gutters\n      //\n      // Make use of `.g-*`, `.gx-*` or `.gy-*` utilities to change spacing between the columns.\n      @each $key, $value in $gutters {\n        .g#{$infix}-#{$key},\n        .gx#{$infix}-#{$key} {\n          --#{$prefix}gutter-x: #{$value};\n        }\n\n        .g#{$infix}-#{$key},\n        .gy#{$infix}-#{$key} {\n          --#{$prefix}gutter-y: #{$value};\n        }\n      }\n    }\n  }\n}\n\n@mixin make-cssgrid($columns: $grid-columns, $breakpoints: $grid-breakpoints) {\n  @each $breakpoint in map-keys($breakpoints) {\n    $infix: breakpoint-infix($breakpoint, $breakpoints);\n\n    @include media-breakpoint-up($breakpoint, $breakpoints) {\n      @if $columns > 0 {\n        @for $i from 1 through $columns {\n          .g-col#{$infix}-#{$i} {\n            grid-column: auto / span $i;\n          }\n        }\n\n        // Start with `1` because `0` is and invalid value.\n        // Ends with `$columns - 1` because offsetting by the width of an entire row isn't possible.\n        @for $i from 1 through ($columns - 1) {\n          .g-start#{$infix}-#{$i} {\n            grid-column-start: $i;\n          }\n        }\n      }\n    }\n  }\n}\n","//\n// Basic Bootstrap table\n//\n\n.table {\n  // Reset needed for nesting tables\n  --#{$prefix}table-color-type: initial;\n  --#{$prefix}table-bg-type: initial;\n  --#{$prefix}table-color-state: initial;\n  --#{$prefix}table-bg-state: initial;\n  // End of reset\n  --#{$prefix}table-color: #{$table-color};\n  --#{$prefix}table-bg: #{$table-bg};\n  --#{$prefix}table-border-color: #{$table-border-color};\n  --#{$prefix}table-accent-bg: #{$table-accent-bg};\n  --#{$prefix}table-striped-color: #{$table-striped-color};\n  --#{$prefix}table-striped-bg: #{$table-striped-bg};\n  --#{$prefix}table-active-color: #{$table-active-color};\n  --#{$prefix}table-active-bg: #{$table-active-bg};\n  --#{$prefix}table-hover-color: #{$table-hover-color};\n  --#{$prefix}table-hover-bg: #{$table-hover-bg};\n\n  width: 100%;\n  margin-bottom: $spacer;\n  vertical-align: $table-cell-vertical-align;\n  border-color: var(--#{$prefix}table-border-color);\n\n  // Target th & td\n  // We need the child combinator to prevent styles leaking to nested tables which doesn't have a `.table` class.\n  // We use the universal selectors here to simplify the selector (else we would need 6 different selectors).\n  // Another advantage is that this generates less code and makes the selector less specific making it easier to override.\n  // stylelint-disable-next-line selector-max-universal\n  > :not(caption) > * > * {\n    padding: $table-cell-padding-y $table-cell-padding-x;\n    // Following the precept of cascades: https://codepen.io/miriamsuzanne/full/vYNgodb\n    color: var(--#{$prefix}table-color-state, var(--#{$prefix}table-color-type, var(--#{$prefix}table-color)));\n    background-color: var(--#{$prefix}table-bg);\n    border-bottom-width: $table-border-width;\n    box-shadow: inset 0 0 0 9999px var(--#{$prefix}table-bg-state, var(--#{$prefix}table-bg-type, var(--#{$prefix}table-accent-bg)));\n  }\n\n  > tbody {\n    vertical-align: inherit;\n  }\n\n  > thead {\n    vertical-align: bottom;\n  }\n}\n\n.table-group-divider {\n  border-top: calc(#{$table-border-width} * 2) solid $table-group-separator-color; // stylelint-disable-line function-disallowed-list\n}\n\n//\n// Change placement of captions with a class\n//\n\n.caption-top {\n  caption-side: top;\n}\n\n\n//\n// Condensed table w/ half padding\n//\n\n.table-sm {\n  // stylelint-disable-next-line selector-max-universal\n  > :not(caption) > * > * {\n    padding: $table-cell-padding-y-sm $table-cell-padding-x-sm;\n  }\n}\n\n\n// Border versions\n//\n// Add or remove borders all around the table and between all the columns.\n//\n// When borders are added on all sides of the cells, the corners can render odd when\n// these borders do not have the same color or if they are semi-transparent.\n// Therefor we add top and border bottoms to the `tr`s and left and right borders\n// to the `td`s or `th`s\n\n.table-bordered {\n  > :not(caption) > * {\n    border-width: $table-border-width 0;\n\n    // stylelint-disable-next-line selector-max-universal\n    > * {\n      border-width: 0 $table-border-width;\n    }\n  }\n}\n\n.table-borderless {\n  // stylelint-disable-next-line selector-max-universal\n  > :not(caption) > * > * {\n    border-bottom-width: 0;\n  }\n\n  > :not(:first-child) {\n    border-top-width: 0;\n  }\n}\n\n// Zebra-striping\n//\n// Default zebra-stripe styles (alternating gray and transparent backgrounds)\n\n// For rows\n.table-striped {\n  > tbody > tr:nth-of-type(#{$table-striped-order}) > * {\n    --#{$prefix}table-color-type: var(--#{$prefix}table-striped-color);\n    --#{$prefix}table-bg-type: var(--#{$prefix}table-striped-bg);\n  }\n}\n\n// For columns\n.table-striped-columns {\n  > :not(caption) > tr > :nth-child(#{$table-striped-columns-order}) {\n    --#{$prefix}table-color-type: var(--#{$prefix}table-striped-color);\n    --#{$prefix}table-bg-type: var(--#{$prefix}table-striped-bg);\n  }\n}\n\n// Active table\n//\n// The `.table-active` class can be added to highlight rows or cells\n\n.table-active {\n  --#{$prefix}table-color-state: var(--#{$prefix}table-active-color);\n  --#{$prefix}table-bg-state: var(--#{$prefix}table-active-bg);\n}\n\n// Hover effect\n//\n// Placed here since it has to come after the potential zebra striping\n\n.table-hover {\n  > tbody > tr:hover > * {\n    --#{$prefix}table-color-state: var(--#{$prefix}table-hover-color);\n    --#{$prefix}table-bg-state: var(--#{$prefix}table-hover-bg);\n  }\n}\n\n\n// Table variants\n//\n// Table variants set the table cell backgrounds, border colors\n// and the colors of the striped, hovered & active tables\n\n@each $color, $value in $table-variants {\n  @include table-variant($color, $value);\n}\n\n// Responsive tables\n//\n// Generate series of `.table-responsive-*` classes for configuring the screen\n// size of where your table will overflow.\n\n@each $breakpoint in map-keys($grid-breakpoints) {\n  $infix: breakpoint-infix($breakpoint, $grid-breakpoints);\n\n  @include media-breakpoint-down($breakpoint) {\n    .table-responsive#{$infix} {\n      overflow-x: auto;\n      -webkit-overflow-scrolling: touch;\n    }\n  }\n}\n","// scss-docs-start table-variant\n@mixin table-variant($state, $background) {\n  .table-#{$state} {\n    $color: color-contrast(opaque($body-bg, $background));\n    $hover-bg: mix($color, $background, percentage($table-hover-bg-factor));\n    $striped-bg: mix($color, $background, percentage($table-striped-bg-factor));\n    $active-bg: mix($color, $background, percentage($table-active-bg-factor));\n    $table-border-color: mix($color, $background, percentage($table-border-factor));\n\n    --#{$prefix}table-color: #{$color};\n    --#{$prefix}table-bg: #{$background};\n    --#{$prefix}table-border-color: #{$table-border-color};\n    --#{$prefix}table-striped-bg: #{$striped-bg};\n    --#{$prefix}table-striped-color: #{color-contrast($striped-bg)};\n    --#{$prefix}table-active-bg: #{$active-bg};\n    --#{$prefix}table-active-color: #{color-contrast($active-bg)};\n    --#{$prefix}table-hover-bg: #{$hover-bg};\n    --#{$prefix}table-hover-color: #{color-contrast($hover-bg)};\n\n    color: var(--#{$prefix}table-color);\n    border-color: var(--#{$prefix}table-border-color);\n  }\n}\n// scss-docs-end table-variant\n","//\n// Labels\n//\n\n.form-label {\n  margin-bottom: $form-label-margin-bottom;\n  @include font-size($form-label-font-size);\n  font-style: $form-label-font-style;\n  font-weight: $form-label-font-weight;\n  color: $form-label-color;\n}\n\n// For use with horizontal and inline forms, when you need the label (or legend)\n// text to align with the form controls.\n.col-form-label {\n  padding-top: add($input-padding-y, $input-border-width);\n  padding-bottom: add($input-padding-y, $input-border-width);\n  margin-bottom: 0; // Override the `<legend>` default\n  @include font-size(inherit); // Override the `<legend>` default\n  font-style: $form-label-font-style;\n  font-weight: $form-label-font-weight;\n  line-height: $input-line-height;\n  color: $form-label-color;\n}\n\n.col-form-label-lg {\n  padding-top: add($input-padding-y-lg, $input-border-width);\n  padding-bottom: add($input-padding-y-lg, $input-border-width);\n  @include font-size($input-font-size-lg);\n}\n\n.col-form-label-sm {\n  padding-top: add($input-padding-y-sm, $input-border-width);\n  padding-bottom: add($input-padding-y-sm, $input-border-width);\n  @include font-size($input-font-size-sm);\n}\n","//\n// Form text\n//\n\n.form-text {\n  margin-top: $form-text-margin-top;\n  @include font-size($form-text-font-size);\n  font-style: $form-text-font-style;\n  font-weight: $form-text-font-weight;\n  color: $form-text-color;\n}\n","//\n// General form controls (plus a few specific high-level interventions)\n//\n\n.form-control {\n  display: block;\n  width: 100%;\n  padding: $input-padding-y $input-padding-x;\n  font-family: $input-font-family;\n  @include font-size($input-font-size);\n  font-weight: $input-font-weight;\n  line-height: $input-line-height;\n  color: $input-color;\n  appearance: none; // Fix appearance for date inputs in Safari\n  background-color: $input-bg;\n  background-clip: padding-box;\n  border: $input-border-width solid $input-border-color;\n\n  // Note: This has no effect on <select>s in some browsers, due to the limited stylability of `<select>`s in CSS.\n  @include border-radius($input-border-radius, 0);\n\n  @include box-shadow($input-box-shadow);\n  @include transition($input-transition);\n\n  &[type=\"file\"] {\n    overflow: hidden; // prevent pseudo element button overlap\n\n    &:not(:disabled):not([readonly]) {\n      cursor: pointer;\n    }\n  }\n\n  // Customize the `:focus` state to imitate native WebKit styles.\n  &:focus {\n    color: $input-focus-color;\n    background-color: $input-focus-bg;\n    border-color: $input-focus-border-color;\n    outline: 0;\n    @if $enable-shadows {\n      @include box-shadow($input-box-shadow, $input-focus-box-shadow);\n    } @else {\n      // Avoid using mixin so we can pass custom focus shadow properly\n      box-shadow: $input-focus-box-shadow;\n    }\n  }\n\n  &::-webkit-date-and-time-value {\n    // On Android Chrome, form-control's \"width: 100%\" makes the input width too small\n    // Tested under Android 11 / Chrome 89, Android 12 / Chrome 100, Android 13 / Chrome 109\n    //\n    // On iOS Safari, form-control's \"appearance: none\" + \"width: 100%\" makes the input width too small\n    // Tested under iOS 16.2 / Safari 16.2\n    min-width: 85px; // Seems to be a good minimum safe width\n\n    // Add some height to date inputs on iOS\n    // https://github.com/twbs/bootstrap/issues/23307\n    // TODO: we can remove this workaround once https://bugs.webkit.org/show_bug.cgi?id=198959 is resolved\n    // Multiply line-height by 1em if it has no unit\n    height: if(unit($input-line-height) == \"\", $input-line-height * 1em, $input-line-height);\n\n    // Android Chrome type=\"date\" is taller than the other inputs\n    // because of \"margin: 1px 24px 1px 4px\" inside the shadow DOM\n    // Tested under Android 11 / Chrome 89, Android 12 / Chrome 100, Android 13 / Chrome 109\n    margin: 0;\n  }\n\n  // Prevent excessive date input height in Webkit\n  // https://github.com/twbs/bootstrap/issues/34433\n  &::-webkit-datetime-edit {\n    display: block;\n    padding: 0;\n  }\n\n  // Placeholder\n  &::placeholder {\n    color: $input-placeholder-color;\n    // Override Firefox's unusual default opacity; see https://github.com/twbs/bootstrap/pull/11526.\n    opacity: 1;\n  }\n\n  // Disabled inputs\n  //\n  // HTML5 says that controls under a fieldset > legend:first-child won't be\n  // disabled if the fieldset is disabled. Due to implementation difficulty, we\n  // don't honor that edge case; we style them as disabled anyway.\n  &:disabled {\n    color: $input-disabled-color;\n    background-color: $input-disabled-bg;\n    border-color: $input-disabled-border-color;\n    // iOS fix for unreadable disabled content; see https://github.com/twbs/bootstrap/issues/11655.\n    opacity: 1;\n  }\n\n  // File input buttons theming\n  &::file-selector-button {\n    padding: $input-padding-y $input-padding-x;\n    margin: (-$input-padding-y) (-$input-padding-x);\n    margin-inline-end: $input-padding-x;\n    color: $form-file-button-color;\n    @include gradient-bg($form-file-button-bg);\n    pointer-events: none;\n    border-color: inherit;\n    border-style: solid;\n    border-width: 0;\n    border-inline-end-width: $input-border-width;\n    border-radius: 0; // stylelint-disable-line property-disallowed-list\n    @include transition($btn-transition);\n  }\n\n  &:hover:not(:disabled):not([readonly])::file-selector-button {\n    background-color: $form-file-button-hover-bg;\n  }\n}\n\n// Readonly controls as plain text\n//\n// Apply class to a readonly input to make it appear like regular plain\n// text (without any border, background color, focus indicator)\n\n.form-control-plaintext {\n  display: block;\n  width: 100%;\n  padding: $input-padding-y 0;\n  margin-bottom: 0; // match inputs if this class comes on inputs with default margins\n  line-height: $input-line-height;\n  color: $input-plaintext-color;\n  background-color: transparent;\n  border: solid transparent;\n  border-width: $input-border-width 0;\n\n  &:focus {\n    outline: 0;\n  }\n\n  &.form-control-sm,\n  &.form-control-lg {\n    padding-right: 0;\n    padding-left: 0;\n  }\n}\n\n// Form control sizing\n//\n// Build on `.form-control` with modifier classes to decrease or increase the\n// height and font-size of form controls.\n//\n// Repeated in `_input_group.scss` to avoid Sass extend issues.\n\n.form-control-sm {\n  min-height: $input-height-sm;\n  padding: $input-padding-y-sm $input-padding-x-sm;\n  @include font-size($input-font-size-sm);\n  @include border-radius($input-border-radius-sm);\n\n  &::file-selector-button {\n    padding: $input-padding-y-sm $input-padding-x-sm;\n    margin: (-$input-padding-y-sm) (-$input-padding-x-sm);\n    margin-inline-end: $input-padding-x-sm;\n  }\n}\n\n.form-control-lg {\n  min-height: $input-height-lg;\n  padding: $input-padding-y-lg $input-padding-x-lg;\n  @include font-size($input-font-size-lg);\n  @include border-radius($input-border-radius-lg);\n\n  &::file-selector-button {\n    padding: $input-padding-y-lg $input-padding-x-lg;\n    margin: (-$input-padding-y-lg) (-$input-padding-x-lg);\n    margin-inline-end: $input-padding-x-lg;\n  }\n}\n\n// Make sure textareas don't shrink too much when resized\n// https://github.com/twbs/bootstrap/pull/29124\n// stylelint-disable selector-no-qualifying-type\ntextarea {\n  &.form-control {\n    min-height: $input-height;\n  }\n\n  &.form-control-sm {\n    min-height: $input-height-sm;\n  }\n\n  &.form-control-lg {\n    min-height: $input-height-lg;\n  }\n}\n// stylelint-enable selector-no-qualifying-type\n\n.form-control-color {\n  width: $form-color-width;\n  height: $input-height;\n  padding: $input-padding-y;\n\n  &:not(:disabled):not([readonly]) {\n    cursor: pointer;\n  }\n\n  &::-moz-color-swatch {\n    border: 0 !important; // stylelint-disable-line declaration-no-important\n    @include border-radius($input-border-radius);\n  }\n\n  &::-webkit-color-swatch {\n    border: 0 !important; // stylelint-disable-line declaration-no-important\n    @include border-radius($input-border-radius);\n  }\n\n  &.form-control-sm { height: $input-height-sm; }\n  &.form-control-lg { height: $input-height-lg; }\n}\n","// stylelint-disable property-disallowed-list\n@mixin transition($transition...) {\n  @if length($transition) == 0 {\n    $transition: $transition-base;\n  }\n\n  @if length($transition) > 1 {\n    @each $value in $transition {\n      @if $value == null or $value == none {\n        @warn \"The keyword 'none' or 'null' must be used as a single argument.\";\n      }\n    }\n  }\n\n  @if $enable-transitions {\n    @if nth($transition, 1) != null {\n      transition: $transition;\n    }\n\n    @if $enable-reduced-motion and nth($transition, 1) != null and nth($transition, 1) != none {\n      @media (prefers-reduced-motion: reduce) {\n        transition: none;\n      }\n    }\n  }\n}\n","// Gradients\n\n// scss-docs-start gradient-bg-mixin\n@mixin gradient-bg($color: null) {\n  background-color: $color;\n\n  @if $enable-gradients {\n    background-image: var(--#{$prefix}gradient);\n  }\n}\n// scss-docs-end gradient-bg-mixin\n\n// scss-docs-start gradient-mixins\n// Horizontal gradient, from left to right\n//\n// Creates two color stops, start and end, by specifying a color and position for each color stop.\n@mixin gradient-x($start-color: $gray-700, $end-color: $gray-800, $start-percent: 0%, $end-percent: 100%) {\n  background-image: linear-gradient(to right, $start-color $start-percent, $end-color $end-percent);\n}\n\n// Vertical gradient, from top to bottom\n//\n// Creates two color stops, start and end, by specifying a color and position for each color stop.\n@mixin gradient-y($start-color: $gray-700, $end-color: $gray-800, $start-percent: null, $end-percent: null) {\n  background-image: linear-gradient(to bottom, $start-color $start-percent, $end-color $end-percent);\n}\n\n@mixin gradient-directional($start-color: $gray-700, $end-color: $gray-800, $deg: 45deg) {\n  background-image: linear-gradient($deg, $start-color, $end-color);\n}\n\n@mixin gradient-x-three-colors($start-color: $blue, $mid-color: $purple, $color-stop: 50%, $end-color: $red) {\n  background-image: linear-gradient(to right, $start-color, $mid-color $color-stop, $end-color);\n}\n\n@mixin gradient-y-three-colors($start-color: $blue, $mid-color: $purple, $color-stop: 50%, $end-color: $red) {\n  background-image: linear-gradient($start-color, $mid-color $color-stop, $end-color);\n}\n\n@mixin gradient-radial($inner-color: $gray-700, $outer-color: $gray-800) {\n  background-image: radial-gradient(circle, $inner-color, $outer-color);\n}\n\n@mixin gradient-striped($color: rgba($white, .15), $angle: 45deg) {\n  background-image: linear-gradient($angle, $color 25%, transparent 25%, transparent 50%, $color 50%, $color 75%, transparent 75%, transparent);\n}\n// scss-docs-end gradient-mixins\n","// Select\n//\n// Replaces the browser default select with a custom one, mostly pulled from\n// https://primer.github.io/.\n\n.form-select {\n  --#{$prefix}form-select-bg-img: #{escape-svg($form-select-indicator)};\n\n  display: block;\n  width: 100%;\n  padding: $form-select-padding-y $form-select-indicator-padding $form-select-padding-y $form-select-padding-x;\n  font-family: $form-select-font-family;\n  @include font-size($form-select-font-size);\n  font-weight: $form-select-font-weight;\n  line-height: $form-select-line-height;\n  color: $form-select-color;\n  appearance: none;\n  background-color: $form-select-bg;\n  background-image: var(--#{$prefix}form-select-bg-img), var(--#{$prefix}form-select-bg-icon, none);\n  background-repeat: no-repeat;\n  background-position: $form-select-bg-position;\n  background-size: $form-select-bg-size;\n  border: $form-select-border-width solid $form-select-border-color;\n  @include border-radius($form-select-border-radius, 0);\n  @include box-shadow($form-select-box-shadow);\n  @include transition($form-select-transition);\n\n  &:focus {\n    border-color: $form-select-focus-border-color;\n    outline: 0;\n    @if $enable-shadows {\n      @include box-shadow($form-select-box-shadow, $form-select-focus-box-shadow);\n    } @else {\n      // Avoid using mixin so we can pass custom focus shadow properly\n      box-shadow: $form-select-focus-box-shadow;\n    }\n  }\n\n  &[multiple],\n  &[size]:not([size=\"1\"]) {\n    padding-right: $form-select-padding-x;\n    background-image: none;\n  }\n\n  &:disabled {\n    color: $form-select-disabled-color;\n    background-color: $form-select-disabled-bg;\n    border-color: $form-select-disabled-border-color;\n  }\n\n  // Remove outline from select box in FF\n  &:-moz-focusring {\n    color: transparent;\n    text-shadow: 0 0 0 $form-select-color;\n  }\n}\n\n.form-select-sm {\n  padding-top: $form-select-padding-y-sm;\n  padding-bottom: $form-select-padding-y-sm;\n  padding-left: $form-select-padding-x-sm;\n  @include font-size($form-select-font-size-sm);\n  @include border-radius($form-select-border-radius-sm);\n}\n\n.form-select-lg {\n  padding-top: $form-select-padding-y-lg;\n  padding-bottom: $form-select-padding-y-lg;\n  padding-left: $form-select-padding-x-lg;\n  @include font-size($form-select-font-size-lg);\n  @include border-radius($form-select-border-radius-lg);\n}\n\n@if $enable-dark-mode {\n  @include color-mode(dark) {\n    .form-select {\n      --#{$prefix}form-select-bg-img: #{escape-svg($form-select-indicator-dark)};\n    }\n  }\n}\n","//\n// Check/radio\n//\n\n.form-check {\n  display: block;\n  min-height: $form-check-min-height;\n  padding-left: $form-check-padding-start;\n  margin-bottom: $form-check-margin-bottom;\n\n  .form-check-input {\n    float: left;\n    margin-left: $form-check-padding-start * -1;\n  }\n}\n\n.form-check-reverse {\n  padding-right: $form-check-padding-start;\n  padding-left: 0;\n  text-align: right;\n\n  .form-check-input {\n    float: right;\n    margin-right: $form-check-padding-start * -1;\n    margin-left: 0;\n  }\n}\n\n.form-check-input {\n  --#{$prefix}form-check-bg: #{$form-check-input-bg};\n\n  flex-shrink: 0;\n  width: $form-check-input-width;\n  height: $form-check-input-width;\n  margin-top: ($line-height-base - $form-check-input-width) * .5; // line-height minus check height\n  vertical-align: top;\n  appearance: none;\n  background-color: var(--#{$prefix}form-check-bg);\n  background-image: var(--#{$prefix}form-check-bg-image);\n  background-repeat: no-repeat;\n  background-position: center;\n  background-size: contain;\n  border: $form-check-input-border;\n  print-color-adjust: exact; // Keep themed appearance for print\n  @include transition($form-check-transition);\n\n  &[type=\"checkbox\"] {\n    @include border-radius($form-check-input-border-radius);\n  }\n\n  &[type=\"radio\"] {\n    // stylelint-disable-next-line property-disallowed-list\n    border-radius: $form-check-radio-border-radius;\n  }\n\n  &:active {\n    filter: $form-check-input-active-filter;\n  }\n\n  &:focus {\n    border-color: $form-check-input-focus-border;\n    outline: 0;\n    box-shadow: $form-check-input-focus-box-shadow;\n  }\n\n  &:checked {\n    background-color: $form-check-input-checked-bg-color;\n    border-color: $form-check-input-checked-border-color;\n\n    &[type=\"checkbox\"] {\n      @if $enable-gradients {\n        --#{$prefix}form-check-bg-image: #{escape-svg($form-check-input-checked-bg-image)}, var(--#{$prefix}gradient);\n      } @else {\n        --#{$prefix}form-check-bg-image: #{escape-svg($form-check-input-checked-bg-image)};\n      }\n    }\n\n    &[type=\"radio\"] {\n      @if $enable-gradients {\n        --#{$prefix}form-check-bg-image: #{escape-svg($form-check-radio-checked-bg-image)}, var(--#{$prefix}gradient);\n      } @else {\n        --#{$prefix}form-check-bg-image: #{escape-svg($form-check-radio-checked-bg-image)};\n      }\n    }\n  }\n\n  &[type=\"checkbox\"]:indeterminate {\n    background-color: $form-check-input-indeterminate-bg-color;\n    border-color: $form-check-input-indeterminate-border-color;\n\n    @if $enable-gradients {\n      --#{$prefix}form-check-bg-image: #{escape-svg($form-check-input-indeterminate-bg-image)}, var(--#{$prefix}gradient);\n    } @else {\n      --#{$prefix}form-check-bg-image: #{escape-svg($form-check-input-indeterminate-bg-image)};\n    }\n  }\n\n  &:disabled {\n    pointer-events: none;\n    filter: none;\n    opacity: $form-check-input-disabled-opacity;\n  }\n\n  // Use disabled attribute in addition of :disabled pseudo-class\n  // See: https://github.com/twbs/bootstrap/issues/28247\n  &[disabled],\n  &:disabled {\n    ~ .form-check-label {\n      cursor: default;\n      opacity: $form-check-label-disabled-opacity;\n    }\n  }\n}\n\n.form-check-label {\n  color: $form-check-label-color;\n  cursor: $form-check-label-cursor;\n}\n\n//\n// Switch\n//\n\n.form-switch {\n  padding-left: $form-switch-padding-start;\n\n  .form-check-input {\n    --#{$prefix}form-switch-bg: #{escape-svg($form-switch-bg-image)};\n\n    width: $form-switch-width;\n    margin-left: $form-switch-padding-start * -1;\n    background-image: var(--#{$prefix}form-switch-bg);\n    background-position: left center;\n    @include border-radius($form-switch-border-radius);\n    @include transition($form-switch-transition);\n\n    &:focus {\n      --#{$prefix}form-switch-bg: #{escape-svg($form-switch-focus-bg-image)};\n    }\n\n    &:checked {\n      background-position: $form-switch-checked-bg-position;\n\n      @if $enable-gradients {\n        --#{$prefix}form-switch-bg: #{escape-svg($form-switch-checked-bg-image)}, var(--#{$prefix}gradient);\n      } @else {\n        --#{$prefix}form-switch-bg: #{escape-svg($form-switch-checked-bg-image)};\n      }\n    }\n  }\n\n  &.form-check-reverse {\n    padding-right: $form-switch-padding-start;\n    padding-left: 0;\n\n    .form-check-input {\n      margin-right: $form-switch-padding-start * -1;\n      margin-left: 0;\n    }\n  }\n}\n\n.form-check-inline {\n  display: inline-block;\n  margin-right: $form-check-inline-margin-end;\n}\n\n.btn-check {\n  position: absolute;\n  clip: rect(0, 0, 0, 0);\n  pointer-events: none;\n\n  &[disabled],\n  &:disabled {\n    + .btn {\n      pointer-events: none;\n      filter: none;\n      opacity: $form-check-btn-check-disabled-opacity;\n    }\n  }\n}\n\n@if $enable-dark-mode {\n  @include color-mode(dark) {\n    .form-switch .form-check-input:not(:checked):not(:focus) {\n      --#{$prefix}form-switch-bg: #{escape-svg($form-switch-bg-image-dark)};\n    }\n  }\n}\n","// Range\n//\n// Style range inputs the same across browsers. Vendor-specific rules for pseudo\n// elements cannot be mixed. As such, there are no shared styles for focus or\n// active states on prefixed selectors.\n\n.form-range {\n  width: 100%;\n  height: add($form-range-thumb-height, $form-range-thumb-focus-box-shadow-width * 2);\n  padding: 0; // Need to reset padding\n  appearance: none;\n  background-color: transparent;\n\n  &:focus {\n    outline: 0;\n\n    // Pseudo-elements must be split across multiple rulesets to have an effect.\n    // No box-shadow() mixin for focus accessibility.\n    &::-webkit-slider-thumb { box-shadow: $form-range-thumb-focus-box-shadow; }\n    &::-moz-range-thumb     { box-shadow: $form-range-thumb-focus-box-shadow; }\n  }\n\n  &::-moz-focus-outer {\n    border: 0;\n  }\n\n  &::-webkit-slider-thumb {\n    width: $form-range-thumb-width;\n    height: $form-range-thumb-height;\n    margin-top: ($form-range-track-height - $form-range-thumb-height) * .5; // Webkit specific\n    appearance: none;\n    @include gradient-bg($form-range-thumb-bg);\n    border: $form-range-thumb-border;\n    @include border-radius($form-range-thumb-border-radius);\n    @include box-shadow($form-range-thumb-box-shadow);\n    @include transition($form-range-thumb-transition);\n\n    &:active {\n      @include gradient-bg($form-range-thumb-active-bg);\n    }\n  }\n\n  &::-webkit-slider-runnable-track {\n    width: $form-range-track-width;\n    height: $form-range-track-height;\n    color: transparent; // Why?\n    cursor: $form-range-track-cursor;\n    background-color: $form-range-track-bg;\n    border-color: transparent;\n    @include border-radius($form-range-track-border-radius);\n    @include box-shadow($form-range-track-box-shadow);\n  }\n\n  &::-moz-range-thumb {\n    width: $form-range-thumb-width;\n    height: $form-range-thumb-height;\n    appearance: none;\n    @include gradient-bg($form-range-thumb-bg);\n    border: $form-range-thumb-border;\n    @include border-radius($form-range-thumb-border-radius);\n    @include box-shadow($form-range-thumb-box-shadow);\n    @include transition($form-range-thumb-transition);\n\n    &:active {\n      @include gradient-bg($form-range-thumb-active-bg);\n    }\n  }\n\n  &::-moz-range-track {\n    width: $form-range-track-width;\n    height: $form-range-track-height;\n    color: transparent;\n    cursor: $form-range-track-cursor;\n    background-color: $form-range-track-bg;\n    border-color: transparent; // Firefox specific?\n    @include border-radius($form-range-track-border-radius);\n    @include box-shadow($form-range-track-box-shadow);\n  }\n\n  &:disabled {\n    pointer-events: none;\n\n    &::-webkit-slider-thumb {\n      background-color: $form-range-thumb-disabled-bg;\n    }\n\n    &::-moz-range-thumb {\n      background-color: $form-range-thumb-disabled-bg;\n    }\n  }\n}\n",".form-floating {\n  position: relative;\n\n  > .form-control,\n  > .form-control-plaintext,\n  > .form-select {\n    height: $form-floating-height;\n    min-height: $form-floating-height;\n    line-height: $form-floating-line-height;\n  }\n\n  > label {\n    position: absolute;\n    top: 0;\n    left: 0;\n    z-index: 2;\n    height: 100%; // allow textareas\n    padding: $form-floating-padding-y $form-floating-padding-x;\n    overflow: hidden;\n    text-align: start;\n    text-overflow: ellipsis;\n    white-space: nowrap;\n    pointer-events: none;\n    border: $input-border-width solid transparent; // Required for aligning label's text with the input as it affects inner box model\n    transform-origin: 0 0;\n    @include transition($form-floating-transition);\n  }\n\n  > .form-control,\n  > .form-control-plaintext {\n    padding: $form-floating-padding-y $form-floating-padding-x;\n\n    &::placeholder {\n      color: transparent;\n    }\n\n    &:focus,\n    &:not(:placeholder-shown) {\n      padding-top: $form-floating-input-padding-t;\n      padding-bottom: $form-floating-input-padding-b;\n    }\n    // Duplicated because `:-webkit-autofill` invalidates other selectors when grouped\n    &:-webkit-autofill {\n      padding-top: $form-floating-input-padding-t;\n      padding-bottom: $form-floating-input-padding-b;\n    }\n  }\n\n  > .form-select {\n    padding-top: $form-floating-input-padding-t;\n    padding-bottom: $form-floating-input-padding-b;\n  }\n\n  > .form-control:focus,\n  > .form-control:not(:placeholder-shown),\n  > .form-control-plaintext,\n  > .form-select {\n    ~ label {\n      color: rgba(var(--#{$prefix}body-color-rgb), #{$form-floating-label-opacity});\n      transform: $form-floating-label-transform;\n\n      &::after {\n        position: absolute;\n        inset: $form-floating-padding-y ($form-floating-padding-x * .5);\n        z-index: -1;\n        height: $form-floating-label-height;\n        content: \"\";\n        background-color: $input-bg;\n        @include border-radius($input-border-radius);\n      }\n    }\n  }\n  // Duplicated because `:-webkit-autofill` invalidates other selectors when grouped\n  > .form-control:-webkit-autofill {\n    ~ label {\n      color: rgba(var(--#{$prefix}body-color-rgb), #{$form-floating-label-opacity});\n      transform: $form-floating-label-transform;\n    }\n  }\n\n  > .form-control-plaintext {\n    ~ label {\n      border-width: $input-border-width 0; // Required to properly position label text - as explained above\n    }\n  }\n\n  > :disabled ~ label,\n  > .form-control:disabled ~ label { // Required for `.form-control`s because of specificity\n    color: $form-floating-label-disabled-color;\n\n    &::after {\n      background-color: $input-disabled-bg;\n    }\n  }\n}\n","//\n// Base styles\n//\n\n.input-group {\n  position: relative;\n  display: flex;\n  flex-wrap: wrap; // For form validation feedback\n  align-items: stretch;\n  width: 100%;\n\n  > .form-control,\n  > .form-select,\n  > .form-floating {\n    position: relative; // For focus state's z-index\n    flex: 1 1 auto;\n    width: 1%;\n    min-width: 0; // https://stackoverflow.com/questions/36247140/why-dont-flex-items-shrink-past-content-size\n  }\n\n  // Bring the \"active\" form control to the top of surrounding elements\n  > .form-control:focus,\n  > .form-select:focus,\n  > .form-floating:focus-within {\n    z-index: 5;\n  }\n\n  // Ensure buttons are always above inputs for more visually pleasing borders.\n  // This isn't needed for `.input-group-text` since it shares the same border-color\n  // as our inputs.\n  .btn {\n    position: relative;\n    z-index: 2;\n\n    &:focus {\n      z-index: 5;\n    }\n  }\n}\n\n\n// Textual addons\n//\n// Serves as a catch-all element for any text or radio/checkbox input you wish\n// to prepend or append to an input.\n\n.input-group-text {\n  display: flex;\n  align-items: center;\n  padding: $input-group-addon-padding-y $input-group-addon-padding-x;\n  @include font-size($input-font-size); // Match inputs\n  font-weight: $input-group-addon-font-weight;\n  line-height: $input-line-height;\n  color: $input-group-addon-color;\n  text-align: center;\n  white-space: nowrap;\n  background-color: $input-group-addon-bg;\n  border: $input-border-width solid $input-group-addon-border-color;\n  @include border-radius($input-border-radius);\n}\n\n\n// Sizing\n//\n// Remix the default form control sizing classes into new ones for easier\n// manipulation.\n\n.input-group-lg > .form-control,\n.input-group-lg > .form-select,\n.input-group-lg > .input-group-text,\n.input-group-lg > .btn {\n  padding: $input-padding-y-lg $input-padding-x-lg;\n  @include font-size($input-font-size-lg);\n  @include border-radius($input-border-radius-lg);\n}\n\n.input-group-sm > .form-control,\n.input-group-sm > .form-select,\n.input-group-sm > .input-group-text,\n.input-group-sm > .btn {\n  padding: $input-padding-y-sm $input-padding-x-sm;\n  @include font-size($input-font-size-sm);\n  @include border-radius($input-border-radius-sm);\n}\n\n.input-group-lg > .form-select,\n.input-group-sm > .form-select {\n  padding-right: $form-select-padding-x + $form-select-indicator-padding;\n}\n\n\n// Rounded corners\n//\n// These rulesets must come after the sizing ones to properly override sm and lg\n// border-radius values when extending. They're more specific than we'd like\n// with the `.input-group >` part, but without it, we cannot override the sizing.\n\n// stylelint-disable-next-line no-duplicate-selectors\n.input-group {\n  &:not(.has-validation) {\n    > :not(:last-child):not(.dropdown-toggle):not(.dropdown-menu):not(.form-floating),\n    > .dropdown-toggle:nth-last-child(n + 3),\n    > .form-floating:not(:last-child) > .form-control,\n    > .form-floating:not(:last-child) > .form-select {\n      @include border-end-radius(0);\n    }\n  }\n\n  &.has-validation {\n    > :nth-last-child(n + 3):not(.dropdown-toggle):not(.dropdown-menu):not(.form-floating),\n    > .dropdown-toggle:nth-last-child(n + 4),\n    > .form-floating:nth-last-child(n + 3) > .form-control,\n    > .form-floating:nth-last-child(n + 3) > .form-select {\n      @include border-end-radius(0);\n    }\n  }\n\n  $validation-messages: \"\";\n  @each $state in map-keys($form-validation-states) {\n    $validation-messages: $validation-messages + \":not(.\" + unquote($state) + \"-tooltip)\" + \":not(.\" + unquote($state) + \"-feedback)\";\n  }\n\n  > :not(:first-child):not(.dropdown-menu)#{$validation-messages} {\n    margin-left: calc(#{$input-border-width} * -1); // stylelint-disable-line function-disallowed-list\n    @include border-start-radius(0);\n  }\n\n  > .form-floating:not(:first-child) > .form-control,\n  > .form-floating:not(:first-child) > .form-select {\n    @include border-start-radius(0);\n  }\n}\n","// This mixin uses an `if()` technique to be compatible with Dart Sass\n// See https://github.com/sass/sass/issues/1873#issuecomment-152293725 for more details\n\n// scss-docs-start form-validation-mixins\n@mixin form-validation-state-selector($state) {\n  @if ($state == \"valid\" or $state == \"invalid\") {\n    .was-validated #{if(&, \"&\", \"\")}:#{$state},\n    #{if(&, \"&\", \"\")}.is-#{$state} {\n      @content;\n    }\n  } @else {\n    #{if(&, \"&\", \"\")}.is-#{$state} {\n      @content;\n    }\n  }\n}\n\n@mixin form-validation-state(\n  $state,\n  $color,\n  $icon,\n  $tooltip-color: color-contrast($color),\n  $tooltip-bg-color: rgba($color, $form-feedback-tooltip-opacity),\n  $focus-box-shadow: 0 0 $input-btn-focus-blur $input-focus-width rgba($color, $input-btn-focus-color-opacity),\n  $border-color: $color\n) {\n  .#{$state}-feedback {\n    display: none;\n    width: 100%;\n    margin-top: $form-feedback-margin-top;\n    @include font-size($form-feedback-font-size);\n    font-style: $form-feedback-font-style;\n    color: $color;\n  }\n\n  .#{$state}-tooltip {\n    position: absolute;\n    top: 100%;\n    z-index: 5;\n    display: none;\n    max-width: 100%; // Contain to parent when possible\n    padding: $form-feedback-tooltip-padding-y $form-feedback-tooltip-padding-x;\n    margin-top: .1rem;\n    @include font-size($form-feedback-tooltip-font-size);\n    line-height: $form-feedback-tooltip-line-height;\n    color: $tooltip-color;\n    background-color: $tooltip-bg-color;\n    @include border-radius($form-feedback-tooltip-border-radius);\n  }\n\n  @include form-validation-state-selector($state) {\n    ~ .#{$state}-feedback,\n    ~ .#{$state}-tooltip {\n      display: block;\n    }\n  }\n\n  .form-control {\n    @include form-validation-state-selector($state) {\n      border-color: $border-color;\n\n      @if $enable-validation-icons {\n        padding-right: $input-height-inner;\n        background-image: escape-svg($icon);\n        background-repeat: no-repeat;\n        background-position: right $input-height-inner-quarter center;\n        background-size: $input-height-inner-half $input-height-inner-half;\n      }\n\n      &:focus {\n        border-color: $border-color;\n        box-shadow: $focus-box-shadow;\n      }\n    }\n  }\n\n  // stylelint-disable-next-line selector-no-qualifying-type\n  textarea.form-control {\n    @include form-validation-state-selector($state) {\n      @if $enable-validation-icons {\n        padding-right: $input-height-inner;\n        background-position: top $input-height-inner-quarter right $input-height-inner-quarter;\n      }\n    }\n  }\n\n  .form-select {\n    @include form-validation-state-selector($state) {\n      border-color: $border-color;\n\n      @if $enable-validation-icons {\n        &:not([multiple]):not([size]),\n        &:not([multiple])[size=\"1\"] {\n          --#{$prefix}form-select-bg-icon: #{escape-svg($icon)};\n          padding-right: $form-select-feedback-icon-padding-end;\n          background-position: $form-select-bg-position, $form-select-feedback-icon-position;\n          background-size: $form-select-bg-size, $form-select-feedback-icon-size;\n        }\n      }\n\n      &:focus {\n        border-color: $border-color;\n        box-shadow: $focus-box-shadow;\n      }\n    }\n  }\n\n  .form-control-color {\n    @include form-validation-state-selector($state) {\n      @if $enable-validation-icons {\n        width: add($form-color-width, $input-height-inner);\n      }\n    }\n  }\n\n  .form-check-input {\n    @include form-validation-state-selector($state) {\n      border-color: $border-color;\n\n      &:checked {\n        background-color: $color;\n      }\n\n      &:focus {\n        box-shadow: $focus-box-shadow;\n      }\n\n      ~ .form-check-label {\n        color: $color;\n      }\n    }\n  }\n  .form-check-inline .form-check-input {\n    ~ .#{$state}-feedback {\n      margin-left: .5em;\n    }\n  }\n\n  .input-group {\n    > .form-control:not(:focus),\n    > .form-select:not(:focus),\n    > .form-floating:not(:focus-within) {\n      @include form-validation-state-selector($state) {\n        @if $state == \"valid\" {\n          z-index: 3;\n        } @else if $state == \"invalid\" {\n          z-index: 4;\n        }\n      }\n    }\n  }\n}\n// scss-docs-end form-validation-mixins\n","//\n// Base styles\n//\n\n.btn {\n  // scss-docs-start btn-css-vars\n  --#{$prefix}btn-padding-x: #{$btn-padding-x};\n  --#{$prefix}btn-padding-y: #{$btn-padding-y};\n  --#{$prefix}btn-font-family: #{$btn-font-family};\n  @include rfs($btn-font-size, --#{$prefix}btn-font-size);\n  --#{$prefix}btn-font-weight: #{$btn-font-weight};\n  --#{$prefix}btn-line-height: #{$btn-line-height};\n  --#{$prefix}btn-color: #{$btn-color};\n  --#{$prefix}btn-bg: transparent;\n  --#{$prefix}btn-border-width: #{$btn-border-width};\n  --#{$prefix}btn-border-color: transparent;\n  --#{$prefix}btn-border-radius: #{$btn-border-radius};\n  --#{$prefix}btn-hover-border-color: transparent;\n  --#{$prefix}btn-box-shadow: #{$btn-box-shadow};\n  --#{$prefix}btn-disabled-opacity: #{$btn-disabled-opacity};\n  --#{$prefix}btn-focus-box-shadow: 0 0 0 #{$btn-focus-width} rgba(var(--#{$prefix}btn-focus-shadow-rgb), .5);\n  // scss-docs-end btn-css-vars\n\n  display: inline-block;\n  padding: var(--#{$prefix}btn-padding-y) var(--#{$prefix}btn-padding-x);\n  font-family: var(--#{$prefix}btn-font-family);\n  @include font-size(var(--#{$prefix}btn-font-size));\n  font-weight: var(--#{$prefix}btn-font-weight);\n  line-height: var(--#{$prefix}btn-line-height);\n  color: var(--#{$prefix}btn-color);\n  text-align: center;\n  text-decoration: if($link-decoration == none, null, none);\n  white-space: $btn-white-space;\n  vertical-align: middle;\n  cursor: if($enable-button-pointers, pointer, null);\n  user-select: none;\n  border: var(--#{$prefix}btn-border-width) solid var(--#{$prefix}btn-border-color);\n  @include border-radius(var(--#{$prefix}btn-border-radius));\n  @include gradient-bg(var(--#{$prefix}btn-bg));\n  @include box-shadow(var(--#{$prefix}btn-box-shadow));\n  @include transition($btn-transition);\n\n  &:hover {\n    color: var(--#{$prefix}btn-hover-color);\n    text-decoration: if($link-hover-decoration == underline, none, null);\n    background-color: var(--#{$prefix}btn-hover-bg);\n    border-color: var(--#{$prefix}btn-hover-border-color);\n  }\n\n  .btn-check + &:hover {\n    // override for the checkbox/radio buttons\n    color: var(--#{$prefix}btn-color);\n    background-color: var(--#{$prefix}btn-bg);\n    border-color: var(--#{$prefix}btn-border-color);\n  }\n\n  &:focus-visible {\n    color: var(--#{$prefix}btn-hover-color);\n    @include gradient-bg(var(--#{$prefix}btn-hover-bg));\n    border-color: var(--#{$prefix}btn-hover-border-color);\n    outline: 0;\n    // Avoid using mixin so we can pass custom focus shadow properly\n    @if $enable-shadows {\n      box-shadow: var(--#{$prefix}btn-box-shadow), var(--#{$prefix}btn-focus-box-shadow);\n    } @else {\n      box-shadow: var(--#{$prefix}btn-focus-box-shadow);\n    }\n  }\n\n  .btn-check:focus-visible + & {\n    border-color: var(--#{$prefix}btn-hover-border-color);\n    outline: 0;\n    // Avoid using mixin so we can pass custom focus shadow properly\n    @if $enable-shadows {\n      box-shadow: var(--#{$prefix}btn-box-shadow), var(--#{$prefix}btn-focus-box-shadow);\n    } @else {\n      box-shadow: var(--#{$prefix}btn-focus-box-shadow);\n    }\n  }\n\n  .btn-check:checked + &,\n  :not(.btn-check) + &:active,\n  &:first-child:active,\n  &.active,\n  &.show {\n    color: var(--#{$prefix}btn-active-color);\n    background-color: var(--#{$prefix}btn-active-bg);\n    // Remove CSS gradients if they're enabled\n    background-image: if($enable-gradients, none, null);\n    border-color: var(--#{$prefix}btn-active-border-color);\n    @include box-shadow(var(--#{$prefix}btn-active-shadow));\n\n    &:focus-visible {\n      // Avoid using mixin so we can pass custom focus shadow properly\n      @if $enable-shadows {\n        box-shadow: var(--#{$prefix}btn-active-shadow), var(--#{$prefix}btn-focus-box-shadow);\n      } @else {\n        box-shadow: var(--#{$prefix}btn-focus-box-shadow);\n      }\n    }\n  }\n\n  &:disabled,\n  &.disabled,\n  fieldset:disabled & {\n    color: var(--#{$prefix}btn-disabled-color);\n    pointer-events: none;\n    background-color: var(--#{$prefix}btn-disabled-bg);\n    background-image: if($enable-gradients, none, null);\n    border-color: var(--#{$prefix}btn-disabled-border-color);\n    opacity: var(--#{$prefix}btn-disabled-opacity);\n    @include box-shadow(none);\n  }\n}\n\n\n//\n// Alternate buttons\n//\n\n// scss-docs-start btn-variant-loops\n@each $color, $value in $theme-colors {\n  .btn-#{$color} {\n    @if $color == \"light\" {\n      @include button-variant(\n        $value,\n        $value,\n        $hover-background: shade-color($value, $btn-hover-bg-shade-amount),\n        $hover-border: shade-color($value, $btn-hover-border-shade-amount),\n        $active-background: shade-color($value, $btn-active-bg-shade-amount),\n        $active-border: shade-color($value, $btn-active-border-shade-amount)\n      );\n    } @else if $color == \"dark\" {\n      @include button-variant(\n        $value,\n        $value,\n        $hover-background: tint-color($value, $btn-hover-bg-tint-amount),\n        $hover-border: tint-color($value, $btn-hover-border-tint-amount),\n        $active-background: tint-color($value, $btn-active-bg-tint-amount),\n        $active-border: tint-color($value, $btn-active-border-tint-amount)\n      );\n    } @else {\n      @include button-variant($value, $value);\n    }\n  }\n}\n\n@each $color, $value in $theme-colors {\n  .btn-outline-#{$color} {\n    @include button-outline-variant($value);\n  }\n}\n// scss-docs-end btn-variant-loops\n\n\n//\n// Link buttons\n//\n\n// Make a button look and behave like a link\n.btn-link {\n  --#{$prefix}btn-font-weight: #{$font-weight-normal};\n  --#{$prefix}btn-color: #{$btn-link-color};\n  --#{$prefix}btn-bg: transparent;\n  --#{$prefix}btn-border-color: transparent;\n  --#{$prefix}btn-hover-color: #{$btn-link-hover-color};\n  --#{$prefix}btn-hover-border-color: transparent;\n  --#{$prefix}btn-active-color: #{$btn-link-hover-color};\n  --#{$prefix}btn-active-border-color: transparent;\n  --#{$prefix}btn-disabled-color: #{$btn-link-disabled-color};\n  --#{$prefix}btn-disabled-border-color: transparent;\n  --#{$prefix}btn-box-shadow: 0 0 0 #000; // Can't use `none` as keyword negates all values when used with multiple shadows\n  --#{$prefix}btn-focus-shadow-rgb: #{$btn-link-focus-shadow-rgb};\n\n  text-decoration: $link-decoration;\n  @if $enable-gradients {\n    background-image: none;\n  }\n\n  &:hover,\n  &:focus-visible {\n    text-decoration: $link-hover-decoration;\n  }\n\n  &:focus-visible {\n    color: var(--#{$prefix}btn-color);\n  }\n\n  &:hover {\n    color: var(--#{$prefix}btn-hover-color);\n  }\n\n  // No need for an active state here\n}\n\n\n//\n// Button Sizes\n//\n\n.btn-lg {\n  @include button-size($btn-padding-y-lg, $btn-padding-x-lg, $btn-font-size-lg, $btn-border-radius-lg);\n}\n\n.btn-sm {\n  @include button-size($btn-padding-y-sm, $btn-padding-x-sm, $btn-font-size-sm, $btn-border-radius-sm);\n}\n","// Button variants\n//\n// Easily pump out default styles, as well as :hover, :focus, :active,\n// and disabled options for all buttons\n\n// scss-docs-start btn-variant-mixin\n@mixin button-variant(\n  $background,\n  $border,\n  $color: color-contrast($background),\n  $hover-background: if($color == $color-contrast-light, shade-color($background, $btn-hover-bg-shade-amount), tint-color($background, $btn-hover-bg-tint-amount)),\n  $hover-border: if($color == $color-contrast-light, shade-color($border, $btn-hover-border-shade-amount), tint-color($border, $btn-hover-border-tint-amount)),\n  $hover-color: color-contrast($hover-background),\n  $active-background: if($color == $color-contrast-light, shade-color($background, $btn-active-bg-shade-amount), tint-color($background, $btn-active-bg-tint-amount)),\n  $active-border: if($color == $color-contrast-light, shade-color($border, $btn-active-border-shade-amount), tint-color($border, $btn-active-border-tint-amount)),\n  $active-color: color-contrast($active-background),\n  $disabled-background: $background,\n  $disabled-border: $border,\n  $disabled-color: color-contrast($disabled-background)\n) {\n  --#{$prefix}btn-color: #{$color};\n  --#{$prefix}btn-bg: #{$background};\n  --#{$prefix}btn-border-color: #{$border};\n  --#{$prefix}btn-hover-color: #{$hover-color};\n  --#{$prefix}btn-hover-bg: #{$hover-background};\n  --#{$prefix}btn-hover-border-color: #{$hover-border};\n  --#{$prefix}btn-focus-shadow-rgb: #{to-rgb(mix($color, $border, 15%))};\n  --#{$prefix}btn-active-color: #{$active-color};\n  --#{$prefix}btn-active-bg: #{$active-background};\n  --#{$prefix}btn-active-border-color: #{$active-border};\n  --#{$prefix}btn-active-shadow: #{$btn-active-box-shadow};\n  --#{$prefix}btn-disabled-color: #{$disabled-color};\n  --#{$prefix}btn-disabled-bg: #{$disabled-background};\n  --#{$prefix}btn-disabled-border-color: #{$disabled-border};\n}\n// scss-docs-end btn-variant-mixin\n\n// scss-docs-start btn-outline-variant-mixin\n@mixin button-outline-variant(\n  $color,\n  $color-hover: color-contrast($color),\n  $active-background: $color,\n  $active-border: $color,\n  $active-color: color-contrast($active-background)\n) {\n  --#{$prefix}btn-color: #{$color};\n  --#{$prefix}btn-border-color: #{$color};\n  --#{$prefix}btn-hover-color: #{$color-hover};\n  --#{$prefix}btn-hover-bg: #{$active-background};\n  --#{$prefix}btn-hover-border-color: #{$active-border};\n  --#{$prefix}btn-focus-shadow-rgb: #{to-rgb($color)};\n  --#{$prefix}btn-active-color: #{$active-color};\n  --#{$prefix}btn-active-bg: #{$active-background};\n  --#{$prefix}btn-active-border-color: #{$active-border};\n  --#{$prefix}btn-active-shadow: #{$btn-active-box-shadow};\n  --#{$prefix}btn-disabled-color: #{$color};\n  --#{$prefix}btn-disabled-bg: transparent;\n  --#{$prefix}btn-disabled-border-color: #{$color};\n  --#{$prefix}gradient: none;\n}\n// scss-docs-end btn-outline-variant-mixin\n\n// scss-docs-start btn-size-mixin\n@mixin button-size($padding-y, $padding-x, $font-size, $border-radius) {\n  --#{$prefix}btn-padding-y: #{$padding-y};\n  --#{$prefix}btn-padding-x: #{$padding-x};\n  @include rfs($font-size, --#{$prefix}btn-font-size);\n  --#{$prefix}btn-border-radius: #{$border-radius};\n}\n// scss-docs-end btn-size-mixin\n",".fade {\n  @include transition($transition-fade);\n\n  &:not(.show) {\n    opacity: 0;\n  }\n}\n\n// scss-docs-start collapse-classes\n.collapse {\n  &:not(.show) {\n    display: none;\n  }\n}\n\n.collapsing {\n  height: 0;\n  overflow: hidden;\n  @include transition($transition-collapse);\n\n  &.collapse-horizontal {\n    width: 0;\n    height: auto;\n    @include transition($transition-collapse-width);\n  }\n}\n// scss-docs-end collapse-classes\n","// The dropdown wrapper (`<div>`)\n.dropup,\n.dropend,\n.dropdown,\n.dropstart,\n.dropup-center,\n.dropdown-center {\n  position: relative;\n}\n\n.dropdown-toggle {\n  white-space: nowrap;\n\n  // Generate the caret automatically\n  @include caret();\n}\n\n// The dropdown menu\n.dropdown-menu {\n  // scss-docs-start dropdown-css-vars\n  --#{$prefix}dropdown-zindex: #{$zindex-dropdown};\n  --#{$prefix}dropdown-min-width: #{$dropdown-min-width};\n  --#{$prefix}dropdown-padding-x: #{$dropdown-padding-x};\n  --#{$prefix}dropdown-padding-y: #{$dropdown-padding-y};\n  --#{$prefix}dropdown-spacer: #{$dropdown-spacer};\n  @include rfs($dropdown-font-size, --#{$prefix}dropdown-font-size);\n  --#{$prefix}dropdown-color: #{$dropdown-color};\n  --#{$prefix}dropdown-bg: #{$dropdown-bg};\n  --#{$prefix}dropdown-border-color: #{$dropdown-border-color};\n  --#{$prefix}dropdown-border-radius: #{$dropdown-border-radius};\n  --#{$prefix}dropdown-border-width: #{$dropdown-border-width};\n  --#{$prefix}dropdown-inner-border-radius: #{$dropdown-inner-border-radius};\n  --#{$prefix}dropdown-divider-bg: #{$dropdown-divider-bg};\n  --#{$prefix}dropdown-divider-margin-y: #{$dropdown-divider-margin-y};\n  --#{$prefix}dropdown-box-shadow: #{$dropdown-box-shadow};\n  --#{$prefix}dropdown-link-color: #{$dropdown-link-color};\n  --#{$prefix}dropdown-link-hover-color: #{$dropdown-link-hover-color};\n  --#{$prefix}dropdown-link-hover-bg: #{$dropdown-link-hover-bg};\n  --#{$prefix}dropdown-link-active-color: #{$dropdown-link-active-color};\n  --#{$prefix}dropdown-link-active-bg: #{$dropdown-link-active-bg};\n  --#{$prefix}dropdown-link-disabled-color: #{$dropdown-link-disabled-color};\n  --#{$prefix}dropdown-item-padding-x: #{$dropdown-item-padding-x};\n  --#{$prefix}dropdown-item-padding-y: #{$dropdown-item-padding-y};\n  --#{$prefix}dropdown-header-color: #{$dropdown-header-color};\n  --#{$prefix}dropdown-header-padding-x: #{$dropdown-header-padding-x};\n  --#{$prefix}dropdown-header-padding-y: #{$dropdown-header-padding-y};\n  // scss-docs-end dropdown-css-vars\n\n  position: absolute;\n  z-index: var(--#{$prefix}dropdown-zindex);\n  display: none; // none by default, but block on \"open\" of the menu\n  min-width: var(--#{$prefix}dropdown-min-width);\n  padding: var(--#{$prefix}dropdown-padding-y) var(--#{$prefix}dropdown-padding-x);\n  margin: 0; // Override default margin of ul\n  @include font-size(var(--#{$prefix}dropdown-font-size));\n  color: var(--#{$prefix}dropdown-color);\n  text-align: left; // Ensures proper alignment if parent has it changed (e.g., modal footer)\n  list-style: none;\n  background-color: var(--#{$prefix}dropdown-bg);\n  background-clip: padding-box;\n  border: var(--#{$prefix}dropdown-border-width) solid var(--#{$prefix}dropdown-border-color);\n  @include border-radius(var(--#{$prefix}dropdown-border-radius));\n  @include box-shadow(var(--#{$prefix}dropdown-box-shadow));\n\n  &[data-bs-popper] {\n    top: 100%;\n    left: 0;\n    margin-top: var(--#{$prefix}dropdown-spacer);\n  }\n\n  @if $dropdown-padding-y == 0 {\n    > .dropdown-item:first-child,\n    > li:first-child .dropdown-item {\n      @include border-top-radius(var(--#{$prefix}dropdown-inner-border-radius));\n    }\n    > .dropdown-item:last-child,\n    > li:last-child .dropdown-item {\n      @include border-bottom-radius(var(--#{$prefix}dropdown-inner-border-radius));\n    }\n\n  }\n}\n\n// scss-docs-start responsive-breakpoints\n// We deliberately hardcode the `bs-` prefix because we check\n// this custom property in JS to determine Popper's positioning\n\n@each $breakpoint in map-keys($grid-breakpoints) {\n  @include media-breakpoint-up($breakpoint) {\n    $infix: breakpoint-infix($breakpoint, $grid-breakpoints);\n\n    .dropdown-menu#{$infix}-start {\n      --bs-position: start;\n\n      &[data-bs-popper] {\n        right: auto;\n        left: 0;\n      }\n    }\n\n    .dropdown-menu#{$infix}-end {\n      --bs-position: end;\n\n      &[data-bs-popper] {\n        right: 0;\n        left: auto;\n      }\n    }\n  }\n}\n// scss-docs-end responsive-breakpoints\n\n// Allow for dropdowns to go bottom up (aka, dropup-menu)\n// Just add .dropup after the standard .dropdown class and you're set.\n.dropup {\n  .dropdown-menu[data-bs-popper] {\n    top: auto;\n    bottom: 100%;\n    margin-top: 0;\n    margin-bottom: var(--#{$prefix}dropdown-spacer);\n  }\n\n  .dropdown-toggle {\n    @include caret(up);\n  }\n}\n\n.dropend {\n  .dropdown-menu[data-bs-popper] {\n    top: 0;\n    right: auto;\n    left: 100%;\n    margin-top: 0;\n    margin-left: var(--#{$prefix}dropdown-spacer);\n  }\n\n  .dropdown-toggle {\n    @include caret(end);\n    &::after {\n      vertical-align: 0;\n    }\n  }\n}\n\n.dropstart {\n  .dropdown-menu[data-bs-popper] {\n    top: 0;\n    right: 100%;\n    left: auto;\n    margin-top: 0;\n    margin-right: var(--#{$prefix}dropdown-spacer);\n  }\n\n  .dropdown-toggle {\n    @include caret(start);\n    &::before {\n      vertical-align: 0;\n    }\n  }\n}\n\n\n// Dividers (basically an `<hr>`) within the dropdown\n.dropdown-divider {\n  height: 0;\n  margin: var(--#{$prefix}dropdown-divider-margin-y) 0;\n  overflow: hidden;\n  border-top: 1px solid var(--#{$prefix}dropdown-divider-bg);\n  opacity: 1; // Revisit in v6 to de-dupe styles that conflict with <hr> element\n}\n\n// Links, buttons, and more within the dropdown menu\n//\n// `<button>`-specific styles are denoted with `// For <button>s`\n.dropdown-item {\n  display: block;\n  width: 100%; // For `<button>`s\n  padding: var(--#{$prefix}dropdown-item-padding-y) var(--#{$prefix}dropdown-item-padding-x);\n  clear: both;\n  font-weight: $font-weight-normal;\n  color: var(--#{$prefix}dropdown-link-color);\n  text-align: inherit; // For `<button>`s\n  text-decoration: if($link-decoration == none, null, none);\n  white-space: nowrap; // prevent links from randomly breaking onto new lines\n  background-color: transparent; // For `<button>`s\n  border: 0; // For `<button>`s\n  @include border-radius(var(--#{$prefix}dropdown-item-border-radius, 0));\n\n  &:hover,\n  &:focus {\n    color: var(--#{$prefix}dropdown-link-hover-color);\n    text-decoration: if($link-hover-decoration == underline, none, null);\n    @include gradient-bg(var(--#{$prefix}dropdown-link-hover-bg));\n  }\n\n  &.active,\n  &:active {\n    color: var(--#{$prefix}dropdown-link-active-color);\n    text-decoration: none;\n    @include gradient-bg(var(--#{$prefix}dropdown-link-active-bg));\n  }\n\n  &.disabled,\n  &:disabled {\n    color: var(--#{$prefix}dropdown-link-disabled-color);\n    pointer-events: none;\n    background-color: transparent;\n    // Remove CSS gradients if they're enabled\n    background-image: if($enable-gradients, none, null);\n  }\n}\n\n.dropdown-menu.show {\n  display: block;\n}\n\n// Dropdown section headers\n.dropdown-header {\n  display: block;\n  padding: var(--#{$prefix}dropdown-header-padding-y) var(--#{$prefix}dropdown-header-padding-x);\n  margin-bottom: 0; // for use with heading elements\n  @include font-size($font-size-sm);\n  color: var(--#{$prefix}dropdown-header-color);\n  white-space: nowrap; // as with > li > a\n}\n\n// Dropdown text\n.dropdown-item-text {\n  display: block;\n  padding: var(--#{$prefix}dropdown-item-padding-y) var(--#{$prefix}dropdown-item-padding-x);\n  color: var(--#{$prefix}dropdown-link-color);\n}\n\n// Dark dropdowns\n.dropdown-menu-dark {\n  // scss-docs-start dropdown-dark-css-vars\n  --#{$prefix}dropdown-color: #{$dropdown-dark-color};\n  --#{$prefix}dropdown-bg: #{$dropdown-dark-bg};\n  --#{$prefix}dropdown-border-color: #{$dropdown-dark-border-color};\n  --#{$prefix}dropdown-box-shadow: #{$dropdown-dark-box-shadow};\n  --#{$prefix}dropdown-link-color: #{$dropdown-dark-link-color};\n  --#{$prefix}dropdown-link-hover-color: #{$dropdown-dark-link-hover-color};\n  --#{$prefix}dropdown-divider-bg: #{$dropdown-dark-divider-bg};\n  --#{$prefix}dropdown-link-hover-bg: #{$dropdown-dark-link-hover-bg};\n  --#{$prefix}dropdown-link-active-color: #{$dropdown-dark-link-active-color};\n  --#{$prefix}dropdown-link-active-bg: #{$dropdown-dark-link-active-bg};\n  --#{$prefix}dropdown-link-disabled-color: #{$dropdown-dark-link-disabled-color};\n  --#{$prefix}dropdown-header-color: #{$dropdown-dark-header-color};\n  // scss-docs-end dropdown-dark-css-vars\n}\n","// scss-docs-start caret-mixins\n@mixin caret-down($width: $caret-width) {\n  border-top: $width solid;\n  border-right: $width solid transparent;\n  border-bottom: 0;\n  border-left: $width solid transparent;\n}\n\n@mixin caret-up($width: $caret-width) {\n  border-top: 0;\n  border-right: $width solid transparent;\n  border-bottom: $width solid;\n  border-left: $width solid transparent;\n}\n\n@mixin caret-end($width: $caret-width) {\n  border-top: $width solid transparent;\n  border-right: 0;\n  border-bottom: $width solid transparent;\n  border-left: $width solid;\n}\n\n@mixin caret-start($width: $caret-width) {\n  border-top: $width solid transparent;\n  border-right: $width solid;\n  border-bottom: $width solid transparent;\n}\n\n@mixin caret(\n  $direction: down,\n  $width: $caret-width,\n  $spacing: $caret-spacing,\n  $vertical-align: $caret-vertical-align\n) {\n  @if $enable-caret {\n    &::after {\n      display: inline-block;\n      margin-left: $spacing;\n      vertical-align: $vertical-align;\n      content: \"\";\n      @if $direction == down {\n        @include caret-down($width);\n      } @else if $direction == up {\n        @include caret-up($width);\n      } @else if $direction == end {\n        @include caret-end($width);\n      }\n    }\n\n    @if $direction == start {\n      &::after {\n        display: none;\n      }\n\n      &::before {\n        display: inline-block;\n        margin-right: $spacing;\n        vertical-align: $vertical-align;\n        content: \"\";\n        @include caret-start($width);\n      }\n    }\n\n    &:empty::after {\n      margin-left: 0;\n    }\n  }\n}\n// scss-docs-end caret-mixins\n","// Make the div behave like a button\n.btn-group,\n.btn-group-vertical {\n  position: relative;\n  display: inline-flex;\n  vertical-align: middle; // match .btn alignment given font-size hack above\n\n  > .btn {\n    position: relative;\n    flex: 1 1 auto;\n  }\n\n  // Bring the hover, focused, and \"active\" buttons to the front to overlay\n  // the borders properly\n  > .btn-check:checked + .btn,\n  > .btn-check:focus + .btn,\n  > .btn:hover,\n  > .btn:focus,\n  > .btn:active,\n  > .btn.active {\n    z-index: 1;\n  }\n}\n\n// Optional: Group multiple button groups together for a toolbar\n.btn-toolbar {\n  display: flex;\n  flex-wrap: wrap;\n  justify-content: flex-start;\n\n  .input-group {\n    width: auto;\n  }\n}\n\n.btn-group {\n  @include border-radius($btn-border-radius);\n\n  // Prevent double borders when buttons are next to each other\n  > :not(.btn-check:first-child) + .btn,\n  > .btn-group:not(:first-child) {\n    margin-left: calc(#{$btn-border-width} * -1); // stylelint-disable-line function-disallowed-list\n  }\n\n  // Reset rounded corners\n  > .btn:not(:last-child):not(.dropdown-toggle),\n  > .btn.dropdown-toggle-split:first-child,\n  > .btn-group:not(:last-child) > .btn {\n    @include border-end-radius(0);\n  }\n\n  // The left radius should be 0 if the button is:\n  // - the \"third or more\" child\n  // - the second child and the previous element isn't `.btn-check` (making it the first child visually)\n  // - part of a btn-group which isn't the first child\n  > .btn:nth-child(n + 3),\n  > :not(.btn-check) + .btn,\n  > .btn-group:not(:first-child) > .btn {\n    @include border-start-radius(0);\n  }\n}\n\n// Sizing\n//\n// Remix the default button sizing classes into new ones for easier manipulation.\n\n.btn-group-sm > .btn { @extend .btn-sm; }\n.btn-group-lg > .btn { @extend .btn-lg; }\n\n\n//\n// Split button dropdowns\n//\n\n.dropdown-toggle-split {\n  padding-right: $btn-padding-x * .75;\n  padding-left: $btn-padding-x * .75;\n\n  &::after,\n  .dropup &::after,\n  .dropend &::after {\n    margin-left: 0;\n  }\n\n  .dropstart &::before {\n    margin-right: 0;\n  }\n}\n\n.btn-sm + .dropdown-toggle-split {\n  padding-right: $btn-padding-x-sm * .75;\n  padding-left: $btn-padding-x-sm * .75;\n}\n\n.btn-lg + .dropdown-toggle-split {\n  padding-right: $btn-padding-x-lg * .75;\n  padding-left: $btn-padding-x-lg * .75;\n}\n\n\n// The clickable button for toggling the menu\n// Set the same inset shadow as the :active state\n.btn-group.show .dropdown-toggle {\n  @include box-shadow($btn-active-box-shadow);\n\n  // Show no shadow for `.btn-link` since it has no other button styles.\n  &.btn-link {\n    @include box-shadow(none);\n  }\n}\n\n\n//\n// Vertical button groups\n//\n\n.btn-group-vertical {\n  flex-direction: column;\n  align-items: flex-start;\n  justify-content: center;\n\n  > .btn,\n  > .btn-group {\n    width: 100%;\n  }\n\n  > .btn:not(:first-child),\n  > .btn-group:not(:first-child) {\n    margin-top: calc(#{$btn-border-width} * -1); // stylelint-disable-line function-disallowed-list\n  }\n\n  // Reset rounded corners\n  > .btn:not(:last-child):not(.dropdown-toggle),\n  > .btn-group:not(:last-child) > .btn {\n    @include border-bottom-radius(0);\n  }\n\n  > .btn ~ .btn,\n  > .btn-group:not(:first-child) > .btn {\n    @include border-top-radius(0);\n  }\n}\n","// Base class\n//\n// Kickstart any navigation component with a set of style resets. Works with\n// `<nav>`s, `<ul>`s or `<ol>`s.\n\n.nav {\n  // scss-docs-start nav-css-vars\n  --#{$prefix}nav-link-padding-x: #{$nav-link-padding-x};\n  --#{$prefix}nav-link-padding-y: #{$nav-link-padding-y};\n  @include rfs($nav-link-font-size, --#{$prefix}nav-link-font-size);\n  --#{$prefix}nav-link-font-weight: #{$nav-link-font-weight};\n  --#{$prefix}nav-link-color: #{$nav-link-color};\n  --#{$prefix}nav-link-hover-color: #{$nav-link-hover-color};\n  --#{$prefix}nav-link-disabled-color: #{$nav-link-disabled-color};\n  // scss-docs-end nav-css-vars\n\n  display: flex;\n  flex-wrap: wrap;\n  padding-left: 0;\n  margin-bottom: 0;\n  list-style: none;\n}\n\n.nav-link {\n  display: block;\n  padding: var(--#{$prefix}nav-link-padding-y) var(--#{$prefix}nav-link-padding-x);\n  @include font-size(var(--#{$prefix}nav-link-font-size));\n  font-weight: var(--#{$prefix}nav-link-font-weight);\n  color: var(--#{$prefix}nav-link-color);\n  text-decoration: if($link-decoration == none, null, none);\n  background: none;\n  border: 0;\n  @include transition($nav-link-transition);\n\n  &:hover,\n  &:focus {\n    color: var(--#{$prefix}nav-link-hover-color);\n    text-decoration: if($link-hover-decoration == underline, none, null);\n  }\n\n  &:focus-visible {\n    outline: 0;\n    box-shadow: $nav-link-focus-box-shadow;\n  }\n\n  // Disabled state lightens text\n  &.disabled,\n  &:disabled {\n    color: var(--#{$prefix}nav-link-disabled-color);\n    pointer-events: none;\n    cursor: default;\n  }\n}\n\n//\n// Tabs\n//\n\n.nav-tabs {\n  // scss-docs-start nav-tabs-css-vars\n  --#{$prefix}nav-tabs-border-width: #{$nav-tabs-border-width};\n  --#{$prefix}nav-tabs-border-color: #{$nav-tabs-border-color};\n  --#{$prefix}nav-tabs-border-radius: #{$nav-tabs-border-radius};\n  --#{$prefix}nav-tabs-link-hover-border-color: #{$nav-tabs-link-hover-border-color};\n  --#{$prefix}nav-tabs-link-active-color: #{$nav-tabs-link-active-color};\n  --#{$prefix}nav-tabs-link-active-bg: #{$nav-tabs-link-active-bg};\n  --#{$prefix}nav-tabs-link-active-border-color: #{$nav-tabs-link-active-border-color};\n  // scss-docs-end nav-tabs-css-vars\n\n  border-bottom: var(--#{$prefix}nav-tabs-border-width) solid var(--#{$prefix}nav-tabs-border-color);\n\n  .nav-link {\n    margin-bottom: calc(-1 * var(--#{$prefix}nav-tabs-border-width)); // stylelint-disable-line function-disallowed-list\n    border: var(--#{$prefix}nav-tabs-border-width) solid transparent;\n    @include border-top-radius(var(--#{$prefix}nav-tabs-border-radius));\n\n    &:hover,\n    &:focus {\n      // Prevents active .nav-link tab overlapping focus outline of previous/next .nav-link\n      isolation: isolate;\n      border-color: var(--#{$prefix}nav-tabs-link-hover-border-color);\n    }\n  }\n\n  .nav-link.active,\n  .nav-item.show .nav-link {\n    color: var(--#{$prefix}nav-tabs-link-active-color);\n    background-color: var(--#{$prefix}nav-tabs-link-active-bg);\n    border-color: var(--#{$prefix}nav-tabs-link-active-border-color);\n  }\n\n  .dropdown-menu {\n    // Make dropdown border overlap tab border\n    margin-top: calc(-1 * var(--#{$prefix}nav-tabs-border-width)); // stylelint-disable-line function-disallowed-list\n    // Remove the top rounded corners here since there is a hard edge above the menu\n    @include border-top-radius(0);\n  }\n}\n\n\n//\n// Pills\n//\n\n.nav-pills {\n  // scss-docs-start nav-pills-css-vars\n  --#{$prefix}nav-pills-border-radius: #{$nav-pills-border-radius};\n  --#{$prefix}nav-pills-link-active-color: #{$nav-pills-link-active-color};\n  --#{$prefix}nav-pills-link-active-bg: #{$nav-pills-link-active-bg};\n  // scss-docs-end nav-pills-css-vars\n\n  .nav-link {\n    @include border-radius(var(--#{$prefix}nav-pills-border-radius));\n  }\n\n  .nav-link.active,\n  .show > .nav-link {\n    color: var(--#{$prefix}nav-pills-link-active-color);\n    @include gradient-bg(var(--#{$prefix}nav-pills-link-active-bg));\n  }\n}\n\n\n//\n// Underline\n//\n\n.nav-underline {\n  // scss-docs-start nav-underline-css-vars\n  --#{$prefix}nav-underline-gap: #{$nav-underline-gap};\n  --#{$prefix}nav-underline-border-width: #{$nav-underline-border-width};\n  --#{$prefix}nav-underline-link-active-color: #{$nav-underline-link-active-color};\n  // scss-docs-end nav-underline-css-vars\n\n  gap: var(--#{$prefix}nav-underline-gap);\n\n  .nav-link {\n    padding-right: 0;\n    padding-left: 0;\n    border-bottom: var(--#{$prefix}nav-underline-border-width) solid transparent;\n\n    &:hover,\n    &:focus {\n      border-bottom-color: currentcolor;\n    }\n  }\n\n  .nav-link.active,\n  .show > .nav-link {\n    font-weight: $font-weight-bold;\n    color: var(--#{$prefix}nav-underline-link-active-color);\n    border-bottom-color: currentcolor;\n  }\n}\n\n\n//\n// Justified variants\n//\n\n.nav-fill {\n  > .nav-link,\n  .nav-item {\n    flex: 1 1 auto;\n    text-align: center;\n  }\n}\n\n.nav-justified {\n  > .nav-link,\n  .nav-item {\n    flex-basis: 0;\n    flex-grow: 1;\n    text-align: center;\n  }\n}\n\n.nav-fill,\n.nav-justified {\n  .nav-item .nav-link {\n    width: 100%; // Make sure button will grow\n  }\n}\n\n\n// Tabbable tabs\n//\n// Hide tabbable panes to start, show them when `.active`\n\n.tab-content {\n  > .tab-pane {\n    display: none;\n  }\n  > .active {\n    display: block;\n  }\n}\n","// Navbar\n//\n// Provide a static navbar from which we expand to create full-width, fixed, and\n// other navbar variations.\n\n.navbar {\n  // scss-docs-start navbar-css-vars\n  --#{$prefix}navbar-padding-x: #{if($navbar-padding-x == null, 0, $navbar-padding-x)};\n  --#{$prefix}navbar-padding-y: #{$navbar-padding-y};\n  --#{$prefix}navbar-color: #{$navbar-light-color};\n  --#{$prefix}navbar-hover-color: #{$navbar-light-hover-color};\n  --#{$prefix}navbar-disabled-color: #{$navbar-light-disabled-color};\n  --#{$prefix}navbar-active-color: #{$navbar-light-active-color};\n  --#{$prefix}navbar-brand-padding-y: #{$navbar-brand-padding-y};\n  --#{$prefix}navbar-brand-margin-end: #{$navbar-brand-margin-end};\n  --#{$prefix}navbar-brand-font-size: #{$navbar-brand-font-size};\n  --#{$prefix}navbar-brand-color: #{$navbar-light-brand-color};\n  --#{$prefix}navbar-brand-hover-color: #{$navbar-light-brand-hover-color};\n  --#{$prefix}navbar-nav-link-padding-x: #{$navbar-nav-link-padding-x};\n  --#{$prefix}navbar-toggler-padding-y: #{$navbar-toggler-padding-y};\n  --#{$prefix}navbar-toggler-padding-x: #{$navbar-toggler-padding-x};\n  --#{$prefix}navbar-toggler-font-size: #{$navbar-toggler-font-size};\n  --#{$prefix}navbar-toggler-icon-bg: #{escape-svg($navbar-light-toggler-icon-bg)};\n  --#{$prefix}navbar-toggler-border-color: #{$navbar-light-toggler-border-color};\n  --#{$prefix}navbar-toggler-border-radius: #{$navbar-toggler-border-radius};\n  --#{$prefix}navbar-toggler-focus-width: #{$navbar-toggler-focus-width};\n  --#{$prefix}navbar-toggler-transition: #{$navbar-toggler-transition};\n  // scss-docs-end navbar-css-vars\n\n  position: relative;\n  display: flex;\n  flex-wrap: wrap; // allow us to do the line break for collapsing content\n  align-items: center;\n  justify-content: space-between; // space out brand from logo\n  padding: var(--#{$prefix}navbar-padding-y) var(--#{$prefix}navbar-padding-x);\n  @include gradient-bg();\n\n  // Because flex properties aren't inherited, we need to redeclare these first\n  // few properties so that content nested within behave properly.\n  // The `flex-wrap` property is inherited to simplify the expanded navbars\n  %container-flex-properties {\n    display: flex;\n    flex-wrap: inherit;\n    align-items: center;\n    justify-content: space-between;\n  }\n\n  > .container,\n  > .container-fluid {\n    @extend %container-flex-properties;\n  }\n\n  @each $breakpoint, $container-max-width in $container-max-widths {\n    > .container#{breakpoint-infix($breakpoint, $container-max-widths)} {\n      @extend %container-flex-properties;\n    }\n  }\n}\n\n\n// Navbar brand\n//\n// Used for brand, project, or site names.\n\n.navbar-brand {\n  padding-top: var(--#{$prefix}navbar-brand-padding-y);\n  padding-bottom: var(--#{$prefix}navbar-brand-padding-y);\n  margin-right: var(--#{$prefix}navbar-brand-margin-end);\n  @include font-size(var(--#{$prefix}navbar-brand-font-size));\n  color: var(--#{$prefix}navbar-brand-color);\n  text-decoration: if($link-decoration == none, null, none);\n  white-space: nowrap;\n\n  &:hover,\n  &:focus {\n    color: var(--#{$prefix}navbar-brand-hover-color);\n    text-decoration: if($link-hover-decoration == underline, none, null);\n  }\n}\n\n\n// Navbar nav\n//\n// Custom navbar navigation (doesn't require `.nav`, but does make use of `.nav-link`).\n\n.navbar-nav {\n  // scss-docs-start navbar-nav-css-vars\n  --#{$prefix}nav-link-padding-x: 0;\n  --#{$prefix}nav-link-padding-y: #{$nav-link-padding-y};\n  @include rfs($nav-link-font-size, --#{$prefix}nav-link-font-size);\n  --#{$prefix}nav-link-font-weight: #{$nav-link-font-weight};\n  --#{$prefix}nav-link-color: var(--#{$prefix}navbar-color);\n  --#{$prefix}nav-link-hover-color: var(--#{$prefix}navbar-hover-color);\n  --#{$prefix}nav-link-disabled-color: var(--#{$prefix}navbar-disabled-color);\n  // scss-docs-end navbar-nav-css-vars\n\n  display: flex;\n  flex-direction: column; // cannot use `inherit` to get the `.navbar`s value\n  padding-left: 0;\n  margin-bottom: 0;\n  list-style: none;\n\n  .nav-link {\n    &.active,\n    &.show {\n      color: var(--#{$prefix}navbar-active-color);\n    }\n  }\n\n  .dropdown-menu {\n    position: static;\n  }\n}\n\n\n// Navbar text\n//\n//\n\n.navbar-text {\n  padding-top: $nav-link-padding-y;\n  padding-bottom: $nav-link-padding-y;\n  color: var(--#{$prefix}navbar-color);\n\n  a,\n  a:hover,\n  a:focus  {\n    color: var(--#{$prefix}navbar-active-color);\n  }\n}\n\n\n// Responsive navbar\n//\n// Custom styles for responsive collapsing and toggling of navbar contents.\n// Powered by the collapse Bootstrap JavaScript plugin.\n\n// When collapsed, prevent the toggleable navbar contents from appearing in\n// the default flexbox row orientation. Requires the use of `flex-wrap: wrap`\n// on the `.navbar` parent.\n.navbar-collapse {\n  flex-basis: 100%;\n  flex-grow: 1;\n  // For always expanded or extra full navbars, ensure content aligns itself\n  // properly vertically. Can be easily overridden with flex utilities.\n  align-items: center;\n}\n\n// Button for toggling the navbar when in its collapsed state\n.navbar-toggler {\n  padding: var(--#{$prefix}navbar-toggler-padding-y) var(--#{$prefix}navbar-toggler-padding-x);\n  @include font-size(var(--#{$prefix}navbar-toggler-font-size));\n  line-height: 1;\n  color: var(--#{$prefix}navbar-color);\n  background-color: transparent; // remove default button style\n  border: var(--#{$prefix}border-width) solid var(--#{$prefix}navbar-toggler-border-color); // remove default button style\n  @include border-radius(var(--#{$prefix}navbar-toggler-border-radius));\n  @include transition(var(--#{$prefix}navbar-toggler-transition));\n\n  &:hover {\n    text-decoration: none;\n  }\n\n  &:focus {\n    text-decoration: none;\n    outline: 0;\n    box-shadow: 0 0 0 var(--#{$prefix}navbar-toggler-focus-width);\n  }\n}\n\n// Keep as a separate element so folks can easily override it with another icon\n// or image file as needed.\n.navbar-toggler-icon {\n  display: inline-block;\n  width: 1.5em;\n  height: 1.5em;\n  vertical-align: middle;\n  background-image: var(--#{$prefix}navbar-toggler-icon-bg);\n  background-repeat: no-repeat;\n  background-position: center;\n  background-size: 100%;\n}\n\n.navbar-nav-scroll {\n  max-height: var(--#{$prefix}scroll-height, 75vh);\n  overflow-y: auto;\n}\n\n// scss-docs-start navbar-expand-loop\n// Generate series of `.navbar-expand-*` responsive classes for configuring\n// where your navbar collapses.\n.navbar-expand {\n  @each $breakpoint in map-keys($grid-breakpoints) {\n    $next: breakpoint-next($breakpoint, $grid-breakpoints);\n    $infix: breakpoint-infix($next, $grid-breakpoints);\n\n    // stylelint-disable-next-line scss/selector-no-union-class-name\n    &#{$infix} {\n      @include media-breakpoint-up($next) {\n        flex-wrap: nowrap;\n        justify-content: flex-start;\n\n        .navbar-nav {\n          flex-direction: row;\n\n          .dropdown-menu {\n            position: absolute;\n          }\n\n          .nav-link {\n            padding-right: var(--#{$prefix}navbar-nav-link-padding-x);\n            padding-left: var(--#{$prefix}navbar-nav-link-padding-x);\n          }\n        }\n\n        .navbar-nav-scroll {\n          overflow: visible;\n        }\n\n        .navbar-collapse {\n          display: flex !important; // stylelint-disable-line declaration-no-important\n          flex-basis: auto;\n        }\n\n        .navbar-toggler {\n          display: none;\n        }\n\n        .offcanvas {\n          // stylelint-disable declaration-no-important\n          position: static;\n          z-index: auto;\n          flex-grow: 1;\n          width: auto !important;\n          height: auto !important;\n          visibility: visible !important;\n          background-color: transparent !important;\n          border: 0 !important;\n          transform: none !important;\n          @include box-shadow(none);\n          @include transition(none);\n          // stylelint-enable declaration-no-important\n\n          .offcanvas-header {\n            display: none;\n          }\n\n          .offcanvas-body {\n            display: flex;\n            flex-grow: 0;\n            padding: 0;\n            overflow-y: visible;\n          }\n        }\n      }\n    }\n  }\n}\n// scss-docs-end navbar-expand-loop\n\n// Navbar themes\n//\n// Styles for switching between navbars with light or dark background.\n\n.navbar-light {\n  @include deprecate(\"`.navbar-light`\", \"v5.2.0\", \"v6.0.0\", true);\n}\n\n.navbar-dark,\n.navbar[data-bs-theme=\"dark\"] {\n  // scss-docs-start navbar-dark-css-vars\n  --#{$prefix}navbar-color: #{$navbar-dark-color};\n  --#{$prefix}navbar-hover-color: #{$navbar-dark-hover-color};\n  --#{$prefix}navbar-disabled-color: #{$navbar-dark-disabled-color};\n  --#{$prefix}navbar-active-color: #{$navbar-dark-active-color};\n  --#{$prefix}navbar-brand-color: #{$navbar-dark-brand-color};\n  --#{$prefix}navbar-brand-hover-color: #{$navbar-dark-brand-hover-color};\n  --#{$prefix}navbar-toggler-border-color: #{$navbar-dark-toggler-border-color};\n  --#{$prefix}navbar-toggler-icon-bg: #{escape-svg($navbar-dark-toggler-icon-bg)};\n  // scss-docs-end navbar-dark-css-vars\n}\n\n@if $enable-dark-mode {\n  @include color-mode(dark) {\n    .navbar-toggler-icon {\n      --#{$prefix}navbar-toggler-icon-bg: #{escape-svg($navbar-dark-toggler-icon-bg)};\n    }\n  }\n}\n","//\n// Base styles\n//\n\n.card {\n  // scss-docs-start card-css-vars\n  --#{$prefix}card-spacer-y: #{$card-spacer-y};\n  --#{$prefix}card-spacer-x: #{$card-spacer-x};\n  --#{$prefix}card-title-spacer-y: #{$card-title-spacer-y};\n  --#{$prefix}card-title-color: #{$card-title-color};\n  --#{$prefix}card-subtitle-color: #{$card-subtitle-color};\n  --#{$prefix}card-border-width: #{$card-border-width};\n  --#{$prefix}card-border-color: #{$card-border-color};\n  --#{$prefix}card-border-radius: #{$card-border-radius};\n  --#{$prefix}card-box-shadow: #{$card-box-shadow};\n  --#{$prefix}card-inner-border-radius: #{$card-inner-border-radius};\n  --#{$prefix}card-cap-padding-y: #{$card-cap-padding-y};\n  --#{$prefix}card-cap-padding-x: #{$card-cap-padding-x};\n  --#{$prefix}card-cap-bg: #{$card-cap-bg};\n  --#{$prefix}card-cap-color: #{$card-cap-color};\n  --#{$prefix}card-height: #{$card-height};\n  --#{$prefix}card-color: #{$card-color};\n  --#{$prefix}card-bg: #{$card-bg};\n  --#{$prefix}card-img-overlay-padding: #{$card-img-overlay-padding};\n  --#{$prefix}card-group-margin: #{$card-group-margin};\n  // scss-docs-end card-css-vars\n\n  position: relative;\n  display: flex;\n  flex-direction: column;\n  min-width: 0; // See https://github.com/twbs/bootstrap/pull/22740#issuecomment-305868106\n  height: var(--#{$prefix}card-height);\n  color: var(--#{$prefix}body-color);\n  word-wrap: break-word;\n  background-color: var(--#{$prefix}card-bg);\n  background-clip: border-box;\n  border: var(--#{$prefix}card-border-width) solid var(--#{$prefix}card-border-color);\n  @include border-radius(var(--#{$prefix}card-border-radius));\n  @include box-shadow(var(--#{$prefix}card-box-shadow));\n\n  > hr {\n    margin-right: 0;\n    margin-left: 0;\n  }\n\n  > .list-group {\n    border-top: inherit;\n    border-bottom: inherit;\n\n    &:first-child {\n      border-top-width: 0;\n      @include border-top-radius(var(--#{$prefix}card-inner-border-radius));\n    }\n\n    &:last-child  {\n      border-bottom-width: 0;\n      @include border-bottom-radius(var(--#{$prefix}card-inner-border-radius));\n    }\n  }\n\n  // Due to specificity of the above selector (`.card > .list-group`), we must\n  // use a child selector here to prevent double borders.\n  > .card-header + .list-group,\n  > .list-group + .card-footer {\n    border-top: 0;\n  }\n}\n\n.card-body {\n  // Enable `flex-grow: 1` for decks and groups so that card blocks take up\n  // as much space as possible, ensuring footers are aligned to the bottom.\n  flex: 1 1 auto;\n  padding: var(--#{$prefix}card-spacer-y) var(--#{$prefix}card-spacer-x);\n  color: var(--#{$prefix}card-color);\n}\n\n.card-title {\n  margin-bottom: var(--#{$prefix}card-title-spacer-y);\n  color: var(--#{$prefix}card-title-color);\n}\n\n.card-subtitle {\n  margin-top: calc(-.5 * var(--#{$prefix}card-title-spacer-y)); // stylelint-disable-line function-disallowed-list\n  margin-bottom: 0;\n  color: var(--#{$prefix}card-subtitle-color);\n}\n\n.card-text:last-child {\n  margin-bottom: 0;\n}\n\n.card-link {\n  &:hover {\n    text-decoration: if($link-hover-decoration == underline, none, null);\n  }\n\n  + .card-link {\n    margin-left: var(--#{$prefix}card-spacer-x);\n  }\n}\n\n//\n// Optional textual caps\n//\n\n.card-header {\n  padding: var(--#{$prefix}card-cap-padding-y) var(--#{$prefix}card-cap-padding-x);\n  margin-bottom: 0; // Removes the default margin-bottom of <hN>\n  color: var(--#{$prefix}card-cap-color);\n  background-color: var(--#{$prefix}card-cap-bg);\n  border-bottom: var(--#{$prefix}card-border-width) solid var(--#{$prefix}card-border-color);\n\n  &:first-child {\n    @include border-radius(var(--#{$prefix}card-inner-border-radius) var(--#{$prefix}card-inner-border-radius) 0 0);\n  }\n}\n\n.card-footer {\n  padding: var(--#{$prefix}card-cap-padding-y) var(--#{$prefix}card-cap-padding-x);\n  color: var(--#{$prefix}card-cap-color);\n  background-color: var(--#{$prefix}card-cap-bg);\n  border-top: var(--#{$prefix}card-border-width) solid var(--#{$prefix}card-border-color);\n\n  &:last-child {\n    @include border-radius(0 0 var(--#{$prefix}card-inner-border-radius) var(--#{$prefix}card-inner-border-radius));\n  }\n}\n\n\n//\n// Header navs\n//\n\n.card-header-tabs {\n  margin-right: calc(-.5 * var(--#{$prefix}card-cap-padding-x)); // stylelint-disable-line function-disallowed-list\n  margin-bottom: calc(-1 * var(--#{$prefix}card-cap-padding-y)); // stylelint-disable-line function-disallowed-list\n  margin-left: calc(-.5 * var(--#{$prefix}card-cap-padding-x)); // stylelint-disable-line function-disallowed-list\n  border-bottom: 0;\n\n  .nav-link.active {\n    background-color: var(--#{$prefix}card-bg);\n    border-bottom-color: var(--#{$prefix}card-bg);\n  }\n}\n\n.card-header-pills {\n  margin-right: calc(-.5 * var(--#{$prefix}card-cap-padding-x)); // stylelint-disable-line function-disallowed-list\n  margin-left: calc(-.5 * var(--#{$prefix}card-cap-padding-x)); // stylelint-disable-line function-disallowed-list\n}\n\n// Card image\n.card-img-overlay {\n  position: absolute;\n  top: 0;\n  right: 0;\n  bottom: 0;\n  left: 0;\n  padding: var(--#{$prefix}card-img-overlay-padding);\n  @include border-radius(var(--#{$prefix}card-inner-border-radius));\n}\n\n.card-img,\n.card-img-top,\n.card-img-bottom {\n  width: 100%; // Required because we use flexbox and this inherently applies align-self: stretch\n}\n\n.card-img,\n.card-img-top {\n  @include border-top-radius(var(--#{$prefix}card-inner-border-radius));\n}\n\n.card-img,\n.card-img-bottom {\n  @include border-bottom-radius(var(--#{$prefix}card-inner-border-radius));\n}\n\n\n//\n// Card groups\n//\n\n.card-group {\n  // The child selector allows nested `.card` within `.card-group`\n  // to display properly.\n  > .card {\n    margin-bottom: var(--#{$prefix}card-group-margin);\n  }\n\n  @include media-breakpoint-up(sm) {\n    display: flex;\n    flex-flow: row wrap;\n    // The child selector allows nested `.card` within `.card-group`\n    // to display properly.\n    > .card {\n      // Flexbugs #4: https://github.com/philipwalton/flexbugs#flexbug-4\n      flex: 1 0 0%;\n      margin-bottom: 0;\n\n      + .card {\n        margin-left: 0;\n        border-left: 0;\n      }\n\n      // Handle rounded corners\n      @if $enable-rounded {\n        &:not(:last-child) {\n          @include border-end-radius(0);\n\n          .card-img-top,\n          .card-header {\n            // stylelint-disable-next-line property-disallowed-list\n            border-top-right-radius: 0;\n          }\n          .card-img-bottom,\n          .card-footer {\n            // stylelint-disable-next-line property-disallowed-list\n            border-bottom-right-radius: 0;\n          }\n        }\n\n        &:not(:first-child) {\n          @include border-start-radius(0);\n\n          .card-img-top,\n          .card-header {\n            // stylelint-disable-next-line property-disallowed-list\n            border-top-left-radius: 0;\n          }\n          .card-img-bottom,\n          .card-footer {\n            // stylelint-disable-next-line property-disallowed-list\n            border-bottom-left-radius: 0;\n          }\n        }\n      }\n    }\n  }\n}\n","//\n// Base styles\n//\n\n.accordion {\n  // scss-docs-start accordion-css-vars\n  --#{$prefix}accordion-color: #{$accordion-color};\n  --#{$prefix}accordion-bg: #{$accordion-bg};\n  --#{$prefix}accordion-transition: #{$accordion-transition};\n  --#{$prefix}accordion-border-color: #{$accordion-border-color};\n  --#{$prefix}accordion-border-width: #{$accordion-border-width};\n  --#{$prefix}accordion-border-radius: #{$accordion-border-radius};\n  --#{$prefix}accordion-inner-border-radius: #{$accordion-inner-border-radius};\n  --#{$prefix}accordion-btn-padding-x: #{$accordion-button-padding-x};\n  --#{$prefix}accordion-btn-padding-y: #{$accordion-button-padding-y};\n  --#{$prefix}accordion-btn-color: #{$accordion-button-color};\n  --#{$prefix}accordion-btn-bg: #{$accordion-button-bg};\n  --#{$prefix}accordion-btn-icon: #{escape-svg($accordion-button-icon)};\n  --#{$prefix}accordion-btn-icon-width: #{$accordion-icon-width};\n  --#{$prefix}accordion-btn-icon-transform: #{$accordion-icon-transform};\n  --#{$prefix}accordion-btn-icon-transition: #{$accordion-icon-transition};\n  --#{$prefix}accordion-btn-active-icon: #{escape-svg($accordion-button-active-icon)};\n  --#{$prefix}accordion-btn-focus-border-color: #{$accordion-button-focus-border-color};\n  --#{$prefix}accordion-btn-focus-box-shadow: #{$accordion-button-focus-box-shadow};\n  --#{$prefix}accordion-body-padding-x: #{$accordion-body-padding-x};\n  --#{$prefix}accordion-body-padding-y: #{$accordion-body-padding-y};\n  --#{$prefix}accordion-active-color: #{$accordion-button-active-color};\n  --#{$prefix}accordion-active-bg: #{$accordion-button-active-bg};\n  // scss-docs-end accordion-css-vars\n}\n\n.accordion-button {\n  position: relative;\n  display: flex;\n  align-items: center;\n  width: 100%;\n  padding: var(--#{$prefix}accordion-btn-padding-y) var(--#{$prefix}accordion-btn-padding-x);\n  @include font-size($font-size-base);\n  color: var(--#{$prefix}accordion-btn-color);\n  text-align: left; // Reset button style\n  background-color: var(--#{$prefix}accordion-btn-bg);\n  border: 0;\n  @include border-radius(0);\n  overflow-anchor: none;\n  @include transition(var(--#{$prefix}accordion-transition));\n\n  &:not(.collapsed) {\n    color: var(--#{$prefix}accordion-active-color);\n    background-color: var(--#{$prefix}accordion-active-bg);\n    box-shadow: inset 0 calc(-1 * var(--#{$prefix}accordion-border-width)) 0 var(--#{$prefix}accordion-border-color); // stylelint-disable-line function-disallowed-list\n\n    &::after {\n      background-image: var(--#{$prefix}accordion-btn-active-icon);\n      transform: var(--#{$prefix}accordion-btn-icon-transform);\n    }\n  }\n\n  // Accordion icon\n  &::after {\n    flex-shrink: 0;\n    width: var(--#{$prefix}accordion-btn-icon-width);\n    height: var(--#{$prefix}accordion-btn-icon-width);\n    margin-left: auto;\n    content: \"\";\n    background-image: var(--#{$prefix}accordion-btn-icon);\n    background-repeat: no-repeat;\n    background-size: var(--#{$prefix}accordion-btn-icon-width);\n    @include transition(var(--#{$prefix}accordion-btn-icon-transition));\n  }\n\n  &:hover {\n    z-index: 2;\n  }\n\n  &:focus {\n    z-index: 3;\n    border-color: var(--#{$prefix}accordion-btn-focus-border-color);\n    outline: 0;\n    box-shadow: var(--#{$prefix}accordion-btn-focus-box-shadow);\n  }\n}\n\n.accordion-header {\n  margin-bottom: 0;\n}\n\n.accordion-item {\n  color: var(--#{$prefix}accordion-color);\n  background-color: var(--#{$prefix}accordion-bg);\n  border: var(--#{$prefix}accordion-border-width) solid var(--#{$prefix}accordion-border-color);\n\n  &:first-of-type {\n    @include border-top-radius(var(--#{$prefix}accordion-border-radius));\n\n    .accordion-button {\n      @include border-top-radius(var(--#{$prefix}accordion-inner-border-radius));\n    }\n  }\n\n  &:not(:first-of-type) {\n    border-top: 0;\n  }\n\n  // Only set a border-radius on the last item if the accordion is collapsed\n  &:last-of-type {\n    @include border-bottom-radius(var(--#{$prefix}accordion-border-radius));\n\n    .accordion-button {\n      &.collapsed {\n        @include border-bottom-radius(var(--#{$prefix}accordion-inner-border-radius));\n      }\n    }\n\n    .accordion-collapse {\n      @include border-bottom-radius(var(--#{$prefix}accordion-border-radius));\n    }\n  }\n}\n\n.accordion-body {\n  padding: var(--#{$prefix}accordion-body-padding-y) var(--#{$prefix}accordion-body-padding-x);\n}\n\n\n// Flush accordion items\n//\n// Remove borders and border-radius to keep accordion items edge-to-edge.\n\n.accordion-flush {\n  .accordion-collapse {\n    border-width: 0;\n  }\n\n  .accordion-item {\n    border-right: 0;\n    border-left: 0;\n    @include border-radius(0);\n\n    &:first-child { border-top: 0; }\n    &:last-child { border-bottom: 0; }\n\n    .accordion-button {\n      &,\n      &.collapsed {\n        @include border-radius(0);\n      }\n    }\n  }\n}\n\n@if $enable-dark-mode {\n  @include color-mode(dark) {\n    .accordion-button::after {\n      --#{$prefix}accordion-btn-icon: #{escape-svg($accordion-button-icon-dark)};\n      --#{$prefix}accordion-btn-active-icon: #{escape-svg($accordion-button-active-icon-dark)};\n    }\n  }\n}\n",".breadcrumb {\n  // scss-docs-start breadcrumb-css-vars\n  --#{$prefix}breadcrumb-padding-x: #{$breadcrumb-padding-x};\n  --#{$prefix}breadcrumb-padding-y: #{$breadcrumb-padding-y};\n  --#{$prefix}breadcrumb-margin-bottom: #{$breadcrumb-margin-bottom};\n  @include rfs($breadcrumb-font-size, --#{$prefix}breadcrumb-font-size);\n  --#{$prefix}breadcrumb-bg: #{$breadcrumb-bg};\n  --#{$prefix}breadcrumb-border-radius: #{$breadcrumb-border-radius};\n  --#{$prefix}breadcrumb-divider-color: #{$breadcrumb-divider-color};\n  --#{$prefix}breadcrumb-item-padding-x: #{$breadcrumb-item-padding-x};\n  --#{$prefix}breadcrumb-item-active-color: #{$breadcrumb-active-color};\n  // scss-docs-end breadcrumb-css-vars\n\n  display: flex;\n  flex-wrap: wrap;\n  padding: var(--#{$prefix}breadcrumb-padding-y) var(--#{$prefix}breadcrumb-padding-x);\n  margin-bottom: var(--#{$prefix}breadcrumb-margin-bottom);\n  @include font-size(var(--#{$prefix}breadcrumb-font-size));\n  list-style: none;\n  background-color: var(--#{$prefix}breadcrumb-bg);\n  @include border-radius(var(--#{$prefix}breadcrumb-border-radius));\n}\n\n.breadcrumb-item {\n  // The separator between breadcrumbs (by default, a forward-slash: \"/\")\n  + .breadcrumb-item {\n    padding-left: var(--#{$prefix}breadcrumb-item-padding-x);\n\n    &::before {\n      float: left; // Suppress inline spacings and underlining of the separator\n      padding-right: var(--#{$prefix}breadcrumb-item-padding-x);\n      color: var(--#{$prefix}breadcrumb-divider-color);\n      content: var(--#{$prefix}breadcrumb-divider, escape-svg($breadcrumb-divider)) #{\"/* rtl:\"} var(--#{$prefix}breadcrumb-divider, escape-svg($breadcrumb-divider-flipped)) #{\"*/\"};\n    }\n  }\n\n  &.active {\n    color: var(--#{$prefix}breadcrumb-item-active-color);\n  }\n}\n",".pagination {\n  // scss-docs-start pagination-css-vars\n  --#{$prefix}pagination-padding-x: #{$pagination-padding-x};\n  --#{$prefix}pagination-padding-y: #{$pagination-padding-y};\n  @include rfs($pagination-font-size, --#{$prefix}pagination-font-size);\n  --#{$prefix}pagination-color: #{$pagination-color};\n  --#{$prefix}pagination-bg: #{$pagination-bg};\n  --#{$prefix}pagination-border-width: #{$pagination-border-width};\n  --#{$prefix}pagination-border-color: #{$pagination-border-color};\n  --#{$prefix}pagination-border-radius: #{$pagination-border-radius};\n  --#{$prefix}pagination-hover-color: #{$pagination-hover-color};\n  --#{$prefix}pagination-hover-bg: #{$pagination-hover-bg};\n  --#{$prefix}pagination-hover-border-color: #{$pagination-hover-border-color};\n  --#{$prefix}pagination-focus-color: #{$pagination-focus-color};\n  --#{$prefix}pagination-focus-bg: #{$pagination-focus-bg};\n  --#{$prefix}pagination-focus-box-shadow: #{$pagination-focus-box-shadow};\n  --#{$prefix}pagination-active-color: #{$pagination-active-color};\n  --#{$prefix}pagination-active-bg: #{$pagination-active-bg};\n  --#{$prefix}pagination-active-border-color: #{$pagination-active-border-color};\n  --#{$prefix}pagination-disabled-color: #{$pagination-disabled-color};\n  --#{$prefix}pagination-disabled-bg: #{$pagination-disabled-bg};\n  --#{$prefix}pagination-disabled-border-color: #{$pagination-disabled-border-color};\n  // scss-docs-end pagination-css-vars\n\n  display: flex;\n  @include list-unstyled();\n}\n\n.page-link {\n  position: relative;\n  display: block;\n  padding: var(--#{$prefix}pagination-padding-y) var(--#{$prefix}pagination-padding-x);\n  @include font-size(var(--#{$prefix}pagination-font-size));\n  color: var(--#{$prefix}pagination-color);\n  text-decoration: if($link-decoration == none, null, none);\n  background-color: var(--#{$prefix}pagination-bg);\n  border: var(--#{$prefix}pagination-border-width) solid var(--#{$prefix}pagination-border-color);\n  @include transition($pagination-transition);\n\n  &:hover {\n    z-index: 2;\n    color: var(--#{$prefix}pagination-hover-color);\n    text-decoration: if($link-hover-decoration == underline, none, null);\n    background-color: var(--#{$prefix}pagination-hover-bg);\n    border-color: var(--#{$prefix}pagination-hover-border-color);\n  }\n\n  &:focus {\n    z-index: 3;\n    color: var(--#{$prefix}pagination-focus-color);\n    background-color: var(--#{$prefix}pagination-focus-bg);\n    outline: $pagination-focus-outline;\n    box-shadow: var(--#{$prefix}pagination-focus-box-shadow);\n  }\n\n  &.active,\n  .active > & {\n    z-index: 3;\n    color: var(--#{$prefix}pagination-active-color);\n    @include gradient-bg(var(--#{$prefix}pagination-active-bg));\n    border-color: var(--#{$prefix}pagination-active-border-color);\n  }\n\n  &.disabled,\n  .disabled > & {\n    color: var(--#{$prefix}pagination-disabled-color);\n    pointer-events: none;\n    background-color: var(--#{$prefix}pagination-disabled-bg);\n    border-color: var(--#{$prefix}pagination-disabled-border-color);\n  }\n}\n\n.page-item {\n  &:not(:first-child) .page-link {\n    margin-left: $pagination-margin-start;\n  }\n\n  @if $pagination-margin-start == calc(#{$pagination-border-width} * -1) {\n    &:first-child {\n      .page-link {\n        @include border-start-radius(var(--#{$prefix}pagination-border-radius));\n      }\n    }\n\n    &:last-child {\n      .page-link {\n        @include border-end-radius(var(--#{$prefix}pagination-border-radius));\n      }\n    }\n  } @else {\n    // Add border-radius to all pageLinks in case they have left margin\n    .page-link {\n      @include border-radius(var(--#{$prefix}pagination-border-radius));\n    }\n  }\n}\n\n\n//\n// Sizing\n//\n\n.pagination-lg {\n  @include pagination-size($pagination-padding-y-lg, $pagination-padding-x-lg, $font-size-lg, $pagination-border-radius-lg);\n}\n\n.pagination-sm {\n  @include pagination-size($pagination-padding-y-sm, $pagination-padding-x-sm, $font-size-sm, $pagination-border-radius-sm);\n}\n","// Pagination\n\n// scss-docs-start pagination-mixin\n@mixin pagination-size($padding-y, $padding-x, $font-size, $border-radius) {\n  --#{$prefix}pagination-padding-x: #{$padding-x};\n  --#{$prefix}pagination-padding-y: #{$padding-y};\n  @include rfs($font-size, --#{$prefix}pagination-font-size);\n  --#{$prefix}pagination-border-radius: #{$border-radius};\n}\n// scss-docs-end pagination-mixin\n","// Base class\n//\n// Requires one of the contextual, color modifier classes for `color` and\n// `background-color`.\n\n.badge {\n  // scss-docs-start badge-css-vars\n  --#{$prefix}badge-padding-x: #{$badge-padding-x};\n  --#{$prefix}badge-padding-y: #{$badge-padding-y};\n  @include rfs($badge-font-size, --#{$prefix}badge-font-size);\n  --#{$prefix}badge-font-weight: #{$badge-font-weight};\n  --#{$prefix}badge-color: #{$badge-color};\n  --#{$prefix}badge-border-radius: #{$badge-border-radius};\n  // scss-docs-end badge-css-vars\n\n  display: inline-block;\n  padding: var(--#{$prefix}badge-padding-y) var(--#{$prefix}badge-padding-x);\n  @include font-size(var(--#{$prefix}badge-font-size));\n  font-weight: var(--#{$prefix}badge-font-weight);\n  line-height: 1;\n  color: var(--#{$prefix}badge-color);\n  text-align: center;\n  white-space: nowrap;\n  vertical-align: baseline;\n  @include border-radius(var(--#{$prefix}badge-border-radius));\n  @include gradient-bg();\n\n  // Empty badges collapse automatically\n  &:empty {\n    display: none;\n  }\n}\n\n// Quick fix for badges in buttons\n.btn .badge {\n  position: relative;\n  top: -1px;\n}\n","//\n// Base styles\n//\n\n.alert {\n  // scss-docs-start alert-css-vars\n  --#{$prefix}alert-bg: transparent;\n  --#{$prefix}alert-padding-x: #{$alert-padding-x};\n  --#{$prefix}alert-padding-y: #{$alert-padding-y};\n  --#{$prefix}alert-margin-bottom: #{$alert-margin-bottom};\n  --#{$prefix}alert-color: inherit;\n  --#{$prefix}alert-border-color: transparent;\n  --#{$prefix}alert-border: #{$alert-border-width} solid var(--#{$prefix}alert-border-color);\n  --#{$prefix}alert-border-radius: #{$alert-border-radius};\n  --#{$prefix}alert-link-color: inherit;\n  // scss-docs-end alert-css-vars\n\n  position: relative;\n  padding: var(--#{$prefix}alert-padding-y) var(--#{$prefix}alert-padding-x);\n  margin-bottom: var(--#{$prefix}alert-margin-bottom);\n  color: var(--#{$prefix}alert-color);\n  background-color: var(--#{$prefix}alert-bg);\n  border: var(--#{$prefix}alert-border);\n  @include border-radius(var(--#{$prefix}alert-border-radius));\n}\n\n// Headings for larger alerts\n.alert-heading {\n  // Specified to prevent conflicts of changing $headings-color\n  color: inherit;\n}\n\n// Provide class for links that match alerts\n.alert-link {\n  font-weight: $alert-link-font-weight;\n  color: var(--#{$prefix}alert-link-color);\n}\n\n\n// Dismissible alerts\n//\n// Expand the right padding and account for the close button's positioning.\n\n.alert-dismissible {\n  padding-right: $alert-dismissible-padding-r;\n\n  // Adjust close link position\n  .btn-close {\n    position: absolute;\n    top: 0;\n    right: 0;\n    z-index: $stretched-link-z-index + 1;\n    padding: $alert-padding-y * 1.25 $alert-padding-x;\n  }\n}\n\n\n// scss-docs-start alert-modifiers\n// Generate contextual modifier classes for colorizing the alert\n@each $state in map-keys($theme-colors) {\n  .alert-#{$state} {\n    --#{$prefix}alert-color: var(--#{$prefix}#{$state}-text-emphasis);\n    --#{$prefix}alert-bg: var(--#{$prefix}#{$state}-bg-subtle);\n    --#{$prefix}alert-border-color: var(--#{$prefix}#{$state}-border-subtle);\n    --#{$prefix}alert-link-color: var(--#{$prefix}#{$state}-text-emphasis);\n  }\n}\n// scss-docs-end alert-modifiers\n","// Disable animation if transitions are disabled\n\n// scss-docs-start progress-keyframes\n@if $enable-transitions {\n  @keyframes progress-bar-stripes {\n    0% { background-position-x: $progress-height; }\n  }\n}\n// scss-docs-end progress-keyframes\n\n.progress,\n.progress-stacked {\n  // scss-docs-start progress-css-vars\n  --#{$prefix}progress-height: #{$progress-height};\n  @include rfs($progress-font-size, --#{$prefix}progress-font-size);\n  --#{$prefix}progress-bg: #{$progress-bg};\n  --#{$prefix}progress-border-radius: #{$progress-border-radius};\n  --#{$prefix}progress-box-shadow: #{$progress-box-shadow};\n  --#{$prefix}progress-bar-color: #{$progress-bar-color};\n  --#{$prefix}progress-bar-bg: #{$progress-bar-bg};\n  --#{$prefix}progress-bar-transition: #{$progress-bar-transition};\n  // scss-docs-end progress-css-vars\n\n  display: flex;\n  height: var(--#{$prefix}progress-height);\n  overflow: hidden; // force rounded corners by cropping it\n  @include font-size(var(--#{$prefix}progress-font-size));\n  background-color: var(--#{$prefix}progress-bg);\n  @include border-radius(var(--#{$prefix}progress-border-radius));\n  @include box-shadow(var(--#{$prefix}progress-box-shadow));\n}\n\n.progress-bar {\n  display: flex;\n  flex-direction: column;\n  justify-content: center;\n  overflow: hidden;\n  color: var(--#{$prefix}progress-bar-color);\n  text-align: center;\n  white-space: nowrap;\n  background-color: var(--#{$prefix}progress-bar-bg);\n  @include transition(var(--#{$prefix}progress-bar-transition));\n}\n\n.progress-bar-striped {\n  @include gradient-striped();\n  background-size: var(--#{$prefix}progress-height) var(--#{$prefix}progress-height);\n}\n\n.progress-stacked > .progress {\n  overflow: visible;\n}\n\n.progress-stacked > .progress > .progress-bar {\n  width: 100%;\n}\n\n@if $enable-transitions {\n  .progress-bar-animated {\n    animation: $progress-bar-animation-timing progress-bar-stripes;\n\n    @if $enable-reduced-motion {\n      @media (prefers-reduced-motion: reduce) {\n        animation: none;\n      }\n    }\n  }\n}\n","// Base class\n//\n// Easily usable on <ul>, <ol>, or <div>.\n\n.list-group {\n  // scss-docs-start list-group-css-vars\n  --#{$prefix}list-group-color: #{$list-group-color};\n  --#{$prefix}list-group-bg: #{$list-group-bg};\n  --#{$prefix}list-group-border-color: #{$list-group-border-color};\n  --#{$prefix}list-group-border-width: #{$list-group-border-width};\n  --#{$prefix}list-group-border-radius: #{$list-group-border-radius};\n  --#{$prefix}list-group-item-padding-x: #{$list-group-item-padding-x};\n  --#{$prefix}list-group-item-padding-y: #{$list-group-item-padding-y};\n  --#{$prefix}list-group-action-color: #{$list-group-action-color};\n  --#{$prefix}list-group-action-hover-color: #{$list-group-action-hover-color};\n  --#{$prefix}list-group-action-hover-bg: #{$list-group-hover-bg};\n  --#{$prefix}list-group-action-active-color: #{$list-group-action-active-color};\n  --#{$prefix}list-group-action-active-bg: #{$list-group-action-active-bg};\n  --#{$prefix}list-group-disabled-color: #{$list-group-disabled-color};\n  --#{$prefix}list-group-disabled-bg: #{$list-group-disabled-bg};\n  --#{$prefix}list-group-active-color: #{$list-group-active-color};\n  --#{$prefix}list-group-active-bg: #{$list-group-active-bg};\n  --#{$prefix}list-group-active-border-color: #{$list-group-active-border-color};\n  // scss-docs-end list-group-css-vars\n\n  display: flex;\n  flex-direction: column;\n\n  // No need to set list-style: none; since .list-group-item is block level\n  padding-left: 0; // reset padding because ul and ol\n  margin-bottom: 0;\n  @include border-radius(var(--#{$prefix}list-group-border-radius));\n}\n\n.list-group-numbered {\n  list-style-type: none;\n  counter-reset: section;\n\n  > .list-group-item::before {\n    // Increments only this instance of the section counter\n    content: counters(section, \".\") \". \";\n    counter-increment: section;\n  }\n}\n\n// Interactive list items\n//\n// Use anchor or button elements instead of `li`s or `div`s to create interactive\n// list items. Includes an extra `.active` modifier class for selected items.\n\n.list-group-item-action {\n  width: 100%; // For `<button>`s (anchors become 100% by default though)\n  color: var(--#{$prefix}list-group-action-color);\n  text-align: inherit; // For `<button>`s (anchors inherit)\n\n  // Hover state\n  &:hover,\n  &:focus {\n    z-index: 1; // Place hover/focus items above their siblings for proper border styling\n    color: var(--#{$prefix}list-group-action-hover-color);\n    text-decoration: none;\n    background-color: var(--#{$prefix}list-group-action-hover-bg);\n  }\n\n  &:active {\n    color: var(--#{$prefix}list-group-action-active-color);\n    background-color: var(--#{$prefix}list-group-action-active-bg);\n  }\n}\n\n// Individual list items\n//\n// Use on `li`s or `div`s within the `.list-group` parent.\n\n.list-group-item {\n  position: relative;\n  display: block;\n  padding: var(--#{$prefix}list-group-item-padding-y) var(--#{$prefix}list-group-item-padding-x);\n  color: var(--#{$prefix}list-group-color);\n  text-decoration: if($link-decoration == none, null, none);\n  background-color: var(--#{$prefix}list-group-bg);\n  border: var(--#{$prefix}list-group-border-width) solid var(--#{$prefix}list-group-border-color);\n\n  &:first-child {\n    @include border-top-radius(inherit);\n  }\n\n  &:last-child {\n    @include border-bottom-radius(inherit);\n  }\n\n  &.disabled,\n  &:disabled {\n    color: var(--#{$prefix}list-group-disabled-color);\n    pointer-events: none;\n    background-color: var(--#{$prefix}list-group-disabled-bg);\n  }\n\n  // Include both here for `<a>`s and `<button>`s\n  &.active {\n    z-index: 2; // Place active items above their siblings for proper border styling\n    color: var(--#{$prefix}list-group-active-color);\n    background-color: var(--#{$prefix}list-group-active-bg);\n    border-color: var(--#{$prefix}list-group-active-border-color);\n  }\n\n  // stylelint-disable-next-line scss/selector-no-redundant-nesting-selector\n  & + .list-group-item {\n    border-top-width: 0;\n\n    &.active {\n      margin-top: calc(-1 * var(--#{$prefix}list-group-border-width)); // stylelint-disable-line function-disallowed-list\n      border-top-width: var(--#{$prefix}list-group-border-width);\n    }\n  }\n}\n\n// Horizontal\n//\n// Change the layout of list group items from vertical (default) to horizontal.\n\n@each $breakpoint in map-keys($grid-breakpoints) {\n  @include media-breakpoint-up($breakpoint) {\n    $infix: breakpoint-infix($breakpoint, $grid-breakpoints);\n\n    .list-group-horizontal#{$infix} {\n      flex-direction: row;\n\n      > .list-group-item {\n        &:first-child:not(:last-child) {\n          @include border-bottom-start-radius(var(--#{$prefix}list-group-border-radius));\n          @include border-top-end-radius(0);\n        }\n\n        &:last-child:not(:first-child) {\n          @include border-top-end-radius(var(--#{$prefix}list-group-border-radius));\n          @include border-bottom-start-radius(0);\n        }\n\n        &.active {\n          margin-top: 0;\n        }\n\n        + .list-group-item {\n          border-top-width: var(--#{$prefix}list-group-border-width);\n          border-left-width: 0;\n\n          &.active {\n            margin-left: calc(-1 * var(--#{$prefix}list-group-border-width)); // stylelint-disable-line function-disallowed-list\n            border-left-width: var(--#{$prefix}list-group-border-width);\n          }\n        }\n      }\n    }\n  }\n}\n\n\n// Flush list items\n//\n// Remove borders and border-radius to keep list group items edge-to-edge. Most\n// useful within other components (e.g., cards).\n\n.list-group-flush {\n  @include border-radius(0);\n\n  > .list-group-item {\n    border-width: 0 0 var(--#{$prefix}list-group-border-width);\n\n    &:last-child {\n      border-bottom-width: 0;\n    }\n  }\n}\n\n\n// scss-docs-start list-group-modifiers\n// List group contextual variants\n//\n// Add modifier classes to change text and background color on individual items.\n// Organizationally, this must come after the `:hover` states.\n\n@each $state in map-keys($theme-colors) {\n  .list-group-item-#{$state} {\n    --#{$prefix}list-group-color: var(--#{$prefix}#{$state}-text-emphasis);\n    --#{$prefix}list-group-bg: var(--#{$prefix}#{$state}-bg-subtle);\n    --#{$prefix}list-group-border-color: var(--#{$prefix}#{$state}-border-subtle);\n    --#{$prefix}list-group-action-hover-color: var(--#{$prefix}emphasis-color);\n    --#{$prefix}list-group-action-hover-bg: var(--#{$prefix}#{$state}-border-subtle);\n    --#{$prefix}list-group-action-active-color: var(--#{$prefix}emphasis-color);\n    --#{$prefix}list-group-action-active-bg: var(--#{$prefix}#{$state}-border-subtle);\n    --#{$prefix}list-group-active-color: var(--#{$prefix}#{$state}-bg-subtle);\n    --#{$prefix}list-group-active-bg: var(--#{$prefix}#{$state}-text-emphasis);\n    --#{$prefix}list-group-active-border-color: var(--#{$prefix}#{$state}-text-emphasis);\n  }\n}\n// scss-docs-end list-group-modifiers\n","// Transparent background and border properties included for button version.\n// iOS requires the button element instead of an anchor tag.\n// If you want the anchor version, it requires `href=\"#\"`.\n// See https://developer.mozilla.org/en-US/docs/Web/Events/click#Safari_Mobile\n\n.btn-close {\n  // scss-docs-start close-css-vars\n  --#{$prefix}btn-close-color: #{$btn-close-color};\n  --#{$prefix}btn-close-bg: #{ escape-svg($btn-close-bg) };\n  --#{$prefix}btn-close-opacity: #{$btn-close-opacity};\n  --#{$prefix}btn-close-hover-opacity: #{$btn-close-hover-opacity};\n  --#{$prefix}btn-close-focus-shadow: #{$btn-close-focus-shadow};\n  --#{$prefix}btn-close-focus-opacity: #{$btn-close-focus-opacity};\n  --#{$prefix}btn-close-disabled-opacity: #{$btn-close-disabled-opacity};\n  --#{$prefix}btn-close-white-filter: #{$btn-close-white-filter};\n  // scss-docs-end close-css-vars\n\n  box-sizing: content-box;\n  width: $btn-close-width;\n  height: $btn-close-height;\n  padding: $btn-close-padding-y $btn-close-padding-x;\n  color: var(--#{$prefix}btn-close-color);\n  background: transparent var(--#{$prefix}btn-close-bg) center / $btn-close-width auto no-repeat; // include transparent for button elements\n  border: 0; // for button elements\n  @include border-radius();\n  opacity: var(--#{$prefix}btn-close-opacity);\n\n  // Override <a>'s hover style\n  &:hover {\n    color: var(--#{$prefix}btn-close-color);\n    text-decoration: none;\n    opacity: var(--#{$prefix}btn-close-hover-opacity);\n  }\n\n  &:focus {\n    outline: 0;\n    box-shadow: var(--#{$prefix}btn-close-focus-shadow);\n    opacity: var(--#{$prefix}btn-close-focus-opacity);\n  }\n\n  &:disabled,\n  &.disabled {\n    pointer-events: none;\n    user-select: none;\n    opacity: var(--#{$prefix}btn-close-disabled-opacity);\n  }\n}\n\n@mixin btn-close-white() {\n  filter: var(--#{$prefix}btn-close-white-filter);\n}\n\n.btn-close-white {\n  @include btn-close-white();\n}\n\n@if $enable-dark-mode {\n  @include color-mode(dark) {\n    .btn-close {\n      @include btn-close-white();\n    }\n  }\n}\n",".toast {\n  // scss-docs-start toast-css-vars\n  --#{$prefix}toast-zindex: #{$zindex-toast};\n  --#{$prefix}toast-padding-x: #{$toast-padding-x};\n  --#{$prefix}toast-padding-y: #{$toast-padding-y};\n  --#{$prefix}toast-spacing: #{$toast-spacing};\n  --#{$prefix}toast-max-width: #{$toast-max-width};\n  @include rfs($toast-font-size, --#{$prefix}toast-font-size);\n  --#{$prefix}toast-color: #{$toast-color};\n  --#{$prefix}toast-bg: #{$toast-background-color};\n  --#{$prefix}toast-border-width: #{$toast-border-width};\n  --#{$prefix}toast-border-color: #{$toast-border-color};\n  --#{$prefix}toast-border-radius: #{$toast-border-radius};\n  --#{$prefix}toast-box-shadow: #{$toast-box-shadow};\n  --#{$prefix}toast-header-color: #{$toast-header-color};\n  --#{$prefix}toast-header-bg: #{$toast-header-background-color};\n  --#{$prefix}toast-header-border-color: #{$toast-header-border-color};\n  // scss-docs-end toast-css-vars\n\n  width: var(--#{$prefix}toast-max-width);\n  max-width: 100%;\n  @include font-size(var(--#{$prefix}toast-font-size));\n  color: var(--#{$prefix}toast-color);\n  pointer-events: auto;\n  background-color: var(--#{$prefix}toast-bg);\n  background-clip: padding-box;\n  border: var(--#{$prefix}toast-border-width) solid var(--#{$prefix}toast-border-color);\n  box-shadow: var(--#{$prefix}toast-box-shadow);\n  @include border-radius(var(--#{$prefix}toast-border-radius));\n\n  &.showing {\n    opacity: 0;\n  }\n\n  &:not(.show) {\n    display: none;\n  }\n}\n\n.toast-container {\n  --#{$prefix}toast-zindex: #{$zindex-toast};\n\n  position: absolute;\n  z-index: var(--#{$prefix}toast-zindex);\n  width: max-content;\n  max-width: 100%;\n  pointer-events: none;\n\n  > :not(:last-child) {\n    margin-bottom: var(--#{$prefix}toast-spacing);\n  }\n}\n\n.toast-header {\n  display: flex;\n  align-items: center;\n  padding: var(--#{$prefix}toast-padding-y) var(--#{$prefix}toast-padding-x);\n  color: var(--#{$prefix}toast-header-color);\n  background-color: var(--#{$prefix}toast-header-bg);\n  background-clip: padding-box;\n  border-bottom: var(--#{$prefix}toast-border-width) solid var(--#{$prefix}toast-header-border-color);\n  @include border-top-radius(calc(var(--#{$prefix}toast-border-radius) - var(--#{$prefix}toast-border-width)));\n\n  .btn-close {\n    margin-right: calc(-.5 * var(--#{$prefix}toast-padding-x)); // stylelint-disable-line function-disallowed-list\n    margin-left: var(--#{$prefix}toast-padding-x);\n  }\n}\n\n.toast-body {\n  padding: var(--#{$prefix}toast-padding-x);\n  word-wrap: break-word;\n}\n","// stylelint-disable function-disallowed-list\n\n// .modal-open      - body class for killing the scroll\n// .modal           - container to scroll within\n// .modal-dialog    - positioning shell for the actual modal\n// .modal-content   - actual modal w/ bg and corners and stuff\n\n\n// Container that the modal scrolls within\n.modal {\n  // scss-docs-start modal-css-vars\n  --#{$prefix}modal-zindex: #{$zindex-modal};\n  --#{$prefix}modal-width: #{$modal-md};\n  --#{$prefix}modal-padding: #{$modal-inner-padding};\n  --#{$prefix}modal-margin: #{$modal-dialog-margin};\n  --#{$prefix}modal-color: #{$modal-content-color};\n  --#{$prefix}modal-bg: #{$modal-content-bg};\n  --#{$prefix}modal-border-color: #{$modal-content-border-color};\n  --#{$prefix}modal-border-width: #{$modal-content-border-width};\n  --#{$prefix}modal-border-radius: #{$modal-content-border-radius};\n  --#{$prefix}modal-box-shadow: #{$modal-content-box-shadow-xs};\n  --#{$prefix}modal-inner-border-radius: #{$modal-content-inner-border-radius};\n  --#{$prefix}modal-header-padding-x: #{$modal-header-padding-x};\n  --#{$prefix}modal-header-padding-y: #{$modal-header-padding-y};\n  --#{$prefix}modal-header-padding: #{$modal-header-padding}; // Todo in v6: Split this padding into x and y\n  --#{$prefix}modal-header-border-color: #{$modal-header-border-color};\n  --#{$prefix}modal-header-border-width: #{$modal-header-border-width};\n  --#{$prefix}modal-title-line-height: #{$modal-title-line-height};\n  --#{$prefix}modal-footer-gap: #{$modal-footer-margin-between};\n  --#{$prefix}modal-footer-bg: #{$modal-footer-bg};\n  --#{$prefix}modal-footer-border-color: #{$modal-footer-border-color};\n  --#{$prefix}modal-footer-border-width: #{$modal-footer-border-width};\n  // scss-docs-end modal-css-vars\n\n  position: fixed;\n  top: 0;\n  left: 0;\n  z-index: var(--#{$prefix}modal-zindex);\n  display: none;\n  width: 100%;\n  height: 100%;\n  overflow-x: hidden;\n  overflow-y: auto;\n  // Prevent Chrome on Windows from adding a focus outline. For details, see\n  // https://github.com/twbs/bootstrap/pull/10951.\n  outline: 0;\n  // We deliberately don't use `-webkit-overflow-scrolling: touch;` due to a\n  // gnarly iOS Safari bug: https://bugs.webkit.org/show_bug.cgi?id=158342\n  // See also https://github.com/twbs/bootstrap/issues/17695\n}\n\n// Shell div to position the modal with bottom padding\n.modal-dialog {\n  position: relative;\n  width: auto;\n  margin: var(--#{$prefix}modal-margin);\n  // allow clicks to pass through for custom click handling to close modal\n  pointer-events: none;\n\n  // When fading in the modal, animate it to slide down\n  .modal.fade & {\n    @include transition($modal-transition);\n    transform: $modal-fade-transform;\n  }\n  .modal.show & {\n    transform: $modal-show-transform;\n  }\n\n  // When trying to close, animate focus to scale\n  .modal.modal-static & {\n    transform: $modal-scale-transform;\n  }\n}\n\n.modal-dialog-scrollable {\n  height: calc(100% - var(--#{$prefix}modal-margin) * 2);\n\n  .modal-content {\n    max-height: 100%;\n    overflow: hidden;\n  }\n\n  .modal-body {\n    overflow-y: auto;\n  }\n}\n\n.modal-dialog-centered {\n  display: flex;\n  align-items: center;\n  min-height: calc(100% - var(--#{$prefix}modal-margin) * 2);\n}\n\n// Actual modal\n.modal-content {\n  position: relative;\n  display: flex;\n  flex-direction: column;\n  width: 100%; // Ensure `.modal-content` extends the full width of the parent `.modal-dialog`\n  // counteract the pointer-events: none; in the .modal-dialog\n  color: var(--#{$prefix}modal-color);\n  pointer-events: auto;\n  background-color: var(--#{$prefix}modal-bg);\n  background-clip: padding-box;\n  border: var(--#{$prefix}modal-border-width) solid var(--#{$prefix}modal-border-color);\n  @include border-radius(var(--#{$prefix}modal-border-radius));\n  @include box-shadow(var(--#{$prefix}modal-box-shadow));\n  // Remove focus outline from opened modal\n  outline: 0;\n}\n\n// Modal background\n.modal-backdrop {\n  // scss-docs-start modal-backdrop-css-vars\n  --#{$prefix}backdrop-zindex: #{$zindex-modal-backdrop};\n  --#{$prefix}backdrop-bg: #{$modal-backdrop-bg};\n  --#{$prefix}backdrop-opacity: #{$modal-backdrop-opacity};\n  // scss-docs-end modal-backdrop-css-vars\n\n  @include overlay-backdrop(var(--#{$prefix}backdrop-zindex), var(--#{$prefix}backdrop-bg), var(--#{$prefix}backdrop-opacity));\n}\n\n// Modal header\n// Top section of the modal w/ title and dismiss\n.modal-header {\n  display: flex;\n  flex-shrink: 0;\n  align-items: center;\n  justify-content: space-between; // Put modal header elements (title and dismiss) on opposite ends\n  padding: var(--#{$prefix}modal-header-padding);\n  border-bottom: var(--#{$prefix}modal-header-border-width) solid var(--#{$prefix}modal-header-border-color);\n  @include border-top-radius(var(--#{$prefix}modal-inner-border-radius));\n\n  .btn-close {\n    padding: calc(var(--#{$prefix}modal-header-padding-y) * .5) calc(var(--#{$prefix}modal-header-padding-x) * .5);\n    margin: calc(-.5 * var(--#{$prefix}modal-header-padding-y)) calc(-.5 * var(--#{$prefix}modal-header-padding-x)) calc(-.5 * var(--#{$prefix}modal-header-padding-y)) auto;\n  }\n}\n\n// Title text within header\n.modal-title {\n  margin-bottom: 0;\n  line-height: var(--#{$prefix}modal-title-line-height);\n}\n\n// Modal body\n// Where all modal content resides (sibling of .modal-header and .modal-footer)\n.modal-body {\n  position: relative;\n  // Enable `flex-grow: 1` so that the body take up as much space as possible\n  // when there should be a fixed height on `.modal-dialog`.\n  flex: 1 1 auto;\n  padding: var(--#{$prefix}modal-padding);\n}\n\n// Footer (for actions)\n.modal-footer {\n  display: flex;\n  flex-shrink: 0;\n  flex-wrap: wrap;\n  align-items: center; // vertically center\n  justify-content: flex-end; // Right align buttons with flex property because text-align doesn't work on flex items\n  padding: calc(var(--#{$prefix}modal-padding) - var(--#{$prefix}modal-footer-gap) * .5);\n  background-color: var(--#{$prefix}modal-footer-bg);\n  border-top: var(--#{$prefix}modal-footer-border-width) solid var(--#{$prefix}modal-footer-border-color);\n  @include border-bottom-radius(var(--#{$prefix}modal-inner-border-radius));\n\n  // Place margin between footer elements\n  // This solution is far from ideal because of the universal selector usage,\n  // but is needed to fix https://github.com/twbs/bootstrap/issues/24800\n  > * {\n    margin: calc(var(--#{$prefix}modal-footer-gap) * .5); // Todo in v6: replace with gap on parent class\n  }\n}\n\n// Scale up the modal\n@include media-breakpoint-up(sm) {\n  .modal {\n    --#{$prefix}modal-margin: #{$modal-dialog-margin-y-sm-up};\n    --#{$prefix}modal-box-shadow: #{$modal-content-box-shadow-sm-up};\n  }\n\n  // Automatically set modal's width for larger viewports\n  .modal-dialog {\n    max-width: var(--#{$prefix}modal-width);\n    margin-right: auto;\n    margin-left: auto;\n  }\n\n  .modal-sm {\n    --#{$prefix}modal-width: #{$modal-sm};\n  }\n}\n\n@include media-breakpoint-up(lg) {\n  .modal-lg,\n  .modal-xl {\n    --#{$prefix}modal-width: #{$modal-lg};\n  }\n}\n\n@include media-breakpoint-up(xl) {\n  .modal-xl {\n    --#{$prefix}modal-width: #{$modal-xl};\n  }\n}\n\n// scss-docs-start modal-fullscreen-loop\n@each $breakpoint in map-keys($grid-breakpoints) {\n  $infix: breakpoint-infix($breakpoint, $grid-breakpoints);\n  $postfix: if($infix != \"\", $infix + \"-down\", \"\");\n\n  @include media-breakpoint-down($breakpoint) {\n    .modal-fullscreen#{$postfix} {\n      width: 100vw;\n      max-width: none;\n      height: 100%;\n      margin: 0;\n\n      .modal-content {\n        height: 100%;\n        border: 0;\n        @include border-radius(0);\n      }\n\n      .modal-header,\n      .modal-footer {\n        @include border-radius(0);\n      }\n\n      .modal-body {\n        overflow-y: auto;\n      }\n    }\n  }\n}\n// scss-docs-end modal-fullscreen-loop\n","// Shared between modals and offcanvases\n@mixin overlay-backdrop($zindex, $backdrop-bg, $backdrop-opacity) {\n  position: fixed;\n  top: 0;\n  left: 0;\n  z-index: $zindex;\n  width: 100vw;\n  height: 100vh;\n  background-color: $backdrop-bg;\n\n  // Fade for backdrop\n  &.fade { opacity: 0; }\n  &.show { opacity: $backdrop-opacity; }\n}\n","// Base class\n.tooltip {\n  // scss-docs-start tooltip-css-vars\n  --#{$prefix}tooltip-zindex: #{$zindex-tooltip};\n  --#{$prefix}tooltip-max-width: #{$tooltip-max-width};\n  --#{$prefix}tooltip-padding-x: #{$tooltip-padding-x};\n  --#{$prefix}tooltip-padding-y: #{$tooltip-padding-y};\n  --#{$prefix}tooltip-margin: #{$tooltip-margin};\n  @include rfs($tooltip-font-size, --#{$prefix}tooltip-font-size);\n  --#{$prefix}tooltip-color: #{$tooltip-color};\n  --#{$prefix}tooltip-bg: #{$tooltip-bg};\n  --#{$prefix}tooltip-border-radius: #{$tooltip-border-radius};\n  --#{$prefix}tooltip-opacity: #{$tooltip-opacity};\n  --#{$prefix}tooltip-arrow-width: #{$tooltip-arrow-width};\n  --#{$prefix}tooltip-arrow-height: #{$tooltip-arrow-height};\n  // scss-docs-end tooltip-css-vars\n\n  z-index: var(--#{$prefix}tooltip-zindex);\n  display: block;\n  margin: var(--#{$prefix}tooltip-margin);\n  @include deprecate(\"`$tooltip-margin`\", \"v5\", \"v5.x\", true);\n  // Our parent element can be arbitrary since tooltips are by default inserted as a sibling of their target element.\n  // So reset our font and text properties to avoid inheriting weird values.\n  @include reset-text();\n  @include font-size(var(--#{$prefix}tooltip-font-size));\n  // Allow breaking very long words so they don't overflow the tooltip's bounds\n  word-wrap: break-word;\n  opacity: 0;\n\n  &.show { opacity: var(--#{$prefix}tooltip-opacity); }\n\n  .tooltip-arrow {\n    display: block;\n    width: var(--#{$prefix}tooltip-arrow-width);\n    height: var(--#{$prefix}tooltip-arrow-height);\n\n    &::before {\n      position: absolute;\n      content: \"\";\n      border-color: transparent;\n      border-style: solid;\n    }\n  }\n}\n\n.bs-tooltip-top .tooltip-arrow {\n  bottom: calc(-1 * var(--#{$prefix}tooltip-arrow-height)); // stylelint-disable-line function-disallowed-list\n\n  &::before {\n    top: -1px;\n    border-width: var(--#{$prefix}tooltip-arrow-height) calc(var(--#{$prefix}tooltip-arrow-width) * .5) 0; // stylelint-disable-line function-disallowed-list\n    border-top-color: var(--#{$prefix}tooltip-bg);\n  }\n}\n\n/* rtl:begin:ignore */\n.bs-tooltip-end .tooltip-arrow {\n  left: calc(-1 * var(--#{$prefix}tooltip-arrow-height)); // stylelint-disable-line function-disallowed-list\n  width: var(--#{$prefix}tooltip-arrow-height);\n  height: var(--#{$prefix}tooltip-arrow-width);\n\n  &::before {\n    right: -1px;\n    border-width: calc(var(--#{$prefix}tooltip-arrow-width) * .5) var(--#{$prefix}tooltip-arrow-height) calc(var(--#{$prefix}tooltip-arrow-width) * .5) 0; // stylelint-disable-line function-disallowed-list\n    border-right-color: var(--#{$prefix}tooltip-bg);\n  }\n}\n\n/* rtl:end:ignore */\n\n.bs-tooltip-bottom .tooltip-arrow {\n  top: calc(-1 * var(--#{$prefix}tooltip-arrow-height)); // stylelint-disable-line function-disallowed-list\n\n  &::before {\n    bottom: -1px;\n    border-width: 0 calc(var(--#{$prefix}tooltip-arrow-width) * .5) var(--#{$prefix}tooltip-arrow-height); // stylelint-disable-line function-disallowed-list\n    border-bottom-color: var(--#{$prefix}tooltip-bg);\n  }\n}\n\n/* rtl:begin:ignore */\n.bs-tooltip-start .tooltip-arrow {\n  right: calc(-1 * var(--#{$prefix}tooltip-arrow-height)); // stylelint-disable-line function-disallowed-list\n  width: var(--#{$prefix}tooltip-arrow-height);\n  height: var(--#{$prefix}tooltip-arrow-width);\n\n  &::before {\n    left: -1px;\n    border-width: calc(var(--#{$prefix}tooltip-arrow-width) * .5) 0 calc(var(--#{$prefix}tooltip-arrow-width) * .5) var(--#{$prefix}tooltip-arrow-height); // stylelint-disable-line function-disallowed-list\n    border-left-color: var(--#{$prefix}tooltip-bg);\n  }\n}\n\n/* rtl:end:ignore */\n\n.bs-tooltip-auto {\n  &[data-popper-placement^=\"top\"] {\n    @extend .bs-tooltip-top;\n  }\n  &[data-popper-placement^=\"right\"] {\n    @extend .bs-tooltip-end;\n  }\n  &[data-popper-placement^=\"bottom\"] {\n    @extend .bs-tooltip-bottom;\n  }\n  &[data-popper-placement^=\"left\"] {\n    @extend .bs-tooltip-start;\n  }\n}\n\n// Wrapper for the tooltip content\n.tooltip-inner {\n  max-width: var(--#{$prefix}tooltip-max-width);\n  padding: var(--#{$prefix}tooltip-padding-y) var(--#{$prefix}tooltip-padding-x);\n  color: var(--#{$prefix}tooltip-color);\n  text-align: center;\n  background-color: var(--#{$prefix}tooltip-bg);\n  @include border-radius(var(--#{$prefix}tooltip-border-radius));\n}\n","@mixin reset-text {\n  font-family: $font-family-base;\n  // We deliberately do NOT reset font-size or overflow-wrap / word-wrap.\n  font-style: normal;\n  font-weight: $font-weight-normal;\n  line-height: $line-height-base;\n  text-align: left; // Fallback for where `start` is not supported\n  text-align: start;\n  text-decoration: none;\n  text-shadow: none;\n  text-transform: none;\n  letter-spacing: normal;\n  word-break: normal;\n  white-space: normal;\n  word-spacing: normal;\n  line-break: auto;\n}\n",".popover {\n  // scss-docs-start popover-css-vars\n  --#{$prefix}popover-zindex: #{$zindex-popover};\n  --#{$prefix}popover-max-width: #{$popover-max-width};\n  @include rfs($popover-font-size, --#{$prefix}popover-font-size);\n  --#{$prefix}popover-bg: #{$popover-bg};\n  --#{$prefix}popover-border-width: #{$popover-border-width};\n  --#{$prefix}popover-border-color: #{$popover-border-color};\n  --#{$prefix}popover-border-radius: #{$popover-border-radius};\n  --#{$prefix}popover-inner-border-radius: #{$popover-inner-border-radius};\n  --#{$prefix}popover-box-shadow: #{$popover-box-shadow};\n  --#{$prefix}popover-header-padding-x: #{$popover-header-padding-x};\n  --#{$prefix}popover-header-padding-y: #{$popover-header-padding-y};\n  @include rfs($popover-header-font-size, --#{$prefix}popover-header-font-size);\n  --#{$prefix}popover-header-color: #{$popover-header-color};\n  --#{$prefix}popover-header-bg: #{$popover-header-bg};\n  --#{$prefix}popover-body-padding-x: #{$popover-body-padding-x};\n  --#{$prefix}popover-body-padding-y: #{$popover-body-padding-y};\n  --#{$prefix}popover-body-color: #{$popover-body-color};\n  --#{$prefix}popover-arrow-width: #{$popover-arrow-width};\n  --#{$prefix}popover-arrow-height: #{$popover-arrow-height};\n  --#{$prefix}popover-arrow-border: var(--#{$prefix}popover-border-color);\n  // scss-docs-end popover-css-vars\n\n  z-index: var(--#{$prefix}popover-zindex);\n  display: block;\n  max-width: var(--#{$prefix}popover-max-width);\n  // Our parent element can be arbitrary since tooltips are by default inserted as a sibling of their target element.\n  // So reset our font and text properties to avoid inheriting weird values.\n  @include reset-text();\n  @include font-size(var(--#{$prefix}popover-font-size));\n  // Allow breaking very long words so they don't overflow the popover's bounds\n  word-wrap: break-word;\n  background-color: var(--#{$prefix}popover-bg);\n  background-clip: padding-box;\n  border: var(--#{$prefix}popover-border-width) solid var(--#{$prefix}popover-border-color);\n  @include border-radius(var(--#{$prefix}popover-border-radius));\n  @include box-shadow(var(--#{$prefix}popover-box-shadow));\n\n  .popover-arrow {\n    display: block;\n    width: var(--#{$prefix}popover-arrow-width);\n    height: var(--#{$prefix}popover-arrow-height);\n\n    &::before,\n    &::after {\n      position: absolute;\n      display: block;\n      content: \"\";\n      border-color: transparent;\n      border-style: solid;\n      border-width: 0;\n    }\n  }\n}\n\n.bs-popover-top {\n  > .popover-arrow {\n    bottom: calc(-1 * (var(--#{$prefix}popover-arrow-height)) - var(--#{$prefix}popover-border-width)); // stylelint-disable-line function-disallowed-list\n\n    &::before,\n    &::after {\n      border-width: var(--#{$prefix}popover-arrow-height) calc(var(--#{$prefix}popover-arrow-width) * .5) 0; // stylelint-disable-line function-disallowed-list\n    }\n\n    &::before {\n      bottom: 0;\n      border-top-color: var(--#{$prefix}popover-arrow-border);\n    }\n\n    &::after {\n      bottom: var(--#{$prefix}popover-border-width);\n      border-top-color: var(--#{$prefix}popover-bg);\n    }\n  }\n}\n\n/* rtl:begin:ignore */\n.bs-popover-end {\n  > .popover-arrow {\n    left: calc(-1 * (var(--#{$prefix}popover-arrow-height)) - var(--#{$prefix}popover-border-width)); // stylelint-disable-line function-disallowed-list\n    width: var(--#{$prefix}popover-arrow-height);\n    height: var(--#{$prefix}popover-arrow-width);\n\n    &::before,\n    &::after {\n      border-width: calc(var(--#{$prefix}popover-arrow-width) * .5) var(--#{$prefix}popover-arrow-height) calc(var(--#{$prefix}popover-arrow-width) * .5) 0; // stylelint-disable-line function-disallowed-list\n    }\n\n    &::before {\n      left: 0;\n      border-right-color: var(--#{$prefix}popover-arrow-border);\n    }\n\n    &::after {\n      left: var(--#{$prefix}popover-border-width);\n      border-right-color: var(--#{$prefix}popover-bg);\n    }\n  }\n}\n\n/* rtl:end:ignore */\n\n.bs-popover-bottom {\n  > .popover-arrow {\n    top: calc(-1 * (var(--#{$prefix}popover-arrow-height)) - var(--#{$prefix}popover-border-width)); // stylelint-disable-line function-disallowed-list\n\n    &::before,\n    &::after {\n      border-width: 0 calc(var(--#{$prefix}popover-arrow-width) * .5) var(--#{$prefix}popover-arrow-height); // stylelint-disable-line function-disallowed-list\n    }\n\n    &::before {\n      top: 0;\n      border-bottom-color: var(--#{$prefix}popover-arrow-border);\n    }\n\n    &::after {\n      top: var(--#{$prefix}popover-border-width);\n      border-bottom-color: var(--#{$prefix}popover-bg);\n    }\n  }\n\n  // This will remove the popover-header's border just below the arrow\n  .popover-header::before {\n    position: absolute;\n    top: 0;\n    left: 50%;\n    display: block;\n    width: var(--#{$prefix}popover-arrow-width);\n    margin-left: calc(-.5 * var(--#{$prefix}popover-arrow-width)); // stylelint-disable-line function-disallowed-list\n    content: \"\";\n    border-bottom: var(--#{$prefix}popover-border-width) solid var(--#{$prefix}popover-header-bg);\n  }\n}\n\n/* rtl:begin:ignore */\n.bs-popover-start {\n  > .popover-arrow {\n    right: calc(-1 * (var(--#{$prefix}popover-arrow-height)) - var(--#{$prefix}popover-border-width)); // stylelint-disable-line function-disallowed-list\n    width: var(--#{$prefix}popover-arrow-height);\n    height: var(--#{$prefix}popover-arrow-width);\n\n    &::before,\n    &::after {\n      border-width: calc(var(--#{$prefix}popover-arrow-width) * .5) 0 calc(var(--#{$prefix}popover-arrow-width) * .5) var(--#{$prefix}popover-arrow-height); // stylelint-disable-line function-disallowed-list\n    }\n\n    &::before {\n      right: 0;\n      border-left-color: var(--#{$prefix}popover-arrow-border);\n    }\n\n    &::after {\n      right: var(--#{$prefix}popover-border-width);\n      border-left-color: var(--#{$prefix}popover-bg);\n    }\n  }\n}\n\n/* rtl:end:ignore */\n\n.bs-popover-auto {\n  &[data-popper-placement^=\"top\"] {\n    @extend .bs-popover-top;\n  }\n  &[data-popper-placement^=\"right\"] {\n    @extend .bs-popover-end;\n  }\n  &[data-popper-placement^=\"bottom\"] {\n    @extend .bs-popover-bottom;\n  }\n  &[data-popper-placement^=\"left\"] {\n    @extend .bs-popover-start;\n  }\n}\n\n// Offset the popover to account for the popover arrow\n.popover-header {\n  padding: var(--#{$prefix}popover-header-padding-y) var(--#{$prefix}popover-header-padding-x);\n  margin-bottom: 0; // Reset the default from Reboot\n  @include font-size(var(--#{$prefix}popover-header-font-size));\n  color: var(--#{$prefix}popover-header-color);\n  background-color: var(--#{$prefix}popover-header-bg);\n  border-bottom: var(--#{$prefix}popover-border-width) solid var(--#{$prefix}popover-border-color);\n  @include border-top-radius(var(--#{$prefix}popover-inner-border-radius));\n\n  &:empty {\n    display: none;\n  }\n}\n\n.popover-body {\n  padding: var(--#{$prefix}popover-body-padding-y) var(--#{$prefix}popover-body-padding-x);\n  color: var(--#{$prefix}popover-body-color);\n}\n","// Notes on the classes:\n//\n// 1. .carousel.pointer-event should ideally be pan-y (to allow for users to scroll vertically)\n//    even when their scroll action started on a carousel, but for compatibility (with Firefox)\n//    we're preventing all actions instead\n// 2. The .carousel-item-start and .carousel-item-end is used to indicate where\n//    the active slide is heading.\n// 3. .active.carousel-item is the current slide.\n// 4. .active.carousel-item-start and .active.carousel-item-end is the current\n//    slide in its in-transition state. Only one of these occurs at a time.\n// 5. .carousel-item-next.carousel-item-start and .carousel-item-prev.carousel-item-end\n//    is the upcoming slide in transition.\n\n.carousel {\n  position: relative;\n}\n\n.carousel.pointer-event {\n  touch-action: pan-y;\n}\n\n.carousel-inner {\n  position: relative;\n  width: 100%;\n  overflow: hidden;\n  @include clearfix();\n}\n\n.carousel-item {\n  position: relative;\n  display: none;\n  float: left;\n  width: 100%;\n  margin-right: -100%;\n  backface-visibility: hidden;\n  @include transition($carousel-transition);\n}\n\n.carousel-item.active,\n.carousel-item-next,\n.carousel-item-prev {\n  display: block;\n}\n\n.carousel-item-next:not(.carousel-item-start),\n.active.carousel-item-end {\n  transform: translateX(100%);\n}\n\n.carousel-item-prev:not(.carousel-item-end),\n.active.carousel-item-start {\n  transform: translateX(-100%);\n}\n\n\n//\n// Alternate transitions\n//\n\n.carousel-fade {\n  .carousel-item {\n    opacity: 0;\n    transition-property: opacity;\n    transform: none;\n  }\n\n  .carousel-item.active,\n  .carousel-item-next.carousel-item-start,\n  .carousel-item-prev.carousel-item-end {\n    z-index: 1;\n    opacity: 1;\n  }\n\n  .active.carousel-item-start,\n  .active.carousel-item-end {\n    z-index: 0;\n    opacity: 0;\n    @include transition(opacity 0s $carousel-transition-duration);\n  }\n}\n\n\n//\n// Left/right controls for nav\n//\n\n.carousel-control-prev,\n.carousel-control-next {\n  position: absolute;\n  top: 0;\n  bottom: 0;\n  z-index: 1;\n  // Use flex for alignment (1-3)\n  display: flex; // 1. allow flex styles\n  align-items: center; // 2. vertically center contents\n  justify-content: center; // 3. horizontally center contents\n  width: $carousel-control-width;\n  padding: 0;\n  color: $carousel-control-color;\n  text-align: center;\n  background: none;\n  border: 0;\n  opacity: $carousel-control-opacity;\n  @include transition($carousel-control-transition);\n\n  // Hover/focus state\n  &:hover,\n  &:focus {\n    color: $carousel-control-color;\n    text-decoration: none;\n    outline: 0;\n    opacity: $carousel-control-hover-opacity;\n  }\n}\n.carousel-control-prev {\n  left: 0;\n  background-image: if($enable-gradients, linear-gradient(90deg, rgba($black, .25), rgba($black, .001)), null);\n}\n.carousel-control-next {\n  right: 0;\n  background-image: if($enable-gradients, linear-gradient(270deg, rgba($black, .25), rgba($black, .001)), null);\n}\n\n// Icons for within\n.carousel-control-prev-icon,\n.carousel-control-next-icon {\n  display: inline-block;\n  width: $carousel-control-icon-width;\n  height: $carousel-control-icon-width;\n  background-repeat: no-repeat;\n  background-position: 50%;\n  background-size: 100% 100%;\n}\n\n/* rtl:options: {\n  \"autoRename\": true,\n  \"stringMap\":[ {\n    \"name\"    : \"prev-next\",\n    \"search\"  : \"prev\",\n    \"replace\" : \"next\"\n  } ]\n} */\n.carousel-control-prev-icon {\n  background-image: escape-svg($carousel-control-prev-icon-bg);\n}\n.carousel-control-next-icon {\n  background-image: escape-svg($carousel-control-next-icon-bg);\n}\n\n// Optional indicator pips/controls\n//\n// Add a container (such as a list) with the following class and add an item (ideally a focusable control,\n// like a button) with data-bs-target for each slide your carousel holds.\n\n.carousel-indicators {\n  position: absolute;\n  right: 0;\n  bottom: 0;\n  left: 0;\n  z-index: 2;\n  display: flex;\n  justify-content: center;\n  padding: 0;\n  // Use the .carousel-control's width as margin so we don't overlay those\n  margin-right: $carousel-control-width;\n  margin-bottom: 1rem;\n  margin-left: $carousel-control-width;\n\n  [data-bs-target] {\n    box-sizing: content-box;\n    flex: 0 1 auto;\n    width: $carousel-indicator-width;\n    height: $carousel-indicator-height;\n    padding: 0;\n    margin-right: $carousel-indicator-spacer;\n    margin-left: $carousel-indicator-spacer;\n    text-indent: -999px;\n    cursor: pointer;\n    background-color: $carousel-indicator-active-bg;\n    background-clip: padding-box;\n    border: 0;\n    // Use transparent borders to increase the hit area by 10px on top and bottom.\n    border-top: $carousel-indicator-hit-area-height solid transparent;\n    border-bottom: $carousel-indicator-hit-area-height solid transparent;\n    opacity: $carousel-indicator-opacity;\n    @include transition($carousel-indicator-transition);\n  }\n\n  .active {\n    opacity: $carousel-indicator-active-opacity;\n  }\n}\n\n\n// Optional captions\n//\n//\n\n.carousel-caption {\n  position: absolute;\n  right: (100% - $carousel-caption-width) * .5;\n  bottom: $carousel-caption-spacer;\n  left: (100% - $carousel-caption-width) * .5;\n  padding-top: $carousel-caption-padding-y;\n  padding-bottom: $carousel-caption-padding-y;\n  color: $carousel-caption-color;\n  text-align: center;\n}\n\n// Dark mode carousel\n\n@mixin carousel-dark() {\n  .carousel-control-prev-icon,\n  .carousel-control-next-icon {\n    filter: $carousel-dark-control-icon-filter;\n  }\n\n  .carousel-indicators [data-bs-target] {\n    background-color: $carousel-dark-indicator-active-bg;\n  }\n\n  .carousel-caption {\n    color: $carousel-dark-caption-color;\n  }\n}\n\n.carousel-dark {\n  @include carousel-dark();\n}\n\n@if $enable-dark-mode {\n  @include color-mode(dark) {\n    @if $color-mode-type == \"media-query\" {\n      .carousel {\n        @include carousel-dark();\n      }\n    } @else {\n      .carousel,\n      &.carousel {\n        @include carousel-dark();\n      }\n    }\n  }\n}\n","// scss-docs-start clearfix\n@mixin clearfix() {\n  &::after {\n    display: block;\n    clear: both;\n    content: \"\";\n  }\n}\n// scss-docs-end clearfix\n","//\n// Rotating border\n//\n\n.spinner-grow,\n.spinner-border {\n  display: inline-block;\n  width: var(--#{$prefix}spinner-width);\n  height: var(--#{$prefix}spinner-height);\n  vertical-align: var(--#{$prefix}spinner-vertical-align);\n  // stylelint-disable-next-line property-disallowed-list\n  border-radius: 50%;\n  animation: var(--#{$prefix}spinner-animation-speed) linear infinite var(--#{$prefix}spinner-animation-name);\n}\n\n// scss-docs-start spinner-border-keyframes\n@keyframes spinner-border {\n  to { transform: rotate(360deg) #{\"/* rtl:ignore */\"}; }\n}\n// scss-docs-end spinner-border-keyframes\n\n.spinner-border {\n  // scss-docs-start spinner-border-css-vars\n  --#{$prefix}spinner-width: #{$spinner-width};\n  --#{$prefix}spinner-height: #{$spinner-height};\n  --#{$prefix}spinner-vertical-align: #{$spinner-vertical-align};\n  --#{$prefix}spinner-border-width: #{$spinner-border-width};\n  --#{$prefix}spinner-animation-speed: #{$spinner-animation-speed};\n  --#{$prefix}spinner-animation-name: spinner-border;\n  // scss-docs-end spinner-border-css-vars\n\n  border: var(--#{$prefix}spinner-border-width) solid currentcolor;\n  border-right-color: transparent;\n}\n\n.spinner-border-sm {\n  // scss-docs-start spinner-border-sm-css-vars\n  --#{$prefix}spinner-width: #{$spinner-width-sm};\n  --#{$prefix}spinner-height: #{$spinner-height-sm};\n  --#{$prefix}spinner-border-width: #{$spinner-border-width-sm};\n  // scss-docs-end spinner-border-sm-css-vars\n}\n\n//\n// Growing circle\n//\n\n// scss-docs-start spinner-grow-keyframes\n@keyframes spinner-grow {\n  0% {\n    transform: scale(0);\n  }\n  50% {\n    opacity: 1;\n    transform: none;\n  }\n}\n// scss-docs-end spinner-grow-keyframes\n\n.spinner-grow {\n  // scss-docs-start spinner-grow-css-vars\n  --#{$prefix}spinner-width: #{$spinner-width};\n  --#{$prefix}spinner-height: #{$spinner-height};\n  --#{$prefix}spinner-vertical-align: #{$spinner-vertical-align};\n  --#{$prefix}spinner-animation-speed: #{$spinner-animation-speed};\n  --#{$prefix}spinner-animation-name: spinner-grow;\n  // scss-docs-end spinner-grow-css-vars\n\n  background-color: currentcolor;\n  opacity: 0;\n}\n\n.spinner-grow-sm {\n  --#{$prefix}spinner-width: #{$spinner-width-sm};\n  --#{$prefix}spinner-height: #{$spinner-height-sm};\n}\n\n@if $enable-reduced-motion {\n  @media (prefers-reduced-motion: reduce) {\n    .spinner-border,\n    .spinner-grow {\n      --#{$prefix}spinner-animation-speed: #{$spinner-animation-speed * 2};\n    }\n  }\n}\n","// stylelint-disable function-disallowed-list\n\n%offcanvas-css-vars {\n  // scss-docs-start offcanvas-css-vars\n  --#{$prefix}offcanvas-zindex: #{$zindex-offcanvas};\n  --#{$prefix}offcanvas-width: #{$offcanvas-horizontal-width};\n  --#{$prefix}offcanvas-height: #{$offcanvas-vertical-height};\n  --#{$prefix}offcanvas-padding-x: #{$offcanvas-padding-x};\n  --#{$prefix}offcanvas-padding-y: #{$offcanvas-padding-y};\n  --#{$prefix}offcanvas-color: #{$offcanvas-color};\n  --#{$prefix}offcanvas-bg: #{$offcanvas-bg-color};\n  --#{$prefix}offcanvas-border-width: #{$offcanvas-border-width};\n  --#{$prefix}offcanvas-border-color: #{$offcanvas-border-color};\n  --#{$prefix}offcanvas-box-shadow: #{$offcanvas-box-shadow};\n  --#{$prefix}offcanvas-transition: #{transform $offcanvas-transition-duration ease-in-out};\n  --#{$prefix}offcanvas-title-line-height: #{$offcanvas-title-line-height};\n  // scss-docs-end offcanvas-css-vars\n}\n\n@each $breakpoint in map-keys($grid-breakpoints) {\n  $next: breakpoint-next($breakpoint, $grid-breakpoints);\n  $infix: breakpoint-infix($next, $grid-breakpoints);\n\n  .offcanvas#{$infix} {\n    @extend %offcanvas-css-vars;\n  }\n}\n\n@each $breakpoint in map-keys($grid-breakpoints) {\n  $next: breakpoint-next($breakpoint, $grid-breakpoints);\n  $infix: breakpoint-infix($next, $grid-breakpoints);\n\n  .offcanvas#{$infix} {\n    @include media-breakpoint-down($next) {\n      position: fixed;\n      bottom: 0;\n      z-index: var(--#{$prefix}offcanvas-zindex);\n      display: flex;\n      flex-direction: column;\n      max-width: 100%;\n      color: var(--#{$prefix}offcanvas-color);\n      visibility: hidden;\n      background-color: var(--#{$prefix}offcanvas-bg);\n      background-clip: padding-box;\n      outline: 0;\n      @include box-shadow(var(--#{$prefix}offcanvas-box-shadow));\n      @include transition(var(--#{$prefix}offcanvas-transition));\n\n      &.offcanvas-start {\n        top: 0;\n        left: 0;\n        width: var(--#{$prefix}offcanvas-width);\n        border-right: var(--#{$prefix}offcanvas-border-width) solid var(--#{$prefix}offcanvas-border-color);\n        transform: translateX(-100%);\n      }\n\n      &.offcanvas-end {\n        top: 0;\n        right: 0;\n        width: var(--#{$prefix}offcanvas-width);\n        border-left: var(--#{$prefix}offcanvas-border-width) solid var(--#{$prefix}offcanvas-border-color);\n        transform: translateX(100%);\n      }\n\n      &.offcanvas-top {\n        top: 0;\n        right: 0;\n        left: 0;\n        height: var(--#{$prefix}offcanvas-height);\n        max-height: 100%;\n        border-bottom: var(--#{$prefix}offcanvas-border-width) solid var(--#{$prefix}offcanvas-border-color);\n        transform: translateY(-100%);\n      }\n\n      &.offcanvas-bottom {\n        right: 0;\n        left: 0;\n        height: var(--#{$prefix}offcanvas-height);\n        max-height: 100%;\n        border-top: var(--#{$prefix}offcanvas-border-width) solid var(--#{$prefix}offcanvas-border-color);\n        transform: translateY(100%);\n      }\n\n      &.showing,\n      &.show:not(.hiding) {\n        transform: none;\n      }\n\n      &.showing,\n      &.hiding,\n      &.show {\n        visibility: visible;\n      }\n    }\n\n    @if not ($infix == \"\") {\n      @include media-breakpoint-up($next) {\n        --#{$prefix}offcanvas-height: auto;\n        --#{$prefix}offcanvas-border-width: 0;\n        background-color: transparent !important; // stylelint-disable-line declaration-no-important\n\n        .offcanvas-header {\n          display: none;\n        }\n\n        .offcanvas-body {\n          display: flex;\n          flex-grow: 0;\n          padding: 0;\n          overflow-y: visible;\n          // Reset `background-color` in case `.bg-*` classes are used in offcanvas\n          background-color: transparent !important; // stylelint-disable-line declaration-no-important\n        }\n      }\n    }\n  }\n}\n\n.offcanvas-backdrop {\n  @include overlay-backdrop($zindex-offcanvas-backdrop, $offcanvas-backdrop-bg, $offcanvas-backdrop-opacity);\n}\n\n.offcanvas-header {\n  display: flex;\n  align-items: center;\n  justify-content: space-between;\n  padding: var(--#{$prefix}offcanvas-padding-y) var(--#{$prefix}offcanvas-padding-x);\n\n  .btn-close {\n    padding: calc(var(--#{$prefix}offcanvas-padding-y) * .5) calc(var(--#{$prefix}offcanvas-padding-x) * .5);\n    margin-top: calc(-.5 * var(--#{$prefix}offcanvas-padding-y));\n    margin-right: calc(-.5 * var(--#{$prefix}offcanvas-padding-x));\n    margin-bottom: calc(-.5 * var(--#{$prefix}offcanvas-padding-y));\n  }\n}\n\n.offcanvas-title {\n  margin-bottom: 0;\n  line-height: var(--#{$prefix}offcanvas-title-line-height);\n}\n\n.offcanvas-body {\n  flex-grow: 1;\n  padding: var(--#{$prefix}offcanvas-padding-y) var(--#{$prefix}offcanvas-padding-x);\n  overflow-y: auto;\n}\n",".placeholder {\n  display: inline-block;\n  min-height: 1em;\n  vertical-align: middle;\n  cursor: wait;\n  background-color: currentcolor;\n  opacity: $placeholder-opacity-max;\n\n  &.btn::before {\n    display: inline-block;\n    content: \"\";\n  }\n}\n\n// Sizing\n.placeholder-xs {\n  min-height: .6em;\n}\n\n.placeholder-sm {\n  min-height: .8em;\n}\n\n.placeholder-lg {\n  min-height: 1.2em;\n}\n\n// Animation\n.placeholder-glow {\n  .placeholder {\n    animation: placeholder-glow 2s ease-in-out infinite;\n  }\n}\n\n@keyframes placeholder-glow {\n  50% {\n    opacity: $placeholder-opacity-min;\n  }\n}\n\n.placeholder-wave {\n  mask-image: linear-gradient(130deg, $black 55%, rgba(0, 0, 0, (1 - $placeholder-opacity-min)) 75%, $black 95%);\n  mask-size: 200% 100%;\n  animation: placeholder-wave 2s linear infinite;\n}\n\n@keyframes placeholder-wave {\n  100% {\n    mask-position: -200% 0%;\n  }\n}\n","// All-caps `RGBA()` function used because of this Sass bug: https://github.com/sass/node-sass/issues/2251\n@each $color, $value in $theme-colors {\n  .text-bg-#{$color} {\n    color: color-contrast($value) if($enable-important-utilities, !important, null);\n    background-color: RGBA(var(--#{$prefix}#{$color}-rgb), var(--#{$prefix}bg-opacity, 1)) if($enable-important-utilities, !important, null);\n  }\n}\n","// All-caps `RGBA()` function used because of this Sass bug: https://github.com/sass/node-sass/issues/2251\n@each $color, $value in $theme-colors {\n  .link-#{$color} {\n    color: RGBA(var(--#{$prefix}#{$color}-rgb), var(--#{$prefix}link-opacity, 1)) if($enable-important-utilities, !important, null);\n    text-decoration-color: RGBA(var(--#{$prefix}#{$color}-rgb), var(--#{$prefix}link-underline-opacity, 1)) if($enable-important-utilities, !important, null);\n\n    @if $link-shade-percentage != 0 {\n      &:hover,\n      &:focus {\n        $hover-color: if(color-contrast($value) == $color-contrast-light, shade-color($value, $link-shade-percentage), tint-color($value, $link-shade-percentage));\n        color: RGBA(#{to-rgb($hover-color)}, var(--#{$prefix}link-opacity, 1)) if($enable-important-utilities, !important, null);\n        text-decoration-color: RGBA(to-rgb($hover-color), var(--#{$prefix}link-underline-opacity, 1)) if($enable-important-utilities, !important, null);\n      }\n    }\n  }\n}\n\n// One-off special link helper as a bridge until v6\n.link-body-emphasis {\n  color: RGBA(var(--#{$prefix}emphasis-color-rgb), var(--#{$prefix}link-opacity, 1)) if($enable-important-utilities, !important, null);\n  text-decoration-color: RGBA(var(--#{$prefix}emphasis-color-rgb), var(--#{$prefix}link-underline-opacity, 1)) if($enable-important-utilities, !important, null);\n\n  @if $link-shade-percentage != 0 {\n    &:hover,\n    &:focus {\n      color: RGBA(var(--#{$prefix}emphasis-color-rgb), var(--#{$prefix}link-opacity, .75)) if($enable-important-utilities, !important, null);\n      text-decoration-color: RGBA(var(--#{$prefix}emphasis-color-rgb), var(--#{$prefix}link-underline-opacity, .75)) if($enable-important-utilities, !important, null);\n    }\n  }\n}\n",".focus-ring:focus {\n  outline: 0;\n  // By default, there is no `--bs-focus-ring-x`, `--bs-focus-ring-y`, or `--bs-focus-ring-blur`, but we provide CSS variables with fallbacks to initial `0` values\n  box-shadow: var(--#{$prefix}focus-ring-x, 0) var(--#{$prefix}focus-ring-y, 0) var(--#{$prefix}focus-ring-blur, 0) var(--#{$prefix}focus-ring-width) var(--#{$prefix}focus-ring-color);\n}\n",".icon-link {\n  display: inline-flex;\n  gap: $icon-link-gap;\n  align-items: center;\n  text-decoration-color: rgba(var(--#{$prefix}link-color-rgb), var(--#{$prefix}link-opacity, .5));\n  text-underline-offset: $icon-link-underline-offset;\n  backface-visibility: hidden;\n\n  > .bi {\n    flex-shrink: 0;\n    width: $icon-link-icon-size;\n    height: $icon-link-icon-size;\n    fill: currentcolor;\n    @include transition($icon-link-icon-transition);\n  }\n}\n\n.icon-link-hover {\n  &:hover,\n  &:focus-visible {\n    > .bi {\n      transform: var(--#{$prefix}icon-link-transform, $icon-link-icon-transform);\n    }\n  }\n}\n","// Credit: Nicolas Gallagher and SUIT CSS.\n\n.ratio {\n  position: relative;\n  width: 100%;\n\n  &::before {\n    display: block;\n    padding-top: var(--#{$prefix}aspect-ratio);\n    content: \"\";\n  }\n\n  > * {\n    position: absolute;\n    top: 0;\n    left: 0;\n    width: 100%;\n    height: 100%;\n  }\n}\n\n@each $key, $ratio in $aspect-ratios {\n  .ratio-#{$key} {\n    --#{$prefix}aspect-ratio: #{$ratio};\n  }\n}\n","// Shorthand\n\n.fixed-top {\n  position: fixed;\n  top: 0;\n  right: 0;\n  left: 0;\n  z-index: $zindex-fixed;\n}\n\n.fixed-bottom {\n  position: fixed;\n  right: 0;\n  bottom: 0;\n  left: 0;\n  z-index: $zindex-fixed;\n}\n\n// Responsive sticky top and bottom\n@each $breakpoint in map-keys($grid-breakpoints) {\n  @include media-breakpoint-up($breakpoint) {\n    $infix: breakpoint-infix($breakpoint, $grid-breakpoints);\n\n    .sticky#{$infix}-top {\n      position: sticky;\n      top: 0;\n      z-index: $zindex-sticky;\n    }\n\n    .sticky#{$infix}-bottom {\n      position: sticky;\n      bottom: 0;\n      z-index: $zindex-sticky;\n    }\n  }\n}\n","// scss-docs-start stacks\n.hstack {\n  display: flex;\n  flex-direction: row;\n  align-items: center;\n  align-self: stretch;\n}\n\n.vstack {\n  display: flex;\n  flex: 1 1 auto;\n  flex-direction: column;\n  align-self: stretch;\n}\n// scss-docs-end stacks\n","//\n// Visually hidden\n//\n\n.visually-hidden,\n.visually-hidden-focusable:not(:focus):not(:focus-within) {\n  @include visually-hidden();\n}\n","// stylelint-disable declaration-no-important\n\n// Hide content visually while keeping it accessible to assistive technologies\n//\n// See: https://www.a11yproject.com/posts/2013-01-11-how-to-hide-content/\n// See: https://kittygiraudel.com/2016/10/13/css-hide-and-seek/\n\n@mixin visually-hidden() {\n  width: 1px !important;\n  height: 1px !important;\n  padding: 0 !important;\n  margin: -1px !important; // Fix for https://github.com/twbs/bootstrap/issues/25686\n  overflow: hidden !important;\n  clip: rect(0, 0, 0, 0) !important;\n  white-space: nowrap !important;\n  border: 0 !important;\n\n  // Fix for positioned table caption that could become anonymous cells\n  &:not(caption) {\n    position: absolute !important;\n  }\n}\n\n// Use to only display content when it's focused, or one of its child elements is focused\n// (i.e. when focus is within the element/container that the class was applied to)\n//\n// Useful for \"Skip to main content\" links; see https://www.w3.org/TR/2013/NOTE-WCAG20-TECHS-20130905/G1\n\n@mixin visually-hidden-focusable() {\n  &:not(:focus):not(:focus-within) {\n    @include visually-hidden();\n  }\n}\n","//\n// Stretched link\n//\n\n.stretched-link {\n  &::#{$stretched-link-pseudo-element} {\n    position: absolute;\n    top: 0;\n    right: 0;\n    bottom: 0;\n    left: 0;\n    z-index: $stretched-link-z-index;\n    content: \"\";\n  }\n}\n","//\n// Text truncation\n//\n\n.text-truncate {\n  @include text-truncate();\n}\n","// Text truncate\n// Requires inline-block or block for proper styling\n\n@mixin text-truncate() {\n  overflow: hidden;\n  text-overflow: ellipsis;\n  white-space: nowrap;\n}\n",".vr {\n  display: inline-block;\n  align-self: stretch;\n  width: $vr-border-width;\n  min-height: 1em;\n  background-color: currentcolor;\n  opacity: $hr-opacity;\n}\n","// Utility generator\n// Used to generate utilities & print utilities\n@mixin generate-utility($utility, $infix: \"\", $is-rfs-media-query: false) {\n  $values: map-get($utility, values);\n\n  // If the values are a list or string, convert it into a map\n  @if type-of($values) == \"string\" or type-of(nth($values, 1)) != \"list\" {\n    $values: zip($values, $values);\n  }\n\n  @each $key, $value in $values {\n    $properties: map-get($utility, property);\n\n    // Multiple properties are possible, for example with vertical or horizontal margins or paddings\n    @if type-of($properties) == \"string\" {\n      $properties: append((), $properties);\n    }\n\n    // Use custom class if present\n    $property-class: if(map-has-key($utility, class), map-get($utility, class), nth($properties, 1));\n    $property-class: if($property-class == null, \"\", $property-class);\n\n    // Use custom CSS variable name if present, otherwise default to `class`\n    $css-variable-name: if(map-has-key($utility, css-variable-name), map-get($utility, css-variable-name), map-get($utility, class));\n\n    // State params to generate pseudo-classes\n    $state: if(map-has-key($utility, state), map-get($utility, state), ());\n\n    $infix: if($property-class == \"\" and str-slice($infix, 1, 1) == \"-\", str-slice($infix, 2), $infix);\n\n    // Don't prefix if value key is null (e.g. with shadow class)\n    $property-class-modifier: if($key, if($property-class == \"\" and $infix == \"\", \"\", \"-\") + $key, \"\");\n\n    @if map-get($utility, rfs) {\n      // Inside the media query\n      @if $is-rfs-media-query {\n        $val: rfs-value($value);\n\n        // Do not render anything if fluid and non fluid values are the same\n        $value: if($val == rfs-fluid-value($value), null, $val);\n      }\n      @else {\n        $value: rfs-fluid-value($value);\n      }\n    }\n\n    $is-css-var: map-get($utility, css-var);\n    $is-local-vars: map-get($utility, local-vars);\n    $is-rtl: map-get($utility, rtl);\n\n    @if $value != null {\n      @if $is-rtl == false {\n        /* rtl:begin:remove */\n      }\n\n      @if $is-css-var {\n        .#{$property-class + $infix + $property-class-modifier} {\n          --#{$prefix}#{$css-variable-name}: #{$value};\n        }\n\n        @each $pseudo in $state {\n          .#{$property-class + $infix + $property-class-modifier}-#{$pseudo}:#{$pseudo} {\n            --#{$prefix}#{$css-variable-name}: #{$value};\n          }\n        }\n      } @else {\n        .#{$property-class + $infix + $property-class-modifier} {\n          @each $property in $properties {\n            @if $is-local-vars {\n              @each $local-var, $variable in $is-local-vars {\n                --#{$prefix}#{$local-var}: #{$variable};\n              }\n            }\n            #{$property}: $value if($enable-important-utilities, !important, null);\n          }\n        }\n\n        @each $pseudo in $state {\n          .#{$property-class + $infix + $property-class-modifier}-#{$pseudo}:#{$pseudo} {\n            @each $property in $properties {\n              @if $is-local-vars {\n                @each $local-var, $variable in $is-local-vars {\n                  --#{$prefix}#{$local-var}: #{$variable};\n                }\n              }\n              #{$property}: $value if($enable-important-utilities, !important, null);\n            }\n          }\n        }\n      }\n\n      @if $is-rtl == false {\n        /* rtl:end:remove */\n      }\n    }\n  }\n}\n","// Loop over each breakpoint\n@each $breakpoint in map-keys($grid-breakpoints) {\n\n  // Generate media query if needed\n  @include media-breakpoint-up($breakpoint) {\n    $infix: breakpoint-infix($breakpoint, $grid-breakpoints);\n\n    // Loop over each utility property\n    @each $key, $utility in $utilities {\n      // The utility can be disabled with `false`, thus check if the utility is a map first\n      // Only proceed if responsive media queries are enabled or if it's the base media query\n      @if type-of($utility) == \"map\" and (map-get($utility, responsive) or $infix == \"\") {\n        @include generate-utility($utility, $infix);\n      }\n    }\n  }\n}\n\n// RFS rescaling\n@media (min-width: $rfs-mq-value) {\n  @each $breakpoint in map-keys($grid-breakpoints) {\n    $infix: breakpoint-infix($breakpoint, $grid-breakpoints);\n\n    @if (map-get($grid-breakpoints, $breakpoint) < $rfs-breakpoint) {\n      // Loop over each utility property\n      @each $key, $utility in $utilities {\n        // The utility can be disabled with `false`, thus check if the utility is a map first\n        // Only proceed if responsive media queries are enabled or if it's the base media query\n        @if type-of($utility) == \"map\" and map-get($utility, rfs) and (map-get($utility, responsive) or $infix == \"\") {\n          @include generate-utility($utility, $infix, true);\n        }\n      }\n    }\n  }\n}\n\n\n// Print utilities\n@media print {\n  @each $key, $utility in $utilities {\n    // The utility can be disabled with `false`, thus check if the utility is a map first\n    // Then check if the utility needs print styles\n    @if type-of($utility) == \"map\" and map-get($utility, print) == true {\n      @include generate-utility($utility, \"-print\");\n    }\n  }\n}\n"],"names":[],"sourceRoot":""}
\ No newline at end of file
diff --git a/_static/styles/pydata-sphinx-theme.css b/_static/styles/pydata-sphinx-theme.css
new file mode 100644
index 0000000..b81ac47
--- /dev/null
+++ b/_static/styles/pydata-sphinx-theme.css
@@ -0,0 +1,2 @@
+html{--pst-header-height:4rem;--pst-header-article-height:calc(var(--pst-header-height)*2/3);--pst-sidebar-secondary:17rem;--pst-font-size-base:1rem;--pst-font-size-h1:2.5rem;--pst-font-size-h2:2rem;--pst-font-size-h3:1.75rem;--pst-font-size-h4:1.5rem;--pst-font-size-h5:1.25rem;--pst-font-size-h6:1.1rem;--pst-font-size-milli:0.9rem;--pst-sidebar-font-size:0.9rem;--pst-sidebar-font-size-mobile:1.1rem;--pst-sidebar-header-font-size:1.2rem;--pst-sidebar-header-font-weight:600;--pst-admonition-font-weight-heading:600;--pst-font-weight-caption:300;--pst-font-weight-heading:400;--pst-font-family-base-system:-apple-system,BlinkMacSystemFont,Segoe UI,"Helvetica Neue",Arial,sans-serif,Apple Color Emoji,Segoe UI Emoji,Segoe UI Symbol;--pst-font-family-monospace-system:"SFMono-Regular",Menlo,Consolas,Monaco,Liberation Mono,Lucida 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+ 1rem)}body{background-color:var(--pst-color-background);color:var(--pst-color-text-base);display:flex;flex-direction:column;font-family:var(--pst-font-family-base);font-weight:400;line-height:1.65;min-height:100vh}body::-webkit-scrollbar-track{background:var(--pst-color-background)}p{color:var(--pst-color-text-base);font-size:1em;margin-bottom:1.15rem}p.rubric{border-bottom:1px solid var(--pst-color-border)}p.centered{text-align:center}a{word-wrap:break-word;color:var(--pst-color-link);text-decoration:underline;text-decoration-thickness:max(1px,.0625rem);text-underline-offset:.1578em}a:hover{text-decoration-skip:none;color:var(--pst-color-link-hover);text-decoration-skip-ink:none;text-decoration-thickness:max(3px,.1875rem,.12em)}a:active,a:visited{color:var(--pst-color-link)}a:visited:hover{color:var(--pst-color-link-hover)}a:focus-visible{outline:2px solid var(--pst-color-accent)}a.headerlink{color:var(--pst-color-secondary);font-size:.8em;margin-left:.2em;opacity:.7;padding:0 4px;text-decoration:none;transition:all .2s ease-out;user-select:none}a.headerlink:hover{opacity:1}a.github:before,a.gitlab:before{color:var(--pst-color-text-muted);font:var(--fa-font-brands);margin-right:.25rem}a.github:before{content:var(--pst-icon-github)}a.gitlab:before{content:var(--pst-icon-gitlab)}.heading-style,h1,h2,h3,h4,h5,h6{font-family:var(--pst-font-family-heading);font-weight:var(--pst-font-weight-heading);line-height:1.15;margin:2.75rem 0 1.05rem}h1{font-size:var(--pst-font-size-h1);margin-top:0}h1,h2{color:var(--pst-heading-color)}h2{font-size:var(--pst-font-size-h2)}h3{font-size:var(--pst-font-size-h3)}h3,h4{color:var(--pst-heading-color)}h4{font-size:var(--pst-font-size-h4)}h5{font-size:var(--pst-font-size-h5)}h5,h6{color:var(--pst-color-text-base)}h6{font-size:var(--pst-font-size-h6)}.text_small,small{font-size:var(--pst-font-size-milli)}hr{border:0;border-top:1px solid 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.bd-footer__inner{display:flex;flex-grow:1;margin:auto;padding:1rem}.bd-footer .footer-items__center,.bd-footer .footer-items__end,.bd-footer .footer-items__start{display:flex;flex-direction:column;flex-grow:1;gap:.5rem;justify-content:center}.bd-footer .footer-items__center{text-align:center}.bd-footer .footer-items__end{text-align:end}.bd-footer .footer-item p{margin-bottom:0}.bd-footer-article{margin-top:auto}.bd-footer-article .footer-article-items{display:flex;flex-direction:column}.bd-footer-content .footer-content-items{display:flex;flex-direction:column;margin-top:auto}.bd-header{background:var(--pst-color-on-background)!important;box-shadow:0 .125rem .25rem 0 var(--pst-color-shadow);justify-content:center;max-width:100vw;padding:0;position:sticky;top:0;width:100%;z-index:1030}.bd-header .bd-header__inner{align-items:center;display:flex;height:fit-content;padding-left:1rem;padding-right:1rem}.bd-header .navbar-item{align-items:center;display:flex;height:var(--pst-header-height);max-height:var(--pst-header-height)}.bd-header .navbar-header-items{flex-shrink:1}@media(min-width:960px){.bd-header .navbar-header-items{display:flex;flex-grow:1;padding:0 0 0 .5rem}}.bd-header .navbar-header-items__center,.bd-header .navbar-header-items__end,.bd-header .navbar-header-items__start{align-items:center;display:flex;flex-flow:wrap;row-gap:0}.bd-header .navbar-header-items__center,.bd-header .navbar-header-items__end{column-gap:1rem}.bd-header .navbar-header-items__start{flex-shrink:0;gap:.5rem;margin-right:auto}.bd-header .navbar-header-items__end{justify-content:end}.bd-header .navbar-nav{display:flex}@media(min-width:960px){.bd-header .navbar-nav{align-items:center}}.bd-header .navbar-nav li a.nav-link{color:var(--pst-color-text-muted);text-decoration:none}.bd-header .navbar-nav li 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details.toggle-details summary{border-left:3px solid var(--pst-color-primary)}html div.rendered_html html .jp-RenderedHTMLCommon table{table-layout:auto}html[data-theme=dark] .bd-content .nboutput .output_area.rendered_html{color:var(--pst-color-on-background);background-color:var(--pst-color-text-base);border-radius:.25rem;padding:.5rem}html[data-theme=dark] .bd-content .nboutput .output_area.stderr{background:var(--pst-color-danger)}div.nblast.container{margin-bottom:1rem}div.cell_output .output{max-width:100%;overflow-x:auto}html[data-theme=dark] .bd-content div.cell_output img,html[data-theme=dark] .bd-content div.cell_output .text_html{color:var(--pst-color-on-background);background-color:var(--pst-color-text-base);border-radius:.25rem;padding:.5rem}.bd-content div.cell_input{display:flex;flex-direction:column;justify-content:stretch}.bd-content div.cell_input,.bd-content div.output{border-radius:.25rem}.bd-content div.output table{table-layout:auto}html[data-theme=dark] .bd-content img.leaflet-tile.leaflet-tile-loaded{border-radius:0;padding:0}.bd-search-container div#search-results>h2{font-size:var(--pst-font-size-icon);margin-top:0}.bd-search-container div#search-results p.search-summary{color:var(--pst-color-text-muted)}.bd-search-container ul.search{margin:0;list-style:none}.bd-search-container ul.search li{background-image:none;padding:1rem 0;margin:1rem 0;border-top:1px solid var(--pst-color-text-muted)}.bd-search-container ul.search li>a{font-size:1.2em}.bd-search-container ul.search li div.context,.bd-search-container ul.search li p.context{color:var(--pst-color-text-base);margin:.5em 0 0 0}.bd-search-container ul.search li div.context a:before,.bd-search-container ul.search li p.context a:before{content:\"#\";padding-right:.2em;color:var(--pst-color-text-muted)}","html {\n  /*****************************************************************************\n  * Overall Layout Variables\n  */\n\n  // Header height will impact the top offset for many sections\n  // Article header is 66% of Header\n  --pst-header-height: 4rem;\n  --pst-header-article-height: calc(var(--pst-header-height) * 2 / 3);\n  --pst-sidebar-secondary: 17rem;\n}\n\n/*******************************************************************************\n* Breakpoints that trigger UI changes\n*\n* Note that media-breakpoint-down begins at the next highest level!\n* So we should choose a media-breakpoint-down one *lower* than when we want to start\n* example: media-breakpoint-up(md) and media-breakpoint-down(sm) trigger at the same time\n* ref: https://github.com/twbs/bootstrap/issues/31214\n*/\n$breakpoint-sidebar-primary: lg; // When we collapse the primary sidebar\n$breakpoint-sidebar-secondary: xl; // When we collapse the secondary sidebar\n$breakpoint-page-width: 88rem; // taken from sphinx-basic-ng, which we are ultimately going to inherit\n\n/*******************************************************************************\n* Define the animation behaviour\n*/\n$animation-time: 200ms;\n\n/*******************************************************************************\n* UI shaping and padding\n*/\n$admonition-border-radius: 0.25rem;\n","html {\n  /*****************************************************************************\n  * Font features used in this theme\n  */\n\n  // base font size - applied at body/html level\n  --pst-font-size-base: 1rem;\n\n  // heading font sizes based on bootstrap sizing\n  --pst-font-size-h1: 2.5rem;\n  --pst-font-size-h2: 2rem;\n  --pst-font-size-h3: 1.75rem;\n  --pst-font-size-h4: 1.5rem;\n  --pst-font-size-h5: 1.25rem;\n  --pst-font-size-h6: 1.1rem;\n\n  // smaller than heading font sizes\n  --pst-font-size-milli: 0.9rem;\n\n  // Sidebar styles\n  --pst-sidebar-font-size: 0.9rem;\n  --pst-sidebar-font-size-mobile: 1.1rem;\n  --pst-sidebar-header-font-size: 1.2rem;\n  --pst-sidebar-header-font-weight: 600;\n\n  // Admonition styles\n  --pst-admonition-font-weight-heading: 600;\n\n  // Font weights\n  --pst-font-weight-caption: 300;\n  --pst-font-weight-heading: 400;\n\n  // Font family\n  // These are adapted from https://systemfontstack.com/ */\n  --pst-font-family-base-system: -apple-system, BlinkMacSystemFont, Segoe UI,\n    \"Helvetica Neue\", Arial, sans-serif, Apple Color Emoji, Segoe UI Emoji,\n    Segoe UI Symbol;\n  --pst-font-family-monospace-system: \"SFMono-Regular\", Menlo, Consolas, Monaco,\n    Liberation Mono, Lucida Console, monospace;\n\n  --pst-font-family-base: var(--pst-font-family-base-system);\n  --pst-font-family-heading: var(--pst-font-family-base-system);\n  --pst-font-family-monospace: var(--pst-font-family-monospace-system);\n}\n","html {\n  /*****************************************************************************\n  * Icon\n  */\n\n  // Font size across all icons\n  --pst-font-size-icon: 1.5rem;\n\n  // Font Awesome default icons\n  --pst-icon-check-circle: \"\\f058\"; // fa-solid fa-circle-check\n  --pst-icon-info-circle: \"\\f05a\"; // fa-solid fa-circle-info\n  --pst-icon-exclamation-triangle: \"\\f071\"; // fa-solid fa-triangle-exclamation\n  --pst-icon-exclamation-circle: \"\\f06a\"; // fa-solid fa-circle-exclamation\n  --pst-icon-times-circle: \"\\f057\"; // fa-solid fa-circle-xmark\n  --pst-icon-lightbulb: \"\\f0eb\"; // fa-solid fa-lightbulb\n  --pst-icon-download: \"\\f019\"; // fa-solid fa-download\n  --pst-icon-angle-left: \"\\f104\"; // fa-solid fa-angle-left\n  --pst-icon-angle-right: \"\\f105\"; // fa-solid fa-angle-right\n  --pst-icon-external-link: \"\\f35d\"; // fa-solid fa-up-right-from-square\n  --pst-icon-search-minus: \"\\f010\"; // fa-solid fa-magnifying-glass-minus\n  --pst-icon-github: \"\\f09b\"; // fa-brands fa-github\n  --pst-icon-gitlab: \"\\f296\"; // fa-brands fa-gitlab\n  --pst-icon-share: \"\\f064\"; // fa-solid fa-share\n  --pst-icon-bell: \"\\f0f3\"; // fa-solid fa-bell\n  --pst-icon-pencil: \"\\f303\"; // fa-solid fa-pencil\n\n  // Bootstrap icons\n  --pst-breadcrumb-divider: \"\\f105\";\n}\n","html {\n  /*****************************************************************************\n  * Admonitions\n  **/\n\n  --pst-icon-admonition-default: var(--pst-icon-bell);\n  --pst-icon-admonition-note: var(--pst-icon-info-circle);\n  --pst-icon-admonition-attention: var(--pst-icon-exclamation-circle);\n  --pst-icon-admonition-caution: var(--pst-icon-exclamation-triangle);\n  --pst-icon-admonition-warning: var(--pst-icon-exclamation-triangle);\n  --pst-icon-admonition-danger: var(--pst-icon-exclamation-triangle);\n  --pst-icon-admonition-error: var(--pst-icon-times-circle);\n  --pst-icon-admonition-hint: var(--pst-icon-lightbulb);\n  --pst-icon-admonition-tip: var(--pst-icon-lightbulb);\n  --pst-icon-admonition-important: var(--pst-icon-exclamation-circle);\n  --pst-icon-admonition-seealso: var(--pst-icon-share);\n  --pst-icon-admonition-todo: var(--pst-icon-pencil);\n}\n","html {\n  /*****************************************************************************\n  * versionmodified\n  **/\n\n  --pst-icon-versionmodified-default: var(--pst-icon-exclamation-circle);\n  --pst-icon-versionmodified-added: var(--pst-icon-exclamation-circle);\n  --pst-icon-versionmodified-changed: var(--pst-icon-exclamation-circle);\n  --pst-icon-versionmodified-deprecated: var(--pst-icon-exclamation-circle);\n}\n","html {\n  font-size: var(--pst-font-size-base);\n  scroll-padding-top: calc(var(--pst-header-height) + 1rem);\n}\n\nbody {\n  background-color: var(--pst-color-background);\n  font-family: var(--pst-font-family-base);\n  font-weight: 400;\n  line-height: 1.65;\n  color: var(--pst-color-text-base);\n  min-height: 100vh;\n  display: flex;\n  flex-direction: column;\n\n  // hack to avoid the black background on some browser including Safari\n  &::-webkit-scrollbar-track {\n    background: var(--pst-color-background);\n  }\n}\n\np {\n  margin-bottom: 1.15rem;\n  font-size: 1em;\n  color: var(--pst-color-text-base);\n\n  /* section header in docstring pages */\n  &.rubric {\n    border-bottom: 1px solid var(--pst-color-border);\n  }\n\n  &.centered {\n    text-align: center;\n  }\n}\n\na {\n  @include link-style-default;\n\n  // The # anchor that appears on hover over headings\n  &.headerlink {\n    color: var(--pst-color-secondary);\n    opacity: 0.7;\n    font-size: 0.8em;\n    padding: 0 4px 0 4px;\n    margin-left: 0.2em;\n    text-decoration: none;\n    transition: all 0.2s ease-out;\n    user-select: none;\n\n    &:hover {\n      opacity: 1;\n    }\n  }\n\n  // set up a icon next to the shorten links from github and gitlab\n  &.github,\n  &.gitlab {\n    &::before {\n      color: var(--pst-color-text-muted);\n      font: var(--fa-font-brands);\n      margin-right: 0.25rem;\n    }\n  }\n\n  &.github::before {\n    content: var(--pst-icon-github);\n  }\n\n  &.gitlab::before {\n    content: var(--pst-icon-gitlab);\n  }\n}\n\n.heading-style {\n  margin: 2.75rem 0 1.05rem;\n  font-family: var(--pst-font-family-heading);\n  font-weight: var(--pst-font-weight-heading);\n  line-height: 1.15;\n}\n\nh1 {\n  @extend .heading-style;\n  margin-top: 0;\n  font-size: var(--pst-font-size-h1);\n  color: var(--pst-heading-color);\n}\n\nh2 {\n  @extend .heading-style;\n  font-size: var(--pst-font-size-h2);\n  color: var(--pst-heading-color);\n}\n\nh3 {\n  @extend .heading-style;\n  font-size: var(--pst-font-size-h3);\n  color: var(--pst-heading-color);\n}\n\nh4 {\n  @extend .heading-style;\n  font-size: var(--pst-font-size-h4);\n  color: var(--pst-heading-color);\n}\n\nh5 {\n  @extend .heading-style;\n  font-size: var(--pst-font-size-h5);\n  color: var(--pst-color-text-base);\n}\n\nh6 {\n  @extend .heading-style;\n  font-size: var(--pst-font-size-h6);\n  color: var(--pst-color-text-base);\n}\n\nsmall,\n.text_small {\n  font-size: var(--pst-font-size-milli);\n}\n\nhr {\n  border: 0;\n  border-top: 1px solid var(--pst-color-border);\n}\n\npre,\ncode,\nkbd,\nsamp {\n  font-family: var(--pst-font-family-monospace);\n}\n\nkbd {\n  // use theme negative\n  background-color: var(--pst-color-on-background);\n  color: var(--pst-color-text-muted);\n\n  // Compound keyboard elements will have nested kbd in them, so this prevents double lines\n  &:not(.compound) {\n    border: 1px solid var(--pst-color-border);\n    margin: 0 0.1rem;\n    padding: 0.1rem 0.4rem;\n    box-shadow: 1px 1px 1px var(--pst-color-shadow);\n  }\n}\n\ncode {\n  color: var(--pst-color-inline-code);\n}\n\npre {\n  margin: 1.5em 0 1.5em 0;\n  padding: 1rem;\n  background-color: var(--pst-color-surface);\n  color: var(--pst-color-text-base);\n  line-height: 1.2em;\n  border: 1px solid var(--pst-color-border);\n  border-radius: $admonition-border-radius;\n\n  .linenos {\n    // minimum opacity to make the line numbers WCAG AA conformant\n    opacity: 0.8;\n    padding-right: 10px;\n  }\n}\n\n// the back to top btn\n#pst-back-to-top {\n  z-index: $zindex-tooltip;\n  position: fixed;\n  display: none;\n  top: 90vh;\n  left: 50vw;\n  transform: translate(-50%);\n  color: var(--pst-color-secondary-text);\n  background-color: var(--pst-color-secondary);\n  border: none;\n}\n","/**\n * Consistent styling for links\n **/\n\n// Define some useful variables for links styling consistency\n//\n//  Thickness of the underline for links\n// the default will be either:\n//  - 1px\n// - 0.0625rem if it's thicker than 1px because the user has changed the text\n//   size in their browser\n$link-underline-thickness: unquote(\"max(1px, .0625rem)\") !default;\n// Offset of link underlines from text baseline\n// The default is 3px expressed as ems, as calculated against the default body\n// font size (on desktop).\n$link-underline-offset: 0.1578em !default;\n// Thickness of link underlines in hover state\n// The default for each link will be the thickest of the following:\n//  - 3px\n//  - 0.1875rem, if it's thicker than 3px because the user has changed the text\n//    size in their browser\n//  - 0.12em (relative to the link's text size)\n$link-hover-decoration-thickness: unquote(\"max(3px, .1875rem, .12em)\") !default;\n\n//  Ensures links have an underline decoration by default - needed to meet\n// WCAG SC 1.4.1\n@mixin link-decoration {\n  text-decoration: underline;\n\n  @if $link-underline-thickness {\n    text-decoration-thickness: $link-underline-thickness;\n  }\n\n  @if $link-underline-offset {\n    text-underline-offset: $link-underline-offset;\n  }\n}\n\n// Ensures links have an underline decoration on hover - distinct from the\n// default behaviour\n@mixin link-decoration-hover {\n  @if $link-hover-decoration-thickness {\n    text-decoration-thickness: $link-hover-decoration-thickness;\n    // Disable ink skipping on underlines on hover. Browsers haven't\n    // standardised on this part of the spec yet, so set both properties\n    text-decoration-skip-ink: none; // Chromium, Firefox\n    text-decoration-skip: none; // Safari\n  }\n}\n\n// Simple hover style - can be used alone or in conjunction with other mixins\n// Add the text underline and change in thickness on hover\n@mixin link-style-hover {\n  &:hover {\n    @include link-decoration;\n    @include link-decoration-hover;\n    color: var(--pst-color-link-hover);\n  }\n}\n\n// Default link styles\n//\n// Defines: default unvisited, visited, hover, and active.\n// TODO: @trallard to improve focus styles in subsequent PR\n@mixin link-style-default {\n  // So that really long links don't spill out of their container\n  word-wrap: break-word;\n\n  color: var(--pst-color-link);\n  @include link-decoration;\n\n  &:hover {\n    color: var(--pst-color-link-hover);\n    @include link-decoration-hover;\n  }\n\n  // TODO: @trallard to add active styles in subsequent PR\n  &:active {\n    color: var(--pst-color-link);\n  }\n\n  // Visited should still be hoverable\n  &:visited {\n    color: var(--pst-color-link);\n    &:hover {\n      color: var(--pst-color-link-hover);\n    }\n  }\n  @include focus-indicator;\n}\n\n// Text link styles\n//\n// Makes links use the muted text colour and removes the underline.\n// Use this mixin for navigation bar links.\n@mixin link-style-text {\n  color: var(--pst-color-text-muted);\n  text-decoration: none;\n\n  &:hover {\n    color: var(--pst-color-link-hover);\n    @include link-decoration;\n    @include link-decoration-hover;\n  }\n  @include focus-indicator;\n}\n\n// Sidebar and TOC links\n//\n// Makes links use the muted text colour and removes the underline.\n// Use this mixin for navigation the primary sidebar and table of contents.\n// Active and hover should work together rather than one overriding the other.\n@mixin link-sidebar {\n  color: var(--pst-color-text-muted);\n  text-decoration: none;\n\n  &:hover {\n    text-decoration: underline;\n    background-color: transparent;\n    color: var(--pst-color-link-hover);\n    @include link-decoration-hover;\n  }\n\n  // TODO: @trallard to update active styles in subsequent PR\n  &:active {\n    color: var(--pst-color-link-hover);\n  }\n}\n\n// Sidebar current page link styles\n//\n// Adds a vertical line on the left hand side of the link to indicate that\n// it's the current page. Note this is distinct from an active state.\n// Used on the primary sidebar and the TOC.\n// We want the side box shadow to have the same thickness as the hover underline\n@mixin link-sidebar-current {\n  font-weight: 600;\n  color: var(--pst-color-primary);\n  @if $link-hover-decoration-thickness {\n    box-shadow: inset\n      $link-hover-decoration-thickness\n      0px\n      0px\n      var(--pst-color-primary);\n  }\n}\n\n// Navigation bar current page link styles\n//\n// Adds a bottom underline, this leaves enough space for the hover state without\n// cluttering the navbar.\n// We want the side box shadow to have the same thickness as the hover underline\n@mixin link-navbar-current {\n  font-weight: 600;\n  color: var(--pst-color-primary);\n  @if $link-hover-decoration-thickness {\n    border-bottom: $link-hover-decoration-thickness\n      solid\n      var(--pst-color-primary);\n  }\n}\n\n// Navigation bar icon links hover styles\n//\n// Adds a bottom box-shadow - since there is no text we cannot use text-decoration\n// We want the side box shadow to have the same thickness as the hover underline\n@mixin icon-navbar-hover {\n  &:hover {\n    color: var(--pst-color-link-hover);\n    @if $link-hover-decoration-thickness {\n      box-shadow: 0px\n        $link-hover-decoration-thickness\n        0px\n        var(--pst-color-link-hover);\n    }\n  }\n}\n\n// Focus indicator\n@mixin focus-indicator {\n  &:focus-visible {\n    outline: 2px solid var(--pst-color-accent);\n  }\n}\n","// Variables\n//\n// Variables should follow the `$component-state-property-size` formula for\n// consistent naming. Ex: $nav-link-disabled-color and $modal-content-box-shadow-xs.\n\n// Color system\n\n// scss-docs-start gray-color-variables\n$white:    #fff !default;\n$gray-100: #f8f9fa !default;\n$gray-200: #e9ecef !default;\n$gray-300: #dee2e6 !default;\n$gray-400: #ced4da !default;\n$gray-500: #adb5bd !default;\n$gray-600: #6c757d !default;\n$gray-700: #495057 !default;\n$gray-800: #343a40 !default;\n$gray-900: #212529 !default;\n$black:    #000 !default;\n// scss-docs-end gray-color-variables\n\n// fusv-disable\n// scss-docs-start gray-colors-map\n$grays: (\n  \"100\": $gray-100,\n  \"200\": $gray-200,\n  \"300\": $gray-300,\n  \"400\": $gray-400,\n  \"500\": $gray-500,\n  \"600\": $gray-600,\n  \"700\": $gray-700,\n  \"800\": $gray-800,\n  \"900\": $gray-900\n) !default;\n// scss-docs-end gray-colors-map\n// fusv-enable\n\n// scss-docs-start color-variables\n$blue:    #0d6efd !default;\n$indigo:  #6610f2 !default;\n$purple:  #6f42c1 !default;\n$pink:    #d63384 !default;\n$red:     #dc3545 !default;\n$orange:  #fd7e14 !default;\n$yellow:  #ffc107 !default;\n$green:   #198754 !default;\n$teal:    #20c997 !default;\n$cyan:    #0dcaf0 !default;\n// scss-docs-end color-variables\n\n// scss-docs-start colors-map\n$colors: (\n  \"blue\":       $blue,\n  \"indigo\":     $indigo,\n  \"purple\":     $purple,\n  \"pink\":       $pink,\n  \"red\":        $red,\n  \"orange\":     $orange,\n  \"yellow\":     $yellow,\n  \"green\":      $green,\n  \"teal\":       $teal,\n  \"cyan\":       $cyan,\n  \"black\":      $black,\n  \"white\":      $white,\n  \"gray\":       $gray-600,\n  \"gray-dark\":  $gray-800\n) !default;\n// scss-docs-end colors-map\n\n// The contrast ratio to reach against white, to determine if color changes from \"light\" to \"dark\". Acceptable values for WCAG 2.0 are 3, 4.5 and 7.\n// See https://www.w3.org/TR/WCAG20/#visual-audio-contrast-contrast\n$min-contrast-ratio:   4.5 !default;\n\n// Customize the light and dark text colors for use in our color contrast function.\n$color-contrast-dark:      $black !default;\n$color-contrast-light:     $white !default;\n\n// fusv-disable\n$blue-100: tint-color($blue, 80%) !default;\n$blue-200: tint-color($blue, 60%) !default;\n$blue-300: tint-color($blue, 40%) !default;\n$blue-400: tint-color($blue, 20%) !default;\n$blue-500: $blue !default;\n$blue-600: shade-color($blue, 20%) !default;\n$blue-700: shade-color($blue, 40%) !default;\n$blue-800: shade-color($blue, 60%) !default;\n$blue-900: shade-color($blue, 80%) !default;\n\n$indigo-100: tint-color($indigo, 80%) !default;\n$indigo-200: tint-color($indigo, 60%) !default;\n$indigo-300: tint-color($indigo, 40%) !default;\n$indigo-400: tint-color($indigo, 20%) !default;\n$indigo-500: $indigo !default;\n$indigo-600: shade-color($indigo, 20%) !default;\n$indigo-700: shade-color($indigo, 40%) !default;\n$indigo-800: shade-color($indigo, 60%) !default;\n$indigo-900: shade-color($indigo, 80%) !default;\n\n$purple-100: tint-color($purple, 80%) !default;\n$purple-200: tint-color($purple, 60%) !default;\n$purple-300: tint-color($purple, 40%) !default;\n$purple-400: tint-color($purple, 20%) !default;\n$purple-500: $purple !default;\n$purple-600: shade-color($purple, 20%) !default;\n$purple-700: shade-color($purple, 40%) !default;\n$purple-800: shade-color($purple, 60%) !default;\n$purple-900: shade-color($purple, 80%) !default;\n\n$pink-100: tint-color($pink, 80%) !default;\n$pink-200: tint-color($pink, 60%) !default;\n$pink-300: tint-color($pink, 40%) !default;\n$pink-400: tint-color($pink, 20%) !default;\n$pink-500: $pink !default;\n$pink-600: shade-color($pink, 20%) !default;\n$pink-700: shade-color($pink, 40%) !default;\n$pink-800: shade-color($pink, 60%) !default;\n$pink-900: shade-color($pink, 80%) !default;\n\n$red-100: tint-color($red, 80%) !default;\n$red-200: tint-color($red, 60%) !default;\n$red-300: tint-color($red, 40%) !default;\n$red-400: tint-color($red, 20%) !default;\n$red-500: $red !default;\n$red-600: shade-color($red, 20%) !default;\n$red-700: shade-color($red, 40%) !default;\n$red-800: shade-color($red, 60%) !default;\n$red-900: shade-color($red, 80%) !default;\n\n$orange-100: tint-color($orange, 80%) !default;\n$orange-200: tint-color($orange, 60%) !default;\n$orange-300: tint-color($orange, 40%) !default;\n$orange-400: tint-color($orange, 20%) !default;\n$orange-500: $orange !default;\n$orange-600: shade-color($orange, 20%) !default;\n$orange-700: shade-color($orange, 40%) !default;\n$orange-800: shade-color($orange, 60%) !default;\n$orange-900: shade-color($orange, 80%) !default;\n\n$yellow-100: tint-color($yellow, 80%) !default;\n$yellow-200: tint-color($yellow, 60%) !default;\n$yellow-300: tint-color($yellow, 40%) !default;\n$yellow-400: tint-color($yellow, 20%) !default;\n$yellow-500: $yellow !default;\n$yellow-600: shade-color($yellow, 20%) !default;\n$yellow-700: shade-color($yellow, 40%) !default;\n$yellow-800: shade-color($yellow, 60%) !default;\n$yellow-900: shade-color($yellow, 80%) !default;\n\n$green-100: tint-color($green, 80%) !default;\n$green-200: tint-color($green, 60%) !default;\n$green-300: tint-color($green, 40%) !default;\n$green-400: tint-color($green, 20%) !default;\n$green-500: $green !default;\n$green-600: shade-color($green, 20%) !default;\n$green-700: shade-color($green, 40%) !default;\n$green-800: shade-color($green, 60%) !default;\n$green-900: shade-color($green, 80%) !default;\n\n$teal-100: tint-color($teal, 80%) !default;\n$teal-200: tint-color($teal, 60%) !default;\n$teal-300: tint-color($teal, 40%) !default;\n$teal-400: tint-color($teal, 20%) !default;\n$teal-500: $teal !default;\n$teal-600: shade-color($teal, 20%) !default;\n$teal-700: shade-color($teal, 40%) !default;\n$teal-800: shade-color($teal, 60%) !default;\n$teal-900: shade-color($teal, 80%) !default;\n\n$cyan-100: tint-color($cyan, 80%) !default;\n$cyan-200: tint-color($cyan, 60%) !default;\n$cyan-300: tint-color($cyan, 40%) !default;\n$cyan-400: tint-color($cyan, 20%) !default;\n$cyan-500: $cyan !default;\n$cyan-600: shade-color($cyan, 20%) !default;\n$cyan-700: shade-color($cyan, 40%) !default;\n$cyan-800: shade-color($cyan, 60%) !default;\n$cyan-900: shade-color($cyan, 80%) !default;\n\n$blues: (\n  \"blue-100\": $blue-100,\n  \"blue-200\": $blue-200,\n  \"blue-300\": $blue-300,\n  \"blue-400\": $blue-400,\n  \"blue-500\": $blue-500,\n  \"blue-600\": $blue-600,\n  \"blue-700\": $blue-700,\n  \"blue-800\": $blue-800,\n  \"blue-900\": $blue-900\n) !default;\n\n$indigos: (\n  \"indigo-100\": $indigo-100,\n  \"indigo-200\": $indigo-200,\n  \"indigo-300\": $indigo-300,\n  \"indigo-400\": $indigo-400,\n  \"indigo-500\": $indigo-500,\n  \"indigo-600\": $indigo-600,\n  \"indigo-700\": $indigo-700,\n  \"indigo-800\": $indigo-800,\n  \"indigo-900\": $indigo-900\n) !default;\n\n$purples: (\n  \"purple-100\": $purple-100,\n  \"purple-200\": $purple-200,\n  \"purple-300\": $purple-300,\n  \"purple-400\": $purple-400,\n  \"purple-500\": $purple-500,\n  \"purple-600\": $purple-600,\n  \"purple-700\": $purple-700,\n  \"purple-800\": $purple-800,\n  \"purple-900\": $purple-900\n) !default;\n\n$pinks: (\n  \"pink-100\": $pink-100,\n  \"pink-200\": $pink-200,\n  \"pink-300\": $pink-300,\n  \"pink-400\": $pink-400,\n  \"pink-500\": $pink-500,\n  \"pink-600\": $pink-600,\n  \"pink-700\": $pink-700,\n  \"pink-800\": $pink-800,\n  \"pink-900\": $pink-900\n) !default;\n\n$reds: (\n  \"red-100\": $red-100,\n  \"red-200\": $red-200,\n  \"red-300\": $red-300,\n  \"red-400\": $red-400,\n  \"red-500\": $red-500,\n  \"red-600\": $red-600,\n  \"red-700\": $red-700,\n  \"red-800\": $red-800,\n  \"red-900\": $red-900\n) !default;\n\n$oranges: (\n  \"orange-100\": $orange-100,\n  \"orange-200\": $orange-200,\n  \"orange-300\": $orange-300,\n  \"orange-400\": $orange-400,\n  \"orange-500\": $orange-500,\n  \"orange-600\": $orange-600,\n  \"orange-700\": $orange-700,\n  \"orange-800\": $orange-800,\n  \"orange-900\": $orange-900\n) !default;\n\n$yellows: (\n  \"yellow-100\": $yellow-100,\n  \"yellow-200\": $yellow-200,\n  \"yellow-300\": $yellow-300,\n  \"yellow-400\": $yellow-400,\n  \"yellow-500\": $yellow-500,\n  \"yellow-600\": $yellow-600,\n  \"yellow-700\": $yellow-700,\n  \"yellow-800\": $yellow-800,\n  \"yellow-900\": $yellow-900\n) !default;\n\n$greens: (\n  \"green-100\": $green-100,\n  \"green-200\": $green-200,\n  \"green-300\": $green-300,\n  \"green-400\": $green-400,\n  \"green-500\": $green-500,\n  \"green-600\": $green-600,\n  \"green-700\": $green-700,\n  \"green-800\": $green-800,\n  \"green-900\": $green-900\n) !default;\n\n$teals: (\n  \"teal-100\": $teal-100,\n  \"teal-200\": $teal-200,\n  \"teal-300\": $teal-300,\n  \"teal-400\": $teal-400,\n  \"teal-500\": $teal-500,\n  \"teal-600\": $teal-600,\n  \"teal-700\": $teal-700,\n  \"teal-800\": $teal-800,\n  \"teal-900\": $teal-900\n) !default;\n\n$cyans: (\n  \"cyan-100\": $cyan-100,\n  \"cyan-200\": $cyan-200,\n  \"cyan-300\": $cyan-300,\n  \"cyan-400\": $cyan-400,\n  \"cyan-500\": $cyan-500,\n  \"cyan-600\": $cyan-600,\n  \"cyan-700\": $cyan-700,\n  \"cyan-800\": $cyan-800,\n  \"cyan-900\": $cyan-900\n) !default;\n// fusv-enable\n\n// scss-docs-start theme-color-variables\n$primary:       $blue !default;\n$secondary:     $gray-600 !default;\n$success:       $green !default;\n$info:          $cyan !default;\n$warning:       $yellow !default;\n$danger:        $red !default;\n$light:         $gray-100 !default;\n$dark:          $gray-900 !default;\n// scss-docs-end theme-color-variables\n\n// scss-docs-start theme-colors-map\n$theme-colors: (\n  \"primary\":    $primary,\n  \"secondary\":  $secondary,\n  \"success\":    $success,\n  \"info\":       $info,\n  \"warning\":    $warning,\n  \"danger\":     $danger,\n  \"light\":      $light,\n  \"dark\":       $dark\n) !default;\n// scss-docs-end theme-colors-map\n\n// scss-docs-start theme-text-variables\n$primary-text-emphasis:   shade-color($primary, 60%) !default;\n$secondary-text-emphasis: shade-color($secondary, 60%) !default;\n$success-text-emphasis:   shade-color($success, 60%) !default;\n$info-text-emphasis:      shade-color($info, 60%) !default;\n$warning-text-emphasis:   shade-color($warning, 60%) !default;\n$danger-text-emphasis:    shade-color($danger, 60%) !default;\n$light-text-emphasis:     $gray-700 !default;\n$dark-text-emphasis:      $gray-700 !default;\n// scss-docs-end theme-text-variables\n\n// scss-docs-start theme-bg-subtle-variables\n$primary-bg-subtle:       tint-color($primary, 80%) !default;\n$secondary-bg-subtle:     tint-color($secondary, 80%) !default;\n$success-bg-subtle:       tint-color($success, 80%) !default;\n$info-bg-subtle:          tint-color($info, 80%) !default;\n$warning-bg-subtle:       tint-color($warning, 80%) !default;\n$danger-bg-subtle:        tint-color($danger, 80%) !default;\n$light-bg-subtle:         mix($gray-100, $white) !default;\n$dark-bg-subtle:          $gray-400 !default;\n// scss-docs-end theme-bg-subtle-variables\n\n// scss-docs-start theme-border-subtle-variables\n$primary-border-subtle:   tint-color($primary, 60%) !default;\n$secondary-border-subtle: tint-color($secondary, 60%) !default;\n$success-border-subtle:   tint-color($success, 60%) !default;\n$info-border-subtle:      tint-color($info, 60%) !default;\n$warning-border-subtle:   tint-color($warning, 60%) !default;\n$danger-border-subtle:    tint-color($danger, 60%) !default;\n$light-border-subtle:     $gray-200 !default;\n$dark-border-subtle:      $gray-500 !default;\n// scss-docs-end theme-border-subtle-variables\n\n// Characters which are escaped by the escape-svg function\n$escaped-characters: (\n  (\"<\", \"%3c\"),\n  (\">\", \"%3e\"),\n  (\"#\", \"%23\"),\n  (\"(\", \"%28\"),\n  (\")\", \"%29\"),\n) !default;\n\n// Options\n//\n// Quickly modify global styling by enabling or disabling optional features.\n\n$enable-caret:                true !default;\n$enable-rounded:              true !default;\n$enable-shadows:              false !default;\n$enable-gradients:            false !default;\n$enable-transitions:          true !default;\n$enable-reduced-motion:       true !default;\n$enable-smooth-scroll:        true !default;\n$enable-grid-classes:         true !default;\n$enable-container-classes:    true !default;\n$enable-cssgrid:              false !default;\n$enable-button-pointers:      true !default;\n$enable-rfs:                  true !default;\n$enable-validation-icons:     true !default;\n$enable-negative-margins:     false !default;\n$enable-deprecation-messages: true !default;\n$enable-important-utilities:  true !default;\n\n$enable-dark-mode:            true !default;\n$color-mode-type:             data !default; // `data` or `media-query`\n\n// Prefix for :root CSS variables\n\n$variable-prefix:             bs- !default; // Deprecated in v5.2.0 for the shorter `$prefix`\n$prefix:                      $variable-prefix !default;\n\n// Gradient\n//\n// The gradient which is added to components if `$enable-gradients` is `true`\n// This gradient is also added to elements with `.bg-gradient`\n// scss-docs-start variable-gradient\n$gradient: linear-gradient(180deg, rgba($white, .15), rgba($white, 0)) !default;\n// scss-docs-end variable-gradient\n\n// Spacing\n//\n// Control the default styling of most Bootstrap elements by modifying these\n// variables. Mostly focused on spacing.\n// You can add more entries to the $spacers map, should you need more variation.\n\n// scss-docs-start spacer-variables-maps\n$spacer: 1rem !default;\n$spacers: (\n  0: 0,\n  1: $spacer * .25,\n  2: $spacer * .5,\n  3: $spacer,\n  4: $spacer * 1.5,\n  5: $spacer * 3,\n) !default;\n// scss-docs-end spacer-variables-maps\n\n// Position\n//\n// Define the edge positioning anchors of the position utilities.\n\n// scss-docs-start position-map\n$position-values: (\n  0: 0,\n  50: 50%,\n  100: 100%\n) !default;\n// scss-docs-end position-map\n\n// Body\n//\n// Settings for the `<body>` element.\n\n$body-text-align:           null !default;\n$body-color:                $gray-900 !default;\n$body-bg:                   $white !default;\n\n$body-secondary-color:      rgba($body-color, .75) !default;\n$body-secondary-bg:         $gray-200 !default;\n\n$body-tertiary-color:       rgba($body-color, .5) !default;\n$body-tertiary-bg:          $gray-100 !default;\n\n$body-emphasis-color:       $black !default;\n\n// Links\n//\n// Style anchor elements.\n\n$link-color:                              $primary !default;\n$link-decoration:                         underline !default;\n$link-shade-percentage:                   20% !default;\n$link-hover-color:                        shift-color($link-color, $link-shade-percentage) !default;\n$link-hover-decoration:                   null !default;\n\n$stretched-link-pseudo-element:           after !default;\n$stretched-link-z-index:                  1 !default;\n\n// Icon links\n// scss-docs-start icon-link-variables\n$icon-link-gap:               .375rem !default;\n$icon-link-underline-offset:  .25em !default;\n$icon-link-icon-size:         1em !default;\n$icon-link-icon-transition:   .2s ease-in-out transform !default;\n$icon-link-icon-transform:    translate3d(.25em, 0, 0) !default;\n// scss-docs-end icon-link-variables\n\n// Paragraphs\n//\n// Style p element.\n\n$paragraph-margin-bottom:   1rem !default;\n\n\n// Grid breakpoints\n//\n// Define the minimum dimensions at which your layout will change,\n// adapting to different screen sizes, for use in media queries.\n\n// scss-docs-start grid-breakpoints\n$grid-breakpoints: (\n  xs: 0,\n  sm: 576px,\n  md: 768px,\n  lg: 992px,\n  xl: 1200px,\n  xxl: 1400px\n) !default;\n// scss-docs-end grid-breakpoints\n\n@include _assert-ascending($grid-breakpoints, \"$grid-breakpoints\");\n@include _assert-starts-at-zero($grid-breakpoints, \"$grid-breakpoints\");\n\n\n// Grid containers\n//\n// Define the maximum width of `.container` for different screen sizes.\n\n// scss-docs-start container-max-widths\n$container-max-widths: (\n  sm: 540px,\n  md: 720px,\n  lg: 960px,\n  xl: 1140px,\n  xxl: 1320px\n) !default;\n// scss-docs-end container-max-widths\n\n@include _assert-ascending($container-max-widths, \"$container-max-widths\");\n\n\n// Grid columns\n//\n// Set the number of columns and specify the width of the gutters.\n\n$grid-columns:                12 !default;\n$grid-gutter-width:           1.5rem !default;\n$grid-row-columns:            6 !default;\n\n// Container padding\n\n$container-padding-x: $grid-gutter-width !default;\n\n\n// Components\n//\n// Define common padding and border radius sizes and more.\n\n// scss-docs-start border-variables\n$border-width:                1px !default;\n$border-widths: (\n  1: 1px,\n  2: 2px,\n  3: 3px,\n  4: 4px,\n  5: 5px\n) !default;\n$border-style:                solid !default;\n$border-color:                $gray-300 !default;\n$border-color-translucent:    rgba($black, .175) !default;\n// scss-docs-end border-variables\n\n// scss-docs-start border-radius-variables\n$border-radius:               .375rem !default;\n$border-radius-sm:            .25rem !default;\n$border-radius-lg:            .5rem !default;\n$border-radius-xl:            1rem !default;\n$border-radius-xxl:           2rem !default;\n$border-radius-pill:          50rem !default;\n// scss-docs-end border-radius-variables\n// fusv-disable\n$border-radius-2xl:           $border-radius-xxl !default; // Deprecated in v5.3.0\n// fusv-enable\n\n// scss-docs-start box-shadow-variables\n$box-shadow:                  0 .5rem 1rem rgba($black, .15) !default;\n$box-shadow-sm:               0 .125rem .25rem rgba($black, .075) !default;\n$box-shadow-lg:               0 1rem 3rem rgba($black, .175) !default;\n$box-shadow-inset:            inset 0 1px 2px rgba($black, .075) !default;\n// scss-docs-end box-shadow-variables\n\n$component-active-color:      $white !default;\n$component-active-bg:         $primary !default;\n\n// scss-docs-start focus-ring-variables\n$focus-ring-width:      .25rem !default;\n$focus-ring-opacity:    .25 !default;\n$focus-ring-color:      rgba($primary, $focus-ring-opacity) !default;\n$focus-ring-blur:       0 !default;\n$focus-ring-box-shadow: 0 0 $focus-ring-blur $focus-ring-width $focus-ring-color !default;\n// scss-docs-end focus-ring-variables\n\n// scss-docs-start caret-variables\n$caret-width:                 .3em !default;\n$caret-vertical-align:        $caret-width * .85 !default;\n$caret-spacing:               $caret-width * .85 !default;\n// scss-docs-end caret-variables\n\n$transition-base:             all .2s ease-in-out !default;\n$transition-fade:             opacity .15s linear !default;\n// scss-docs-start collapse-transition\n$transition-collapse:         height .35s ease !default;\n$transition-collapse-width:   width .35s ease !default;\n// scss-docs-end collapse-transition\n\n// stylelint-disable function-disallowed-list\n// scss-docs-start aspect-ratios\n$aspect-ratios: (\n  \"1x1\": 100%,\n  \"4x3\": calc(3 / 4 * 100%),\n  \"16x9\": calc(9 / 16 * 100%),\n  \"21x9\": calc(9 / 21 * 100%)\n) !default;\n// scss-docs-end aspect-ratios\n// stylelint-enable function-disallowed-list\n\n// Typography\n//\n// Font, line-height, and color for body text, headings, and more.\n\n// scss-docs-start font-variables\n// stylelint-disable value-keyword-case\n$font-family-sans-serif:      system-ui, -apple-system, \"Segoe UI\", Roboto, \"Helvetica Neue\", \"Noto Sans\", \"Liberation Sans\", Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\", \"Noto Color Emoji\" !default;\n$font-family-monospace:       SFMono-Regular, Menlo, Monaco, Consolas, \"Liberation Mono\", \"Courier New\", monospace !default;\n// stylelint-enable value-keyword-case\n$font-family-base:            var(--#{$prefix}font-sans-serif) !default;\n$font-family-code:            var(--#{$prefix}font-monospace) !default;\n\n// $font-size-root affects the value of `rem`, which is used for as well font sizes, paddings, and margins\n// $font-size-base affects the font size of the body text\n$font-size-root:              null !default;\n$font-size-base:              1rem !default; // Assumes the browser default, typically `16px`\n$font-size-sm:                $font-size-base * .875 !default;\n$font-size-lg:                $font-size-base * 1.25 !default;\n\n$font-weight-lighter:         lighter !default;\n$font-weight-light:           300 !default;\n$font-weight-normal:          400 !default;\n$font-weight-medium:          500 !default;\n$font-weight-semibold:        600 !default;\n$font-weight-bold:            700 !default;\n$font-weight-bolder:          bolder !default;\n\n$font-weight-base:            $font-weight-normal !default;\n\n$line-height-base:            1.5 !default;\n$line-height-sm:              1.25 !default;\n$line-height-lg:              2 !default;\n\n$h1-font-size:                $font-size-base * 2.5 !default;\n$h2-font-size:                $font-size-base * 2 !default;\n$h3-font-size:                $font-size-base * 1.75 !default;\n$h4-font-size:                $font-size-base * 1.5 !default;\n$h5-font-size:                $font-size-base * 1.25 !default;\n$h6-font-size:                $font-size-base !default;\n// scss-docs-end font-variables\n\n// scss-docs-start font-sizes\n$font-sizes: (\n  1: $h1-font-size,\n  2: $h2-font-size,\n  3: $h3-font-size,\n  4: $h4-font-size,\n  5: $h5-font-size,\n  6: $h6-font-size\n) !default;\n// scss-docs-end font-sizes\n\n// scss-docs-start headings-variables\n$headings-margin-bottom:      $spacer * .5 !default;\n$headings-font-family:        null !default;\n$headings-font-style:         null !default;\n$headings-font-weight:        500 !default;\n$headings-line-height:        1.2 !default;\n$headings-color:              inherit !default;\n// scss-docs-end headings-variables\n\n// scss-docs-start display-headings\n$display-font-sizes: (\n  1: 5rem,\n  2: 4.5rem,\n  3: 4rem,\n  4: 3.5rem,\n  5: 3rem,\n  6: 2.5rem\n) !default;\n\n$display-font-family: null !default;\n$display-font-style:  null !default;\n$display-font-weight: 300 !default;\n$display-line-height: $headings-line-height !default;\n// scss-docs-end display-headings\n\n// scss-docs-start type-variables\n$lead-font-size:              $font-size-base * 1.25 !default;\n$lead-font-weight:            300 !default;\n\n$small-font-size:             .875em !default;\n\n$sub-sup-font-size:           .75em !default;\n\n// fusv-disable\n$text-muted:                  var(--#{$prefix}secondary-color) !default; // Deprecated in 5.3.0\n// fusv-enable\n\n$initialism-font-size:        $small-font-size !default;\n\n$blockquote-margin-y:         $spacer !default;\n$blockquote-font-size:        $font-size-base * 1.25 !default;\n$blockquote-footer-color:     $gray-600 !default;\n$blockquote-footer-font-size: $small-font-size !default;\n\n$hr-margin-y:                 $spacer !default;\n$hr-color:                    inherit !default;\n\n// fusv-disable\n$hr-bg-color:                 null !default; // Deprecated in v5.2.0\n$hr-height:                   null !default; // Deprecated in v5.2.0\n// fusv-enable\n\n$hr-border-color:             null !default; // Allows for inherited colors\n$hr-border-width:             var(--#{$prefix}border-width) !default;\n$hr-opacity:                  .25 !default;\n\n// scss-docs-start vr-variables\n$vr-border-width:             var(--#{$prefix}border-width) !default;\n// scss-docs-end vr-variables\n\n$legend-margin-bottom:        .5rem !default;\n$legend-font-size:            1.5rem !default;\n$legend-font-weight:          null !default;\n\n$dt-font-weight:              $font-weight-bold !default;\n\n$list-inline-padding:         .5rem !default;\n\n$mark-padding:                .1875em !default;\n$mark-color:                  $body-color !default;\n$mark-bg:                     $yellow-100 !default;\n// scss-docs-end type-variables\n\n\n// Tables\n//\n// Customizes the `.table` component with basic values, each used across all table variations.\n\n// scss-docs-start table-variables\n$table-cell-padding-y:        .5rem !default;\n$table-cell-padding-x:        .5rem !default;\n$table-cell-padding-y-sm:     .25rem !default;\n$table-cell-padding-x-sm:     .25rem !default;\n\n$table-cell-vertical-align:   top !default;\n\n$table-color:                 var(--#{$prefix}emphasis-color) !default;\n$table-bg:                    var(--#{$prefix}body-bg) !default;\n$table-accent-bg:             transparent !default;\n\n$table-th-font-weight:        null !default;\n\n$table-striped-color:         $table-color !default;\n$table-striped-bg-factor:     .05 !default;\n$table-striped-bg:            rgba(var(--#{$prefix}emphasis-color-rgb), $table-striped-bg-factor) !default;\n\n$table-active-color:          $table-color !default;\n$table-active-bg-factor:      .1 !default;\n$table-active-bg:             rgba(var(--#{$prefix}emphasis-color-rgb), $table-active-bg-factor) !default;\n\n$table-hover-color:           $table-color !default;\n$table-hover-bg-factor:       .075 !default;\n$table-hover-bg:              rgba(var(--#{$prefix}emphasis-color-rgb), $table-hover-bg-factor) !default;\n\n$table-border-factor:         .2 !default;\n$table-border-width:          var(--#{$prefix}border-width) !default;\n$table-border-color:          var(--#{$prefix}border-color) !default;\n\n$table-striped-order:         odd !default;\n$table-striped-columns-order: even !default;\n\n$table-group-separator-color: currentcolor !default;\n\n$table-caption-color:         var(--#{$prefix}secondary-color) !default;\n\n$table-bg-scale:              -80% !default;\n// scss-docs-end table-variables\n\n// scss-docs-start table-loop\n$table-variants: (\n  \"primary\":    shift-color($primary, $table-bg-scale),\n  \"secondary\":  shift-color($secondary, $table-bg-scale),\n  \"success\":    shift-color($success, $table-bg-scale),\n  \"info\":       shift-color($info, $table-bg-scale),\n  \"warning\":    shift-color($warning, $table-bg-scale),\n  \"danger\":     shift-color($danger, $table-bg-scale),\n  \"light\":      $light,\n  \"dark\":       $dark,\n) !default;\n// scss-docs-end table-loop\n\n\n// Buttons + Forms\n//\n// Shared variables that are reassigned to `$input-` and `$btn-` specific variables.\n\n// scss-docs-start input-btn-variables\n$input-btn-padding-y:         .375rem !default;\n$input-btn-padding-x:         .75rem !default;\n$input-btn-font-family:       null !default;\n$input-btn-font-size:         $font-size-base !default;\n$input-btn-line-height:       $line-height-base !default;\n\n$input-btn-focus-width:         $focus-ring-width !default;\n$input-btn-focus-color-opacity: $focus-ring-opacity !default;\n$input-btn-focus-color:         $focus-ring-color !default;\n$input-btn-focus-blur:          $focus-ring-blur !default;\n$input-btn-focus-box-shadow:    $focus-ring-box-shadow !default;\n\n$input-btn-padding-y-sm:      .25rem !default;\n$input-btn-padding-x-sm:      .5rem !default;\n$input-btn-font-size-sm:      $font-size-sm !default;\n\n$input-btn-padding-y-lg:      .5rem !default;\n$input-btn-padding-x-lg:      1rem !default;\n$input-btn-font-size-lg:      $font-size-lg !default;\n\n$input-btn-border-width:      var(--#{$prefix}border-width) !default;\n// scss-docs-end input-btn-variables\n\n\n// Buttons\n//\n// For each of Bootstrap's buttons, define text, background, and border color.\n\n// scss-docs-start btn-variables\n$btn-color:                   var(--#{$prefix}body-color) !default;\n$btn-padding-y:               $input-btn-padding-y !default;\n$btn-padding-x:               $input-btn-padding-x !default;\n$btn-font-family:             $input-btn-font-family !default;\n$btn-font-size:               $input-btn-font-size !default;\n$btn-line-height:             $input-btn-line-height !default;\n$btn-white-space:             null !default; // Set to `nowrap` to prevent text wrapping\n\n$btn-padding-y-sm:            $input-btn-padding-y-sm !default;\n$btn-padding-x-sm:            $input-btn-padding-x-sm !default;\n$btn-font-size-sm:            $input-btn-font-size-sm !default;\n\n$btn-padding-y-lg:            $input-btn-padding-y-lg !default;\n$btn-padding-x-lg:            $input-btn-padding-x-lg !default;\n$btn-font-size-lg:            $input-btn-font-size-lg !default;\n\n$btn-border-width:            $input-btn-border-width !default;\n\n$btn-font-weight:             $font-weight-normal !default;\n$btn-box-shadow:              inset 0 1px 0 rgba($white, .15), 0 1px 1px rgba($black, .075) !default;\n$btn-focus-width:             $input-btn-focus-width !default;\n$btn-focus-box-shadow:        $input-btn-focus-box-shadow !default;\n$btn-disabled-opacity:        .65 !default;\n$btn-active-box-shadow:       inset 0 3px 5px rgba($black, .125) !default;\n\n$btn-link-color:              var(--#{$prefix}link-color) !default;\n$btn-link-hover-color:        var(--#{$prefix}link-hover-color) !default;\n$btn-link-disabled-color:     $gray-600 !default;\n$btn-link-focus-shadow-rgb:   to-rgb(mix(color-contrast($link-color), $link-color, 15%)) !default;\n\n// Allows for customizing button radius independently from global border radius\n$btn-border-radius:           var(--#{$prefix}border-radius) !default;\n$btn-border-radius-sm:        var(--#{$prefix}border-radius-sm) !default;\n$btn-border-radius-lg:        var(--#{$prefix}border-radius-lg) !default;\n\n$btn-transition:              color .15s ease-in-out, background-color .15s ease-in-out, border-color .15s ease-in-out, box-shadow .15s ease-in-out !default;\n\n$btn-hover-bg-shade-amount:       15% !default;\n$btn-hover-bg-tint-amount:        15% !default;\n$btn-hover-border-shade-amount:   20% !default;\n$btn-hover-border-tint-amount:    10% !default;\n$btn-active-bg-shade-amount:      20% !default;\n$btn-active-bg-tint-amount:       20% !default;\n$btn-active-border-shade-amount:  25% !default;\n$btn-active-border-tint-amount:   10% !default;\n// scss-docs-end btn-variables\n\n\n// Forms\n\n// scss-docs-start form-text-variables\n$form-text-margin-top:                  .25rem !default;\n$form-text-font-size:                   $small-font-size !default;\n$form-text-font-style:                  null !default;\n$form-text-font-weight:                 null !default;\n$form-text-color:                       var(--#{$prefix}secondary-color) !default;\n// scss-docs-end form-text-variables\n\n// scss-docs-start form-label-variables\n$form-label-margin-bottom:              .5rem !default;\n$form-label-font-size:                  null !default;\n$form-label-font-style:                 null !default;\n$form-label-font-weight:                null !default;\n$form-label-color:                      null !default;\n// scss-docs-end form-label-variables\n\n// scss-docs-start form-input-variables\n$input-padding-y:                       $input-btn-padding-y !default;\n$input-padding-x:                       $input-btn-padding-x !default;\n$input-font-family:                     $input-btn-font-family !default;\n$input-font-size:                       $input-btn-font-size !default;\n$input-font-weight:                     $font-weight-base !default;\n$input-line-height:                     $input-btn-line-height !default;\n\n$input-padding-y-sm:                    $input-btn-padding-y-sm !default;\n$input-padding-x-sm:                    $input-btn-padding-x-sm !default;\n$input-font-size-sm:                    $input-btn-font-size-sm !default;\n\n$input-padding-y-lg:                    $input-btn-padding-y-lg !default;\n$input-padding-x-lg:                    $input-btn-padding-x-lg !default;\n$input-font-size-lg:                    $input-btn-font-size-lg !default;\n\n$input-bg:                              var(--#{$prefix}body-bg) !default;\n$input-disabled-color:                  null !default;\n$input-disabled-bg:                     var(--#{$prefix}secondary-bg) !default;\n$input-disabled-border-color:           null !default;\n\n$input-color:                           var(--#{$prefix}body-color) !default;\n$input-border-color:                    var(--#{$prefix}border-color) !default;\n$input-border-width:                    $input-btn-border-width !default;\n$input-box-shadow:                      var(--#{$prefix}box-shadow-inset) !default;\n\n$input-border-radius:                   var(--#{$prefix}border-radius) !default;\n$input-border-radius-sm:                var(--#{$prefix}border-radius-sm) !default;\n$input-border-radius-lg:                var(--#{$prefix}border-radius-lg) !default;\n\n$input-focus-bg:                        $input-bg !default;\n$input-focus-border-color:              tint-color($component-active-bg, 50%) !default;\n$input-focus-color:                     $input-color !default;\n$input-focus-width:                     $input-btn-focus-width !default;\n$input-focus-box-shadow:                $input-btn-focus-box-shadow !default;\n\n$input-placeholder-color:               var(--#{$prefix}secondary-color) !default;\n$input-plaintext-color:                 var(--#{$prefix}body-color) !default;\n\n$input-height-border:                   calc(#{$input-border-width} * 2) !default; // stylelint-disable-line function-disallowed-list\n\n$input-height-inner:                    add($input-line-height * 1em, $input-padding-y * 2) !default;\n$input-height-inner-half:               add($input-line-height * .5em, $input-padding-y) !default;\n$input-height-inner-quarter:            add($input-line-height * .25em, $input-padding-y * .5) !default;\n\n$input-height:                          add($input-line-height * 1em, add($input-padding-y * 2, $input-height-border, false)) !default;\n$input-height-sm:                       add($input-line-height * 1em, add($input-padding-y-sm * 2, $input-height-border, false)) !default;\n$input-height-lg:                       add($input-line-height * 1em, add($input-padding-y-lg * 2, $input-height-border, false)) !default;\n\n$input-transition:                      border-color .15s ease-in-out, box-shadow .15s ease-in-out !default;\n\n$form-color-width:                      3rem !default;\n// scss-docs-end form-input-variables\n\n// scss-docs-start form-check-variables\n$form-check-input-width:                  1em !default;\n$form-check-min-height:                   $font-size-base * $line-height-base !default;\n$form-check-padding-start:                $form-check-input-width + .5em !default;\n$form-check-margin-bottom:                .125rem !default;\n$form-check-label-color:                  null !default;\n$form-check-label-cursor:                 null !default;\n$form-check-transition:                   null !default;\n\n$form-check-input-active-filter:          brightness(90%) !default;\n\n$form-check-input-bg:                     $input-bg !default;\n$form-check-input-border:                 var(--#{$prefix}border-width) solid var(--#{$prefix}border-color) !default;\n$form-check-input-border-radius:          .25em !default;\n$form-check-radio-border-radius:          50% !default;\n$form-check-input-focus-border:           $input-focus-border-color !default;\n$form-check-input-focus-box-shadow:       $focus-ring-box-shadow !default;\n\n$form-check-input-checked-color:          $component-active-color !default;\n$form-check-input-checked-bg-color:       $component-active-bg !default;\n$form-check-input-checked-border-color:   $form-check-input-checked-bg-color !default;\n$form-check-input-checked-bg-image:       url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 20 20'><path fill='none' stroke='#{$form-check-input-checked-color}' stroke-linecap='round' stroke-linejoin='round' stroke-width='3' d='m6 10 3 3 6-6'/></svg>\") !default;\n$form-check-radio-checked-bg-image:       url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'><circle r='2' fill='#{$form-check-input-checked-color}'/></svg>\") !default;\n\n$form-check-input-indeterminate-color:          $component-active-color !default;\n$form-check-input-indeterminate-bg-color:       $component-active-bg !default;\n$form-check-input-indeterminate-border-color:   $form-check-input-indeterminate-bg-color !default;\n$form-check-input-indeterminate-bg-image:       url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 20 20'><path fill='none' stroke='#{$form-check-input-indeterminate-color}' stroke-linecap='round' stroke-linejoin='round' stroke-width='3' d='M6 10h8'/></svg>\") !default;\n\n$form-check-input-disabled-opacity:        .5 !default;\n$form-check-label-disabled-opacity:        $form-check-input-disabled-opacity !default;\n$form-check-btn-check-disabled-opacity:    $btn-disabled-opacity !default;\n\n$form-check-inline-margin-end:    1rem !default;\n// scss-docs-end form-check-variables\n\n// scss-docs-start form-switch-variables\n$form-switch-color:               rgba($black, .25) !default;\n$form-switch-width:               2em !default;\n$form-switch-padding-start:       $form-switch-width + .5em !default;\n$form-switch-bg-image:            url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'><circle r='3' fill='#{$form-switch-color}'/></svg>\") !default;\n$form-switch-border-radius:       $form-switch-width !default;\n$form-switch-transition:          background-position .15s ease-in-out !default;\n\n$form-switch-focus-color:         $input-focus-border-color !default;\n$form-switch-focus-bg-image:      url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'><circle r='3' fill='#{$form-switch-focus-color}'/></svg>\") !default;\n\n$form-switch-checked-color:       $component-active-color !default;\n$form-switch-checked-bg-image:    url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='-4 -4 8 8'><circle r='3' fill='#{$form-switch-checked-color}'/></svg>\") !default;\n$form-switch-checked-bg-position: right center !default;\n// scss-docs-end form-switch-variables\n\n// scss-docs-start input-group-variables\n$input-group-addon-padding-y:           $input-padding-y !default;\n$input-group-addon-padding-x:           $input-padding-x !default;\n$input-group-addon-font-weight:         $input-font-weight !default;\n$input-group-addon-color:               $input-color !default;\n$input-group-addon-bg:                  var(--#{$prefix}tertiary-bg) !default;\n$input-group-addon-border-color:        $input-border-color !default;\n// scss-docs-end input-group-variables\n\n// scss-docs-start form-select-variables\n$form-select-padding-y:             $input-padding-y !default;\n$form-select-padding-x:             $input-padding-x !default;\n$form-select-font-family:           $input-font-family !default;\n$form-select-font-size:             $input-font-size !default;\n$form-select-indicator-padding:     $form-select-padding-x * 3 !default; // Extra padding for background-image\n$form-select-font-weight:           $input-font-weight !default;\n$form-select-line-height:           $input-line-height !default;\n$form-select-color:                 $input-color !default;\n$form-select-bg:                    $input-bg !default;\n$form-select-disabled-color:        null !default;\n$form-select-disabled-bg:           $input-disabled-bg !default;\n$form-select-disabled-border-color: $input-disabled-border-color !default;\n$form-select-bg-position:           right $form-select-padding-x center !default;\n$form-select-bg-size:               16px 12px !default; // In pixels because image dimensions\n$form-select-indicator-color:       $gray-800 !default;\n$form-select-indicator:             url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'><path fill='none' stroke='#{$form-select-indicator-color}' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' d='m2 5 6 6 6-6'/></svg>\") !default;\n\n$form-select-feedback-icon-padding-end: $form-select-padding-x * 2.5 + $form-select-indicator-padding !default;\n$form-select-feedback-icon-position:    center right $form-select-indicator-padding !default;\n$form-select-feedback-icon-size:        $input-height-inner-half $input-height-inner-half !default;\n\n$form-select-border-width:        $input-border-width !default;\n$form-select-border-color:        $input-border-color !default;\n$form-select-border-radius:       $input-border-radius !default;\n$form-select-box-shadow:          var(--#{$prefix}box-shadow-inset) !default;\n\n$form-select-focus-border-color:  $input-focus-border-color !default;\n$form-select-focus-width:         $input-focus-width !default;\n$form-select-focus-box-shadow:    0 0 0 $form-select-focus-width $input-btn-focus-color !default;\n\n$form-select-padding-y-sm:        $input-padding-y-sm !default;\n$form-select-padding-x-sm:        $input-padding-x-sm !default;\n$form-select-font-size-sm:        $input-font-size-sm !default;\n$form-select-border-radius-sm:    $input-border-radius-sm !default;\n\n$form-select-padding-y-lg:        $input-padding-y-lg !default;\n$form-select-padding-x-lg:        $input-padding-x-lg !default;\n$form-select-font-size-lg:        $input-font-size-lg !default;\n$form-select-border-radius-lg:    $input-border-radius-lg !default;\n\n$form-select-transition:          $input-transition !default;\n// scss-docs-end form-select-variables\n\n// scss-docs-start form-range-variables\n$form-range-track-width:          100% !default;\n$form-range-track-height:         .5rem !default;\n$form-range-track-cursor:         pointer !default;\n$form-range-track-bg:             var(--#{$prefix}secondary-bg) !default;\n$form-range-track-border-radius:  1rem !default;\n$form-range-track-box-shadow:     var(--#{$prefix}box-shadow-inset) !default;\n\n$form-range-thumb-width:                   1rem !default;\n$form-range-thumb-height:                  $form-range-thumb-width !default;\n$form-range-thumb-bg:                      $component-active-bg !default;\n$form-range-thumb-border:                  0 !default;\n$form-range-thumb-border-radius:           1rem !default;\n$form-range-thumb-box-shadow:              0 .1rem .25rem rgba($black, .1) !default;\n$form-range-thumb-focus-box-shadow:        0 0 0 1px $body-bg, $input-focus-box-shadow !default;\n$form-range-thumb-focus-box-shadow-width:  $input-focus-width !default; // For focus box shadow issue in Edge\n$form-range-thumb-active-bg:               tint-color($component-active-bg, 70%) !default;\n$form-range-thumb-disabled-bg:             var(--#{$prefix}secondary-color) !default;\n$form-range-thumb-transition:              background-color .15s ease-in-out, border-color .15s ease-in-out, box-shadow .15s ease-in-out !default;\n// scss-docs-end form-range-variables\n\n// scss-docs-start form-file-variables\n$form-file-button-color:          $input-color !default;\n$form-file-button-bg:             var(--#{$prefix}tertiary-bg) !default;\n$form-file-button-hover-bg:       var(--#{$prefix}secondary-bg) !default;\n// scss-docs-end form-file-variables\n\n// scss-docs-start form-floating-variables\n$form-floating-height:                  add(3.5rem, $input-height-border) !default;\n$form-floating-line-height:             1.25 !default;\n$form-floating-padding-x:               $input-padding-x !default;\n$form-floating-padding-y:               1rem !default;\n$form-floating-input-padding-t:         1.625rem !default;\n$form-floating-input-padding-b:         .625rem !default;\n$form-floating-label-height:            1.5em !default;\n$form-floating-label-opacity:           .65 !default;\n$form-floating-label-transform:         scale(.85) translateY(-.5rem) translateX(.15rem) !default;\n$form-floating-label-disabled-color:    $gray-600 !default;\n$form-floating-transition:              opacity .1s ease-in-out, transform .1s ease-in-out !default;\n// scss-docs-end form-floating-variables\n\n// Form validation\n\n// scss-docs-start form-feedback-variables\n$form-feedback-margin-top:          $form-text-margin-top !default;\n$form-feedback-font-size:           $form-text-font-size !default;\n$form-feedback-font-style:          $form-text-font-style !default;\n$form-feedback-valid-color:         $success !default;\n$form-feedback-invalid-color:       $danger !default;\n\n$form-feedback-icon-valid-color:    $form-feedback-valid-color !default;\n$form-feedback-icon-valid:          url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 8 8'><path fill='#{$form-feedback-icon-valid-color}' d='M2.3 6.73.6 4.53c-.4-1.04.46-1.4 1.1-.8l1.1 1.4 3.4-3.8c.6-.63 1.6-.27 1.2.7l-4 4.6c-.43.5-.8.4-1.1.1z'/></svg>\") !default;\n$form-feedback-icon-invalid-color:  $form-feedback-invalid-color !default;\n$form-feedback-icon-invalid:        url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 12 12' width='12' height='12' fill='none' stroke='#{$form-feedback-icon-invalid-color}'><circle cx='6' cy='6' r='4.5'/><path stroke-linejoin='round' d='M5.8 3.6h.4L6 6.5z'/><circle cx='6' cy='8.2' r='.6' fill='#{$form-feedback-icon-invalid-color}' stroke='none'/></svg>\") !default;\n// scss-docs-end form-feedback-variables\n\n// scss-docs-start form-validation-colors\n$form-valid-color:                  $form-feedback-valid-color !default;\n$form-valid-border-color:           $form-feedback-valid-color !default;\n$form-invalid-color:                $form-feedback-invalid-color !default;\n$form-invalid-border-color:         $form-feedback-invalid-color !default;\n// scss-docs-end form-validation-colors\n\n// scss-docs-start form-validation-states\n$form-validation-states: (\n  \"valid\": (\n    \"color\": var(--#{$prefix}form-valid-color),\n    \"icon\": $form-feedback-icon-valid,\n    \"tooltip-color\": #fff,\n    \"tooltip-bg-color\": var(--#{$prefix}success),\n    \"focus-box-shadow\": 0 0 $input-btn-focus-blur $input-focus-width rgba(var(--#{$prefix}success-rgb), $input-btn-focus-color-opacity),\n    \"border-color\": var(--#{$prefix}form-valid-border-color),\n  ),\n  \"invalid\": (\n    \"color\": var(--#{$prefix}form-invalid-color),\n    \"icon\": $form-feedback-icon-invalid,\n    \"tooltip-color\": #fff,\n    \"tooltip-bg-color\": var(--#{$prefix}danger),\n    \"focus-box-shadow\": 0 0 $input-btn-focus-blur $input-focus-width rgba(var(--#{$prefix}danger-rgb), $input-btn-focus-color-opacity),\n    \"border-color\": var(--#{$prefix}form-invalid-border-color),\n  )\n) !default;\n// scss-docs-end form-validation-states\n\n// Z-index master list\n//\n// Warning: Avoid customizing these values. They're used for a bird's eye view\n// of components dependent on the z-axis and are designed to all work together.\n\n// scss-docs-start zindex-stack\n$zindex-dropdown:                   1000 !default;\n$zindex-sticky:                     1020 !default;\n$zindex-fixed:                      1030 !default;\n$zindex-offcanvas-backdrop:         1040 !default;\n$zindex-offcanvas:                  1045 !default;\n$zindex-modal-backdrop:             1050 !default;\n$zindex-modal:                      1055 !default;\n$zindex-popover:                    1070 !default;\n$zindex-tooltip:                    1080 !default;\n$zindex-toast:                      1090 !default;\n// scss-docs-end zindex-stack\n\n// scss-docs-start zindex-levels-map\n$zindex-levels: (\n  n1: -1,\n  0: 0,\n  1: 1,\n  2: 2,\n  3: 3\n) !default;\n// scss-docs-end zindex-levels-map\n\n\n// Navs\n\n// scss-docs-start nav-variables\n$nav-link-padding-y:                .5rem !default;\n$nav-link-padding-x:                1rem !default;\n$nav-link-font-size:                null !default;\n$nav-link-font-weight:              null !default;\n$nav-link-color:                    var(--#{$prefix}link-color) !default;\n$nav-link-hover-color:              var(--#{$prefix}link-hover-color) !default;\n$nav-link-transition:               color .15s ease-in-out, background-color .15s ease-in-out, border-color .15s ease-in-out !default;\n$nav-link-disabled-color:           var(--#{$prefix}secondary-color) !default;\n$nav-link-focus-box-shadow:         $focus-ring-box-shadow !default;\n\n$nav-tabs-border-color:             var(--#{$prefix}border-color) !default;\n$nav-tabs-border-width:             var(--#{$prefix}border-width) !default;\n$nav-tabs-border-radius:            var(--#{$prefix}border-radius) !default;\n$nav-tabs-link-hover-border-color:  var(--#{$prefix}secondary-bg) var(--#{$prefix}secondary-bg) $nav-tabs-border-color !default;\n$nav-tabs-link-active-color:        var(--#{$prefix}emphasis-color) !default;\n$nav-tabs-link-active-bg:           var(--#{$prefix}body-bg) !default;\n$nav-tabs-link-active-border-color: var(--#{$prefix}border-color) var(--#{$prefix}border-color) $nav-tabs-link-active-bg !default;\n\n$nav-pills-border-radius:           var(--#{$prefix}border-radius) !default;\n$nav-pills-link-active-color:       $component-active-color !default;\n$nav-pills-link-active-bg:          $component-active-bg !default;\n\n$nav-underline-gap:                 1rem !default;\n$nav-underline-border-width:        .125rem !default;\n$nav-underline-link-active-color:   var(--#{$prefix}emphasis-color) !default;\n// scss-docs-end nav-variables\n\n\n// Navbar\n\n// scss-docs-start navbar-variables\n$navbar-padding-y:                  $spacer * .5 !default;\n$navbar-padding-x:                  null !default;\n\n$navbar-nav-link-padding-x:         .5rem !default;\n\n$navbar-brand-font-size:            $font-size-lg !default;\n// Compute the navbar-brand padding-y so the navbar-brand will have the same height as navbar-text and nav-link\n$nav-link-height:                   $font-size-base * $line-height-base + $nav-link-padding-y * 2 !default;\n$navbar-brand-height:               $navbar-brand-font-size * $line-height-base !default;\n$navbar-brand-padding-y:            ($nav-link-height - $navbar-brand-height) * .5 !default;\n$navbar-brand-margin-end:           1rem !default;\n\n$navbar-toggler-padding-y:          .25rem !default;\n$navbar-toggler-padding-x:          .75rem !default;\n$navbar-toggler-font-size:          $font-size-lg !default;\n$navbar-toggler-border-radius:      $btn-border-radius !default;\n$navbar-toggler-focus-width:        $btn-focus-width !default;\n$navbar-toggler-transition:         box-shadow .15s ease-in-out !default;\n\n$navbar-light-color:                rgba(var(--#{$prefix}emphasis-color-rgb), .65) !default;\n$navbar-light-hover-color:          rgba(var(--#{$prefix}emphasis-color-rgb), .8) !default;\n$navbar-light-active-color:         rgba(var(--#{$prefix}emphasis-color-rgb), 1) !default;\n$navbar-light-disabled-color:       rgba(var(--#{$prefix}emphasis-color-rgb), .3) !default;\n$navbar-light-icon-color:           rgba($body-color, .75) !default;\n$navbar-light-toggler-icon-bg:      url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'><path stroke='#{$navbar-light-icon-color}' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/></svg>\") !default;\n$navbar-light-toggler-border-color: rgba(var(--#{$prefix}emphasis-color-rgb), .15) !default;\n$navbar-light-brand-color:          $navbar-light-active-color !default;\n$navbar-light-brand-hover-color:    $navbar-light-active-color !default;\n// scss-docs-end navbar-variables\n\n// scss-docs-start navbar-dark-variables\n$navbar-dark-color:                 rgba($white, .55) !default;\n$navbar-dark-hover-color:           rgba($white, .75) !default;\n$navbar-dark-active-color:          $white !default;\n$navbar-dark-disabled-color:        rgba($white, .25) !default;\n$navbar-dark-icon-color:            $navbar-dark-color !default;\n$navbar-dark-toggler-icon-bg:       url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'><path stroke='#{$navbar-dark-icon-color}' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/></svg>\") !default;\n$navbar-dark-toggler-border-color:  rgba($white, .1) !default;\n$navbar-dark-brand-color:           $navbar-dark-active-color !default;\n$navbar-dark-brand-hover-color:     $navbar-dark-active-color !default;\n// scss-docs-end navbar-dark-variables\n\n\n// Dropdowns\n//\n// Dropdown menu container and contents.\n\n// scss-docs-start dropdown-variables\n$dropdown-min-width:                10rem !default;\n$dropdown-padding-x:                0 !default;\n$dropdown-padding-y:                .5rem !default;\n$dropdown-spacer:                   .125rem !default;\n$dropdown-font-size:                $font-size-base !default;\n$dropdown-color:                    var(--#{$prefix}body-color) !default;\n$dropdown-bg:                       var(--#{$prefix}body-bg) !default;\n$dropdown-border-color:             var(--#{$prefix}border-color-translucent) !default;\n$dropdown-border-radius:            var(--#{$prefix}border-radius) !default;\n$dropdown-border-width:             var(--#{$prefix}border-width) !default;\n$dropdown-inner-border-radius:      calc(#{$dropdown-border-radius} - #{$dropdown-border-width}) !default; // stylelint-disable-line function-disallowed-list\n$dropdown-divider-bg:               $dropdown-border-color !default;\n$dropdown-divider-margin-y:         $spacer * .5 !default;\n$dropdown-box-shadow:               var(--#{$prefix}box-shadow) !default;\n\n$dropdown-link-color:               var(--#{$prefix}body-color) !default;\n$dropdown-link-hover-color:         $dropdown-link-color !default;\n$dropdown-link-hover-bg:            var(--#{$prefix}tertiary-bg) !default;\n\n$dropdown-link-active-color:        $component-active-color !default;\n$dropdown-link-active-bg:           $component-active-bg !default;\n\n$dropdown-link-disabled-color:      var(--#{$prefix}tertiary-color) !default;\n\n$dropdown-item-padding-y:           $spacer * .25 !default;\n$dropdown-item-padding-x:           $spacer !default;\n\n$dropdown-header-color:             $gray-600 !default;\n$dropdown-header-padding-x:         $dropdown-item-padding-x !default;\n$dropdown-header-padding-y:         $dropdown-padding-y !default;\n// fusv-disable\n$dropdown-header-padding:           $dropdown-header-padding-y $dropdown-header-padding-x !default; // Deprecated in v5.2.0\n// fusv-enable\n// scss-docs-end dropdown-variables\n\n// scss-docs-start dropdown-dark-variables\n$dropdown-dark-color:               $gray-300 !default;\n$dropdown-dark-bg:                  $gray-800 !default;\n$dropdown-dark-border-color:        $dropdown-border-color !default;\n$dropdown-dark-divider-bg:          $dropdown-divider-bg !default;\n$dropdown-dark-box-shadow:          null !default;\n$dropdown-dark-link-color:          $dropdown-dark-color !default;\n$dropdown-dark-link-hover-color:    $white !default;\n$dropdown-dark-link-hover-bg:       rgba($white, .15) !default;\n$dropdown-dark-link-active-color:   $dropdown-link-active-color !default;\n$dropdown-dark-link-active-bg:      $dropdown-link-active-bg !default;\n$dropdown-dark-link-disabled-color: $gray-500 !default;\n$dropdown-dark-header-color:        $gray-500 !default;\n// scss-docs-end dropdown-dark-variables\n\n\n// Pagination\n\n// scss-docs-start pagination-variables\n$pagination-padding-y:              .375rem !default;\n$pagination-padding-x:              .75rem !default;\n$pagination-padding-y-sm:           .25rem !default;\n$pagination-padding-x-sm:           .5rem !default;\n$pagination-padding-y-lg:           .75rem !default;\n$pagination-padding-x-lg:           1.5rem !default;\n\n$pagination-font-size:              $font-size-base !default;\n\n$pagination-color:                  var(--#{$prefix}link-color) !default;\n$pagination-bg:                     var(--#{$prefix}body-bg) !default;\n$pagination-border-radius:          var(--#{$prefix}border-radius) !default;\n$pagination-border-width:           var(--#{$prefix}border-width) !default;\n$pagination-margin-start:           calc(#{$pagination-border-width} * -1) !default; // stylelint-disable-line function-disallowed-list\n$pagination-border-color:           var(--#{$prefix}border-color) !default;\n\n$pagination-focus-color:            var(--#{$prefix}link-hover-color) !default;\n$pagination-focus-bg:               var(--#{$prefix}secondary-bg) !default;\n$pagination-focus-box-shadow:       $focus-ring-box-shadow !default;\n$pagination-focus-outline:          0 !default;\n\n$pagination-hover-color:            var(--#{$prefix}link-hover-color) !default;\n$pagination-hover-bg:               var(--#{$prefix}tertiary-bg) !default;\n$pagination-hover-border-color:     var(--#{$prefix}border-color) !default; // Todo in v6: remove this?\n\n$pagination-active-color:           $component-active-color !default;\n$pagination-active-bg:              $component-active-bg !default;\n$pagination-active-border-color:    $component-active-bg !default;\n\n$pagination-disabled-color:         var(--#{$prefix}secondary-color) !default;\n$pagination-disabled-bg:            var(--#{$prefix}secondary-bg) !default;\n$pagination-disabled-border-color:  var(--#{$prefix}border-color) !default;\n\n$pagination-transition:              color .15s ease-in-out, background-color .15s ease-in-out, border-color .15s ease-in-out, box-shadow .15s ease-in-out !default;\n\n$pagination-border-radius-sm:       var(--#{$prefix}border-radius-sm) !default;\n$pagination-border-radius-lg:       var(--#{$prefix}border-radius-lg) !default;\n// scss-docs-end pagination-variables\n\n\n// Placeholders\n\n// scss-docs-start placeholders\n$placeholder-opacity-max:           .5 !default;\n$placeholder-opacity-min:           .2 !default;\n// scss-docs-end placeholders\n\n// Cards\n\n// scss-docs-start card-variables\n$card-spacer-y:                     $spacer !default;\n$card-spacer-x:                     $spacer !default;\n$card-title-spacer-y:               $spacer * .5 !default;\n$card-title-color:                  null !default;\n$card-subtitle-color:               null !default;\n$card-border-width:                 var(--#{$prefix}border-width) !default;\n$card-border-color:                 var(--#{$prefix}border-color-translucent) !default;\n$card-border-radius:                var(--#{$prefix}border-radius) !default;\n$card-box-shadow:                   null !default;\n$card-inner-border-radius:          subtract($card-border-radius, $card-border-width) !default;\n$card-cap-padding-y:                $card-spacer-y * .5 !default;\n$card-cap-padding-x:                $card-spacer-x !default;\n$card-cap-bg:                       rgba(var(--#{$prefix}body-color-rgb), .03) !default;\n$card-cap-color:                    null !default;\n$card-height:                       null !default;\n$card-color:                        null !default;\n$card-bg:                           var(--#{$prefix}body-bg) !default;\n$card-img-overlay-padding:          $spacer !default;\n$card-group-margin:                 $grid-gutter-width * .5 !default;\n// scss-docs-end card-variables\n\n// Accordion\n\n// scss-docs-start accordion-variables\n$accordion-padding-y:                     1rem !default;\n$accordion-padding-x:                     1.25rem !default;\n$accordion-color:                         var(--#{$prefix}body-color) !default;\n$accordion-bg:                            var(--#{$prefix}body-bg) !default;\n$accordion-border-width:                  var(--#{$prefix}border-width) !default;\n$accordion-border-color:                  var(--#{$prefix}border-color) !default;\n$accordion-border-radius:                 var(--#{$prefix}border-radius) !default;\n$accordion-inner-border-radius:           subtract($accordion-border-radius, $accordion-border-width) !default;\n\n$accordion-body-padding-y:                $accordion-padding-y !default;\n$accordion-body-padding-x:                $accordion-padding-x !default;\n\n$accordion-button-padding-y:              $accordion-padding-y !default;\n$accordion-button-padding-x:              $accordion-padding-x !default;\n$accordion-button-color:                  var(--#{$prefix}body-color) !default;\n$accordion-button-bg:                     var(--#{$prefix}accordion-bg) !default;\n$accordion-transition:                    $btn-transition, border-radius .15s ease !default;\n$accordion-button-active-bg:              var(--#{$prefix}primary-bg-subtle) !default;\n$accordion-button-active-color:           var(--#{$prefix}primary-text-emphasis) !default;\n\n$accordion-button-focus-border-color:     $input-focus-border-color !default;\n$accordion-button-focus-box-shadow:       $btn-focus-box-shadow !default;\n\n$accordion-icon-width:                    1.25rem !default;\n$accordion-icon-color:                    $body-color !default;\n$accordion-icon-active-color:             $primary-text-emphasis !default;\n$accordion-icon-transition:               transform .2s ease-in-out !default;\n$accordion-icon-transform:                rotate(-180deg) !default;\n\n$accordion-button-icon:         url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$accordion-icon-color}'><path fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/></svg>\") !default;\n$accordion-button-active-icon:  url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$accordion-icon-active-color}'><path fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/></svg>\") !default;\n// scss-docs-end accordion-variables\n\n// Tooltips\n\n// scss-docs-start tooltip-variables\n$tooltip-font-size:                 $font-size-sm !default;\n$tooltip-max-width:                 200px !default;\n$tooltip-color:                     var(--#{$prefix}body-bg) !default;\n$tooltip-bg:                        var(--#{$prefix}emphasis-color) !default;\n$tooltip-border-radius:             var(--#{$prefix}border-radius) !default;\n$tooltip-opacity:                   .9 !default;\n$tooltip-padding-y:                 $spacer * .25 !default;\n$tooltip-padding-x:                 $spacer * .5 !default;\n$tooltip-margin:                    null !default; // TODO: remove this in v6\n\n$tooltip-arrow-width:               .8rem !default;\n$tooltip-arrow-height:              .4rem !default;\n// fusv-disable\n$tooltip-arrow-color:               null !default; // Deprecated in Bootstrap 5.2.0 for CSS variables\n// fusv-enable\n// scss-docs-end tooltip-variables\n\n// Form tooltips must come after regular tooltips\n// scss-docs-start tooltip-feedback-variables\n$form-feedback-tooltip-padding-y:     $tooltip-padding-y !default;\n$form-feedback-tooltip-padding-x:     $tooltip-padding-x !default;\n$form-feedback-tooltip-font-size:     $tooltip-font-size !default;\n$form-feedback-tooltip-line-height:   null !default;\n$form-feedback-tooltip-opacity:       $tooltip-opacity !default;\n$form-feedback-tooltip-border-radius: $tooltip-border-radius !default;\n// scss-docs-end tooltip-feedback-variables\n\n\n// Popovers\n\n// scss-docs-start popover-variables\n$popover-font-size:                 $font-size-sm !default;\n$popover-bg:                        var(--#{$prefix}body-bg) !default;\n$popover-max-width:                 276px !default;\n$popover-border-width:              var(--#{$prefix}border-width) !default;\n$popover-border-color:              var(--#{$prefix}border-color-translucent) !default;\n$popover-border-radius:             var(--#{$prefix}border-radius-lg) !default;\n$popover-inner-border-radius:       calc(#{$popover-border-radius} - #{$popover-border-width}) !default; // stylelint-disable-line function-disallowed-list\n$popover-box-shadow:                var(--#{$prefix}box-shadow) !default;\n\n$popover-header-font-size:          $font-size-base !default;\n$popover-header-bg:                 var(--#{$prefix}secondary-bg) !default;\n$popover-header-color:              $headings-color !default;\n$popover-header-padding-y:          .5rem !default;\n$popover-header-padding-x:          $spacer !default;\n\n$popover-body-color:                var(--#{$prefix}body-color) !default;\n$popover-body-padding-y:            $spacer !default;\n$popover-body-padding-x:            $spacer !default;\n\n$popover-arrow-width:               1rem !default;\n$popover-arrow-height:              .5rem !default;\n// scss-docs-end popover-variables\n\n// fusv-disable\n// Deprecated in Bootstrap 5.2.0 for CSS variables\n$popover-arrow-color:               $popover-bg !default;\n$popover-arrow-outer-color:         var(--#{$prefix}border-color-translucent) !default;\n// fusv-enable\n\n\n// Toasts\n\n// scss-docs-start toast-variables\n$toast-max-width:                   350px !default;\n$toast-padding-x:                   .75rem !default;\n$toast-padding-y:                   .5rem !default;\n$toast-font-size:                   .875rem !default;\n$toast-color:                       null !default;\n$toast-background-color:            rgba(var(--#{$prefix}body-bg-rgb), .85) !default;\n$toast-border-width:                var(--#{$prefix}border-width) !default;\n$toast-border-color:                var(--#{$prefix}border-color-translucent) !default;\n$toast-border-radius:               var(--#{$prefix}border-radius) !default;\n$toast-box-shadow:                  var(--#{$prefix}box-shadow) !default;\n$toast-spacing:                     $container-padding-x !default;\n\n$toast-header-color:                var(--#{$prefix}secondary-color) !default;\n$toast-header-background-color:     rgba(var(--#{$prefix}body-bg-rgb), .85) !default;\n$toast-header-border-color:         $toast-border-color !default;\n// scss-docs-end toast-variables\n\n\n// Badges\n\n// scss-docs-start badge-variables\n$badge-font-size:                   .75em !default;\n$badge-font-weight:                 $font-weight-bold !default;\n$badge-color:                       $white !default;\n$badge-padding-y:                   .35em !default;\n$badge-padding-x:                   .65em !default;\n$badge-border-radius:               var(--#{$prefix}border-radius) !default;\n// scss-docs-end badge-variables\n\n\n// Modals\n\n// scss-docs-start modal-variables\n$modal-inner-padding:               $spacer !default;\n\n$modal-footer-margin-between:       .5rem !default;\n\n$modal-dialog-margin:               .5rem !default;\n$modal-dialog-margin-y-sm-up:       1.75rem !default;\n\n$modal-title-line-height:           $line-height-base !default;\n\n$modal-content-color:               null !default;\n$modal-content-bg:                  var(--#{$prefix}body-bg) !default;\n$modal-content-border-color:        var(--#{$prefix}border-color-translucent) !default;\n$modal-content-border-width:        var(--#{$prefix}border-width) !default;\n$modal-content-border-radius:       var(--#{$prefix}border-radius-lg) !default;\n$modal-content-inner-border-radius: subtract($modal-content-border-radius, $modal-content-border-width) !default;\n$modal-content-box-shadow-xs:       var(--#{$prefix}box-shadow-sm) !default;\n$modal-content-box-shadow-sm-up:    var(--#{$prefix}box-shadow) !default;\n\n$modal-backdrop-bg:                 $black !default;\n$modal-backdrop-opacity:            .5 !default;\n\n$modal-header-border-color:         var(--#{$prefix}border-color) !default;\n$modal-header-border-width:         $modal-content-border-width !default;\n$modal-header-padding-y:            $modal-inner-padding !default;\n$modal-header-padding-x:            $modal-inner-padding !default;\n$modal-header-padding:              $modal-header-padding-y $modal-header-padding-x !default; // Keep this for backwards compatibility\n\n$modal-footer-bg:                   null !default;\n$modal-footer-border-color:         $modal-header-border-color !default;\n$modal-footer-border-width:         $modal-header-border-width !default;\n\n$modal-sm:                          300px !default;\n$modal-md:                          500px !default;\n$modal-lg:                          800px !default;\n$modal-xl:                          1140px !default;\n\n$modal-fade-transform:              translate(0, -50px) !default;\n$modal-show-transform:              none !default;\n$modal-transition:                  transform .3s ease-out !default;\n$modal-scale-transform:             scale(1.02) !default;\n// scss-docs-end modal-variables\n\n\n// Alerts\n//\n// Define alert colors, border radius, and padding.\n\n// scss-docs-start alert-variables\n$alert-padding-y:               $spacer !default;\n$alert-padding-x:               $spacer !default;\n$alert-margin-bottom:           1rem !default;\n$alert-border-radius:           var(--#{$prefix}border-radius) !default;\n$alert-link-font-weight:        $font-weight-bold !default;\n$alert-border-width:            var(--#{$prefix}border-width) !default;\n$alert-dismissible-padding-r:   $alert-padding-x * 3 !default; // 3x covers width of x plus default padding on either side\n// scss-docs-end alert-variables\n\n// fusv-disable\n$alert-bg-scale:                -80% !default; // Deprecated in v5.2.0, to be removed in v6\n$alert-border-scale:            -70% !default; // Deprecated in v5.2.0, to be removed in v6\n$alert-color-scale:             40% !default; // Deprecated in v5.2.0, to be removed in v6\n// fusv-enable\n\n// Progress bars\n\n// scss-docs-start progress-variables\n$progress-height:                   1rem !default;\n$progress-font-size:                $font-size-base * .75 !default;\n$progress-bg:                       var(--#{$prefix}secondary-bg) !default;\n$progress-border-radius:            var(--#{$prefix}border-radius) !default;\n$progress-box-shadow:               var(--#{$prefix}box-shadow-inset) !default;\n$progress-bar-color:                $white !default;\n$progress-bar-bg:                   $primary !default;\n$progress-bar-animation-timing:     1s linear infinite !default;\n$progress-bar-transition:           width .6s ease !default;\n// scss-docs-end progress-variables\n\n\n// List group\n\n// scss-docs-start list-group-variables\n$list-group-color:                  var(--#{$prefix}body-color) !default;\n$list-group-bg:                     var(--#{$prefix}body-bg) !default;\n$list-group-border-color:           var(--#{$prefix}border-color) !default;\n$list-group-border-width:           var(--#{$prefix}border-width) !default;\n$list-group-border-radius:          var(--#{$prefix}border-radius) !default;\n\n$list-group-item-padding-y:         $spacer * .5 !default;\n$list-group-item-padding-x:         $spacer !default;\n// fusv-disable\n$list-group-item-bg-scale:          -80% !default; // Deprecated in v5.3.0\n$list-group-item-color-scale:       40% !default; // Deprecated in v5.3.0\n// fusv-enable\n\n$list-group-hover-bg:               var(--#{$prefix}tertiary-bg) !default;\n$list-group-active-color:           $component-active-color !default;\n$list-group-active-bg:              $component-active-bg !default;\n$list-group-active-border-color:    $list-group-active-bg !default;\n\n$list-group-disabled-color:         var(--#{$prefix}secondary-color) !default;\n$list-group-disabled-bg:            $list-group-bg !default;\n\n$list-group-action-color:           var(--#{$prefix}secondary-color) !default;\n$list-group-action-hover-color:     var(--#{$prefix}emphasis-color) !default;\n\n$list-group-action-active-color:    var(--#{$prefix}body-color) !default;\n$list-group-action-active-bg:       var(--#{$prefix}secondary-bg) !default;\n// scss-docs-end list-group-variables\n\n\n// Image thumbnails\n\n// scss-docs-start thumbnail-variables\n$thumbnail-padding:                 .25rem !default;\n$thumbnail-bg:                      var(--#{$prefix}body-bg) !default;\n$thumbnail-border-width:            var(--#{$prefix}border-width) !default;\n$thumbnail-border-color:            var(--#{$prefix}border-color) !default;\n$thumbnail-border-radius:           var(--#{$prefix}border-radius) !default;\n$thumbnail-box-shadow:              var(--#{$prefix}box-shadow-sm) !default;\n// scss-docs-end thumbnail-variables\n\n\n// Figures\n\n// scss-docs-start figure-variables\n$figure-caption-font-size:          $small-font-size !default;\n$figure-caption-color:              var(--#{$prefix}secondary-color) !default;\n// scss-docs-end figure-variables\n\n\n// Breadcrumbs\n\n// scss-docs-start breadcrumb-variables\n$breadcrumb-font-size:              null !default;\n$breadcrumb-padding-y:              0 !default;\n$breadcrumb-padding-x:              0 !default;\n$breadcrumb-item-padding-x:         .5rem !default;\n$breadcrumb-margin-bottom:          1rem !default;\n$breadcrumb-bg:                     null !default;\n$breadcrumb-divider-color:          var(--#{$prefix}secondary-color) !default;\n$breadcrumb-active-color:           var(--#{$prefix}secondary-color) !default;\n$breadcrumb-divider:                quote(\"/\") !default;\n$breadcrumb-divider-flipped:        $breadcrumb-divider !default;\n$breadcrumb-border-radius:          null !default;\n// scss-docs-end breadcrumb-variables\n\n// Carousel\n\n// scss-docs-start carousel-variables\n$carousel-control-color:             $white !default;\n$carousel-control-width:             15% !default;\n$carousel-control-opacity:           .5 !default;\n$carousel-control-hover-opacity:     .9 !default;\n$carousel-control-transition:        opacity .15s ease !default;\n\n$carousel-indicator-width:           30px !default;\n$carousel-indicator-height:          3px !default;\n$carousel-indicator-hit-area-height: 10px !default;\n$carousel-indicator-spacer:          3px !default;\n$carousel-indicator-opacity:         .5 !default;\n$carousel-indicator-active-bg:       $white !default;\n$carousel-indicator-active-opacity:  1 !default;\n$carousel-indicator-transition:      opacity .6s ease !default;\n\n$carousel-caption-width:             70% !default;\n$carousel-caption-color:             $white !default;\n$carousel-caption-padding-y:         1.25rem !default;\n$carousel-caption-spacer:            1.25rem !default;\n\n$carousel-control-icon-width:        2rem !default;\n\n$carousel-control-prev-icon-bg:      url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$carousel-control-color}'><path d='M11.354 1.646a.5.5 0 0 1 0 .708L5.707 8l5.647 5.646a.5.5 0 0 1-.708.708l-6-6a.5.5 0 0 1 0-.708l6-6a.5.5 0 0 1 .708 0z'/></svg>\") !default;\n$carousel-control-next-icon-bg:      url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$carousel-control-color}'><path d='M4.646 1.646a.5.5 0 0 1 .708 0l6 6a.5.5 0 0 1 0 .708l-6 6a.5.5 0 0 1-.708-.708L10.293 8 4.646 2.354a.5.5 0 0 1 0-.708z'/></svg>\") !default;\n\n$carousel-transition-duration:       .6s !default;\n$carousel-transition:                transform $carousel-transition-duration ease-in-out !default; // Define transform transition first if using multiple transitions (e.g., `transform 2s ease, opacity .5s ease-out`)\n// scss-docs-end carousel-variables\n\n// scss-docs-start carousel-dark-variables\n$carousel-dark-indicator-active-bg:  $black !default;\n$carousel-dark-caption-color:        $black !default;\n$carousel-dark-control-icon-filter:  invert(1) grayscale(100) !default;\n// scss-docs-end carousel-dark-variables\n\n\n// Spinners\n\n// scss-docs-start spinner-variables\n$spinner-width:           2rem !default;\n$spinner-height:          $spinner-width !default;\n$spinner-vertical-align:  -.125em !default;\n$spinner-border-width:    .25em !default;\n$spinner-animation-speed: .75s !default;\n\n$spinner-width-sm:        1rem !default;\n$spinner-height-sm:       $spinner-width-sm !default;\n$spinner-border-width-sm: .2em !default;\n// scss-docs-end spinner-variables\n\n\n// Close\n\n// scss-docs-start close-variables\n$btn-close-width:            1em !default;\n$btn-close-height:           $btn-close-width !default;\n$btn-close-padding-x:        .25em !default;\n$btn-close-padding-y:        $btn-close-padding-x !default;\n$btn-close-color:            $black !default;\n$btn-close-bg:               url(\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='#{$btn-close-color}'><path d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/></svg>\") !default;\n$btn-close-focus-shadow:     $focus-ring-box-shadow !default;\n$btn-close-opacity:          .5 !default;\n$btn-close-hover-opacity:    .75 !default;\n$btn-close-focus-opacity:    1 !default;\n$btn-close-disabled-opacity: .25 !default;\n$btn-close-white-filter:     invert(1) grayscale(100%) brightness(200%) !default;\n// scss-docs-end close-variables\n\n\n// Offcanvas\n\n// scss-docs-start offcanvas-variables\n$offcanvas-padding-y:               $modal-inner-padding !default;\n$offcanvas-padding-x:               $modal-inner-padding !default;\n$offcanvas-horizontal-width:        400px !default;\n$offcanvas-vertical-height:         30vh !default;\n$offcanvas-transition-duration:     .3s !default;\n$offcanvas-border-color:            $modal-content-border-color !default;\n$offcanvas-border-width:            $modal-content-border-width !default;\n$offcanvas-title-line-height:       $modal-title-line-height !default;\n$offcanvas-bg-color:                var(--#{$prefix}body-bg) !default;\n$offcanvas-color:                   var(--#{$prefix}body-color) !default;\n$offcanvas-box-shadow:              $modal-content-box-shadow-xs !default;\n$offcanvas-backdrop-bg:             $modal-backdrop-bg !default;\n$offcanvas-backdrop-opacity:        $modal-backdrop-opacity !default;\n// scss-docs-end offcanvas-variables\n\n// Code\n\n$code-font-size:                    $small-font-size !default;\n$code-color:                        $pink !default;\n\n$kbd-padding-y:                     .1875rem !default;\n$kbd-padding-x:                     .375rem !default;\n$kbd-font-size:                     $code-font-size !default;\n$kbd-color:                         var(--#{$prefix}body-bg) !default;\n$kbd-bg:                            var(--#{$prefix}body-color) !default;\n$nested-kbd-font-weight:            null !default; // Deprecated in v5.2.0, removing in v6\n\n$pre-color:                         null !default;\n","/***\n * Rules for the UX/UI of skip navigation link btn. \n *It's only visible to people\n * navigating with keyboard for accessibility purposes\n * ref: https://www.youtube.com/watch?v=VUR0I5mqq7I\n ***/\n\n.skip-link {\n  position: fixed;\n  top: 0;\n  left: 0;\n  right: 0;\n  text-align: center;\n  background-color: var(--pst-color-warning);\n  // Ensure we are using a WCAG conformant colour\n  color: var(--pst-color-warning-text) !important;\n  padding: 0.5rem;\n  z-index: $zindex-modal;\n  border-bottom: 1px solid var(--pst-color-border);\n\n  // This shows / hides the button\n  transform: translateY(-100%);\n  transition: transform 150ms ease-in-out;\n  &:focus {\n    transform: translateY(0%);\n    // ensure this is visible\n    outline: 3px solid $foundation-black;\n  }\n}\n",".bd-container {\n  flex-grow: 1;\n  display: flex;\n  justify-content: center;\n\n  .bd-container__inner {\n    display: flex;\n  }\n}\n\n.bd-page-width {\n  width: 100%;\n  @include media-breakpoint-up(lg) {\n    max-width: $breakpoint-page-width;\n  }\n}\n","// Breakpoint viewport sizes and media queries.\n//\n// Breakpoints are defined as a map of (name: minimum width), order from small to large:\n//\n//    (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px)\n//\n// The map defined in the `$grid-breakpoints` global variable is used as the `$breakpoints` argument by default.\n\n// Name of the next breakpoint, or null for the last breakpoint.\n//\n//    >> breakpoint-next(sm)\n//    md\n//    >> breakpoint-next(sm, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    md\n//    >> breakpoint-next(sm, $breakpoint-names: (xs sm md lg xl xxl))\n//    md\n@function breakpoint-next($name, $breakpoints: $grid-breakpoints, $breakpoint-names: map-keys($breakpoints)) {\n  $n: index($breakpoint-names, $name);\n  @if not $n {\n    @error \"breakpoint `#{$name}` not found in `#{$breakpoints}`\";\n  }\n  @return if($n < length($breakpoint-names), nth($breakpoint-names, $n + 1), null);\n}\n\n// Minimum breakpoint width. Null for the smallest (first) breakpoint.\n//\n//    >> breakpoint-min(sm, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    576px\n@function breakpoint-min($name, $breakpoints: $grid-breakpoints) {\n  $min: map-get($breakpoints, $name);\n  @return if($min != 0, $min, null);\n}\n\n// Maximum breakpoint width.\n// The maximum value is reduced by 0.02px to work around the limitations of\n// `min-` and `max-` prefixes and viewports with fractional widths.\n// See https://www.w3.org/TR/mediaqueries-4/#mq-min-max\n// Uses 0.02px rather than 0.01px to work around a current rounding bug in Safari.\n// See https://bugs.webkit.org/show_bug.cgi?id=178261\n//\n//    >> breakpoint-max(md, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    767.98px\n@function breakpoint-max($name, $breakpoints: $grid-breakpoints) {\n  $max: map-get($breakpoints, $name);\n  @return if($max and $max > 0, $max - .02, null);\n}\n\n// Returns a blank string if smallest breakpoint, otherwise returns the name with a dash in front.\n// Useful for making responsive utilities.\n//\n//    >> breakpoint-infix(xs, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    \"\"  (Returns a blank string)\n//    >> breakpoint-infix(sm, (xs: 0, sm: 576px, md: 768px, lg: 992px, xl: 1200px, xxl: 1400px))\n//    \"-sm\"\n@function breakpoint-infix($name, $breakpoints: $grid-breakpoints) {\n  @return if(breakpoint-min($name, $breakpoints) == null, \"\", \"-#{$name}\");\n}\n\n// Media of at least the minimum breakpoint width. No query for the smallest breakpoint.\n// Makes the @content apply to the given breakpoint and wider.\n@mixin media-breakpoint-up($name, $breakpoints: $grid-breakpoints) {\n  $min: breakpoint-min($name, $breakpoints);\n  @if $min {\n    @media (min-width: $min) {\n      @content;\n    }\n  } @else {\n    @content;\n  }\n}\n\n// Media of at most the maximum breakpoint width. No query for the largest breakpoint.\n// Makes the @content apply to the given breakpoint and narrower.\n@mixin media-breakpoint-down($name, $breakpoints: $grid-breakpoints) {\n  $max: breakpoint-max($name, $breakpoints);\n  @if $max {\n    @media (max-width: $max) {\n      @content;\n    }\n  } @else {\n    @content;\n  }\n}\n\n// Media that spans multiple breakpoint widths.\n// Makes the @content apply between the min and max breakpoints\n@mixin media-breakpoint-between($lower, $upper, $breakpoints: $grid-breakpoints) {\n  $min: breakpoint-min($lower, $breakpoints);\n  $max: breakpoint-max($upper, $breakpoints);\n\n  @if $min != null and $max != null {\n    @media (min-width: $min) and (max-width: $max) {\n      @content;\n    }\n  } @else if $max == null {\n    @include media-breakpoint-up($lower, $breakpoints) {\n      @content;\n    }\n  } @else if $min == null {\n    @include media-breakpoint-down($upper, $breakpoints) {\n      @content;\n    }\n  }\n}\n\n// Media between the breakpoint's minimum and maximum widths.\n// No minimum for the smallest breakpoint, and no maximum for the largest one.\n// Makes the @content apply only to the given breakpoint, not viewports any wider or narrower.\n@mixin media-breakpoint-only($name, $breakpoints: $grid-breakpoints) {\n  $min:  breakpoint-min($name, $breakpoints);\n  $next: breakpoint-next($name, $breakpoints);\n  $max:  breakpoint-max($next, $breakpoints);\n\n  @if $min != null and $max != null {\n    @media (min-width: $min) and (max-width: $max) {\n      @content;\n    }\n  } @else if $max == null {\n    @include media-breakpoint-up($name, $breakpoints) {\n      @content;\n    }\n  } @else if $min == null {\n    @include media-breakpoint-down($next, $breakpoints) {\n      @content;\n    }\n  }\n}\n",".bd-header-version-warning,\n.bd-header-announcement {\n  min-height: 3rem;\n  width: 100%;\n  display: flex;\n  position: relative;\n  align-items: center;\n  justify-content: center;\n  text-align: center;\n  padding: 0.5rem 12.5%; // Horizontal padding so the width is 75%\n  // One breakpoint less than $breakpoint-sidebar-primary. See variables/_layout.scss for more info.\n  @include media-breakpoint-down(lg) {\n    // Announcements can take a bit more width on mobile\n    padding: 0.5rem 2%;\n  }\n\n  p {\n    font-weight: bold;\n    margin: 0;\n  }\n\n  &:after {\n    position: absolute;\n    width: 100%;\n    height: 100%;\n    left: 0;\n    top: 0;\n    content: \"\";\n    z-index: -1; // So it doesn't hover over the content\n  }\n\n  &:empty {\n    display: none;\n  }\n\n  // Ensure there is enough contrast against the background\n  a {\n    color: var(--pst-color-inline-code-links);\n  }\n}\n\n// Bg color is now defined in the theme color palette - using our secondary color\n.bd-header-announcement {\n  &:after {\n    background-color: var(--pst-color-secondary-bg);\n  }\n}\n\n.bd-header-version-warning {\n  &:after {\n    background-color: var(--pst-color-danger-bg);\n  }\n}\n","/**\n * Main content area\n */\n.bd-main {\n  flex-grow: 1;\n  flex-direction: column;\n  display: flex;\n  min-width: 0;\n\n  .bd-content {\n    display: flex;\n    justify-content: center;\n    height: 100%;\n    .bd-article-container {\n      justify-content: start;\n      display: flex;\n      flex-direction: column;\n      // Max-width is slightly more than the W3 since our docs often have images.\n      // We shoot for about 100 characters per line instead of 80.\n      // ref: https://www.w3.org/WAI/tutorials/page-structure/styling/#line-length\n      width: 100%;\n      max-width: 60em;\n      overflow-x: auto; // Prevent wide content from pushing off the secondary sidebar\n      padding: 1rem;\n      .bd-article {\n        // Give a bit more verticle spacing on wide screens\n        @include media-breakpoint-up($breakpoint-sidebar-secondary) {\n          padding-top: 1.5rem;\n          padding-left: 2rem;\n        }\n      }\n    }\n  }\n}\n",".bd-footer {\n  width: 100%;\n  border-top: 1px solid var(--pst-color-border);\n\n  .bd-footer__inner {\n    display: flex;\n    flex-grow: 1;\n    padding: 1rem;\n    margin: auto;\n  }\n\n  .footer-items__start,\n  .footer-items__center,\n  .footer-items__end {\n    display: flex;\n    flex-direction: column;\n    gap: 0.5rem;\n    justify-content: center;\n    flex-grow: 1;\n  }\n\n  .footer-items__center {\n    text-align: center;\n  }\n\n  .footer-items__end {\n    text-align: end;\n  }\n\n  // So that paragraphs don't take up extra room\n  .footer-item p {\n    margin-bottom: 0;\n  }\n}\n",".bd-footer-article {\n  margin-top: auto;\n\n  .footer-article-items {\n    display: flex;\n    flex-direction: column;\n  }\n}\n",".bd-footer-content {\n  .footer-content-items {\n    display: flex;\n    flex-direction: column;\n    margin-top: auto;\n  }\n}\n","/**\n * Header at the top of the page\n * It includes the announcement bar and the navigation bar.\n */\n\n// Styling for the Icon links can be found in components/_icon-links.scss\n\n// If we want the shadow to only point downward in the future, set\n// box-shadow to: 0 0.125rem 0.25rem -0.125rem rgba(0, 0, 0, 0.11);\n.bd-header {\n  position: sticky;\n  top: 0;\n  z-index: $zindex-fixed;\n\n  // Overrides bootstrap\n  background: var(--pst-color-on-background) !important;\n  box-shadow: 0 0.125rem 0.25rem 0 var(--pst-color-shadow);\n\n  width: 100%;\n  padding: 0;\n  max-width: 100vw;\n  justify-content: center;\n  .bd-header__inner {\n    display: flex;\n    align-items: center;\n    height: fit-content;\n    padding-left: 1rem;\n    padding-right: 1rem;\n  }\n\n  // These items will define the height of the header\n  .navbar-item {\n    height: var(--pst-header-height);\n    max-height: var(--pst-header-height);\n    display: flex;\n    align-items: center;\n  }\n\n  // Hide the header items on mobile\n  .navbar-header-items {\n    display: none;\n    flex-shrink: 1;\n    @include media-breakpoint-up($breakpoint-sidebar-primary) {\n      display: flex;\n      flex-grow: 1;\n      padding: 0 0 0 0.5rem;\n    }\n  }\n\n  .navbar-header-items__end,\n  .navbar-header-items__center,\n  .navbar-header-items__start {\n    display: flex;\n    align-items: center;\n    flex-flow: wrap;\n    // In case we wrap our items to multiple rows on small screens\n    row-gap: 0;\n  }\n\n  .navbar-header-items__end,\n  .navbar-header-items__center {\n    column-gap: 1rem;\n  }\n\n  // A little smaller because this is displayed by default on mobile\n  .navbar-header-items__start {\n    flex-shrink: 0;\n    margin-right: auto;\n    gap: 0.5rem;\n  }\n\n  .navbar-header-items__end {\n    // End navbar items should snap to the right\n    justify-content: end;\n  }\n\n  // Contains the navigation links within the navbar\n  .navbar-nav {\n    display: flex;\n\n    @include media-breakpoint-up($breakpoint-sidebar-primary) {\n      // Center align on wide screens so the dropdown button is centered properly\n      align-items: center;\n    }\n\n    li a.nav-link {\n      @include link-style-text;\n    }\n\n    // Current page is always underlined in the navbar\n    > .current > .nav-link {\n      @include link-navbar-current;\n    }\n\n    // Dropdowns for the extra links\n    .dropdown {\n      button {\n        display: unset;\n        color: var(--pst-color-text-muted);\n        border: none;\n        @include link-style-hover;\n        @include focus-indicator;\n      }\n\n      .dropdown-menu {\n        z-index: $zindex-popover;\n        border: 1px solid var(--pst-color-border);\n        box-shadow: 0 0 0.3rem 0.1rem var(--pst-color-shadow);\n        background-color: var(--pst-color-on-background);\n        padding: 0.5rem 0;\n        margin: 0.5rem 0;\n        min-width: 20rem;\n\n        .dropdown-item {\n          // Give the items in the dropdown some breathing room but let the hit\n          // and hover area of the items extend to the edges of the menu\n          padding: 0.25rem 1.5rem;\n\n          // Override Bootstrap\n          &:focus:not(:hover):not(:active) {\n            background-color: inherit;\n          }\n        }\n\n        // Hide the menu unless show has been clicked\n        &:not(.show) {\n          display: none;\n        }\n      }\n    }\n  }\n}\n\n// inline the element in the navbar as long as they fit and use display block when collapsing\n@include media-breakpoint-up($breakpoint-sidebar-primary) {\n  .navbar-center-items .navbar-item {\n    display: inline-block;\n  }\n}\n\n.nav-link {\n  @include link-style-hover;\n\n  // Override Bootstrap\n  transition: none;\n\n  &.nav-external:after {\n    font: var(--fa-font-solid);\n    content: var(--pst-icon-external-link);\n    font-size: 0.75em;\n    margin-left: 0.3em;\n  }\n}\n\n.bd-navbar-elements li.nav-item i {\n  font-size: 0.7rem;\n  padding-left: 2px;\n  vertical-align: middle;\n}\n\n/**\n * Showing and hiding the sidebar toggle buttons and header items\n */\n\n// Hide the header items on mobile\n.bd-header {\n  // Toggle labels\n  label {\n    &.sidebar-toggle {\n      display: flex;\n      cursor: pointer;\n      font-size: var(--pst-font-size-icon);\n      align-items: center;\n      color: var(--pst-color-muted);\n      margin-bottom: 0;\n      padding-bottom: 0.25rem;\n    }\n\n    &.primary-toggle {\n      margin-right: 1rem;\n      @include media-breakpoint-up($breakpoint-sidebar-primary) {\n        display: none;\n      }\n    }\n\n    &.secondary-toggle {\n      margin-left: 1rem;\n      @include media-breakpoint-up($breakpoint-sidebar-secondary) {\n        display: none;\n      }\n    }\n    @include icon-navbar-hover;\n    @include focus-indicator;\n  }\n\n  // Hide the navbar header items on mobile because they're in the sidebar\n  .navbar-header-items {\n    display: none;\n    @include media-breakpoint-up($breakpoint-sidebar-primary) {\n      display: inherit;\n    }\n  }\n}\n\n// THe elements next to the hamburger menu only show on narrow screens\n.navbar-persistent--mobile {\n  margin-left: auto;\n  @include media-breakpoint-up($breakpoint-sidebar-primary) {\n    display: none;\n  }\n}\n\n// The navbar-persistent content should only show on wide screens\n.navbar-persistent--container {\n  display: none;\n  @include media-breakpoint-up($breakpoint-sidebar-primary) {\n    display: flex;\n  }\n}\n",".header-article__inner {\n  display: flex;\n  padding: 0 0.5rem;\n\n  // The items define the height so that it disappears if there are no items\n  .header-article-item {\n    min-height: var(--pst-header-article-height);\n    height: var(--pst-header-article-height);\n  }\n\n  .header-article-items__start,\n  .header-article-items__end {\n    display: flex;\n    align-items: start;\n    gap: 0.5rem;\n  }\n\n  .header-article-items__end {\n    margin-left: auto;\n  }\n}\n","/**\n * The primary sidebar on the left.\n * e.g., between-pages navigation.\n */\n\n.bd-sidebar-primary {\n  display: flex;\n  flex-direction: column;\n  gap: 1rem;\n  max-height: calc(100vh - var(--pst-header-height));\n  position: sticky;\n  top: var(--pst-header-height);\n  @include make-col(3);\n\n  // Borders padding and whitespace\n  padding: 2rem 1rem 1rem 1rem;\n  border-right: 1px solid var(--pst-color-border);\n  background-color: var(--pst-color-background);\n  overflow-y: auto;\n\n  font-size: var(--pst-sidebar-font-size-mobile);\n  @include media-breakpoint-up($breakpoint-sidebar-primary) {\n    font-size: var(--pst-sidebar-font-size);\n  }\n\n  // override bootstrap when navlink are displayed in the sidebar\n  .nav-link {\n    font-size: var(--pst-sidebar-font-size-mobile);\n  }\n\n  &.no-sidebar {\n    border-right: 0;\n  }\n\n  &.hide-on-wide {\n    @include media-breakpoint-up($breakpoint-sidebar-primary) {\n      display: none;\n    }\n  }\n\n  // Headers shouldn't be colored in the sidebars and some extensions add headers\n  h1,\n  h2,\n  h3,\n  h4 {\n    color: var(--pst-color-text-base);\n  }\n\n  .sidebar-primary-items__start,\n  .sidebar-primary-items__end {\n    .sidebar-primary-item {\n      padding: 0.5rem 0;\n    }\n  }\n\n  // Hide the sidebar header items on widescreen since they are visible in the header\n  .sidebar-header-items {\n    display: flex;\n    flex-direction: column;\n\n    .sidebar-header-items__title {\n      font-weight: var(--pst-sidebar-header-font-weight);\n      font-size: var(--pst-sidebar-header-font-size);\n      color: var(--pst-color-text-base);\n      margin-bottom: 0.5rem;\n    }\n\n    // The dropdown toggle for extra links just shows them all instead.\n    .nav-item.dropdown {\n      // On mobile, the dropdown behaves like any other link, no hiding\n      button {\n        display: none;\n      }\n\n      .dropdown-menu {\n        display: flex;\n        flex-direction: column;\n        padding: 0;\n        margin: 0;\n        border: none;\n        background-color: inherit;\n        font-size: inherit;\n      }\n    }\n\n    // Center header items get displayed vertically, end items are displayed horizontally\n    .sidebar-header-items__center {\n      display: flex;\n      flex-direction: column;\n    }\n\n    // Positioning end items\n    .sidebar-header-items__end {\n      display: flex;\n      align-items: center;\n      gap: 0.5rem;\n    }\n\n    @include media-breakpoint-up($breakpoint-sidebar-primary) {\n      display: none;\n    }\n  }\n\n  .sidebar-primary-items__start {\n    // Add a border on mobile to separate it from the header sidebar area\n    border-top: 1px solid var(--pst-color-border);\n    @include media-breakpoint-up($breakpoint-sidebar-primary) {\n      border-top: none;\n    }\n  }\n\n  .sidebar-primary-items__end {\n    margin-top: auto;\n    margin-bottom: 1em;\n  }\n  .list-caption {\n    list-style: none;\n    padding-left: 0px;\n  }\n  li {\n    position: relative;\n    // If it has children, add a bit more padding to wrap the content to avoid\n    // overlapping with the <label>\n    &.has-children {\n      > .reference {\n        padding-right: 30px;\n      }\n    }\n  }\n  // Navigation item chevrons\n  label.toctree-toggle {\n    position: absolute;\n    top: 0;\n    right: 0;\n    height: 30px;\n    width: 30px;\n\n    cursor: pointer;\n\n    display: flex;\n    justify-content: center;\n    align-items: center;\n\n    &:hover {\n      background: var(--pst-color-surface);\n    }\n\n    i {\n      display: inline-block;\n      font-size: 0.75rem;\n      text-align: center;\n      &:hover {\n        color: var(--pst-color-primary);\n      }\n    }\n  }\n  .label-parts {\n    width: 100%;\n    height: 100%;\n    &:hover {\n      background: none;\n    }\n    i {\n      width: 30px;\n      position: absolute;\n      top: 0.3em; // aligning chevron with text\n      right: 0em; // aligning chevron to the right\n    }\n  }\n}\n\n/* Between-page links and captions */\nnav.bd-links {\n  margin-right: -1rem;\n\n  @include media-breakpoint-up($breakpoint-sidebar-primary) {\n    display: block;\n  }\n\n  ul {\n    list-style: none;\n\n    // Reduce padding of nested `ul` items a bit\n    ul {\n      padding: 0 0 0 1rem;\n    }\n  }\n\n  li > a {\n    display: block;\n    padding: 0.25rem 0.65rem;\n    @include link-sidebar;\n    box-shadow: none;\n\n    &.reference.external {\n      &:after {\n        font: var(--fa-font-solid);\n        content: var(--pst-icon-external-link);\n        font-size: 0.75em;\n        margin-left: 0.3em;\n      }\n    }\n  }\n\n  .current {\n    > a {\n      @include link-sidebar-current;\n      background-color: transparent;\n    }\n  }\n\n  // Title\n  p.bd-links__title {\n    font-size: var(--pst-sidebar-header-font-size);\n    font-weight: var(--pst-sidebar-header-font-weight);\n    margin-bottom: 0.5rem;\n  }\n\n  // Toctree captions\n  p.caption {\n    font-weight: var(--pst-sidebar-header-font-weight);\n    position: relative;\n    margin-top: 1.25rem;\n    margin-bottom: 0.5rem;\n    color: var(--pst-color-text-base);\n    &:first-child {\n      margin-top: 0;\n    }\n\n    font-size: var(--pst-sidebar-font-size-mobile);\n    @include media-breakpoint-up($breakpoint-sidebar-primary) {\n      font-size: var(--pst-sidebar-font-size);\n    }\n  }\n}\n","// Grid system\n//\n// Generate semantic grid columns with these mixins.\n\n@mixin make-row($gutter: $grid-gutter-width) {\n  --#{$prefix}gutter-x: #{$gutter};\n  --#{$prefix}gutter-y: 0;\n  display: flex;\n  flex-wrap: wrap;\n  // TODO: Revisit calc order after https://github.com/react-bootstrap/react-bootstrap/issues/6039 is fixed\n  margin-top: calc(-1 * var(--#{$prefix}gutter-y)); // stylelint-disable-line function-disallowed-list\n  margin-right: calc(-.5 * var(--#{$prefix}gutter-x)); // stylelint-disable-line function-disallowed-list\n  margin-left: calc(-.5 * var(--#{$prefix}gutter-x)); // stylelint-disable-line function-disallowed-list\n}\n\n@mixin make-col-ready() {\n  // Add box sizing if only the grid is loaded\n  box-sizing: if(variable-exists(include-column-box-sizing) and $include-column-box-sizing, border-box, null);\n  // Prevent columns from becoming too narrow when at smaller grid tiers by\n  // always setting `width: 100%;`. This works because we set the width\n  // later on to override this initial width.\n  flex-shrink: 0;\n  width: 100%;\n  max-width: 100%; // Prevent `.col-auto`, `.col` (& responsive variants) from breaking out the grid\n  padding-right: calc(var(--#{$prefix}gutter-x) * .5); // stylelint-disable-line function-disallowed-list\n  padding-left: calc(var(--#{$prefix}gutter-x) * .5); // stylelint-disable-line function-disallowed-list\n  margin-top: var(--#{$prefix}gutter-y);\n}\n\n@mixin make-col($size: false, $columns: $grid-columns) {\n  @if $size {\n    flex: 0 0 auto;\n    width: percentage(divide($size, $columns));\n\n  } @else {\n    flex: 1 1 0;\n    max-width: 100%;\n  }\n}\n\n@mixin make-col-auto() {\n  flex: 0 0 auto;\n  width: auto;\n}\n\n@mixin make-col-offset($size, $columns: $grid-columns) {\n  $num: divide($size, $columns);\n  margin-left: if($num == 0, 0, percentage($num));\n}\n\n// Row columns\n//\n// Specify on a parent element(e.g., .row) to force immediate children into NN\n// number of columns. Supports wrapping to new lines, but does not do a Masonry\n// style grid.\n@mixin row-cols($count) {\n  > * {\n    flex: 0 0 auto;\n    width: percentage(divide(1, $count));\n  }\n}\n\n// Framework grid generation\n//\n// Used only by Bootstrap to generate the correct number of grid classes given\n// any value of `$grid-columns`.\n\n@mixin make-grid-columns($columns: $grid-columns, $gutter: $grid-gutter-width, $breakpoints: $grid-breakpoints) {\n  @each $breakpoint in map-keys($breakpoints) {\n    $infix: breakpoint-infix($breakpoint, $breakpoints);\n\n    @include media-breakpoint-up($breakpoint, $breakpoints) {\n      // Provide basic `.col-{bp}` classes for equal-width flexbox columns\n      .col#{$infix} {\n        flex: 1 0 0%; // Flexbugs #4: https://github.com/philipwalton/flexbugs#flexbug-4\n      }\n\n      .row-cols#{$infix}-auto > * {\n        @include make-col-auto();\n      }\n\n      @if $grid-row-columns > 0 {\n        @for $i from 1 through $grid-row-columns {\n          .row-cols#{$infix}-#{$i} {\n            @include row-cols($i);\n          }\n        }\n      }\n\n      .col#{$infix}-auto {\n        @include make-col-auto();\n      }\n\n      @if $columns > 0 {\n        @for $i from 1 through $columns {\n          .col#{$infix}-#{$i} {\n            @include make-col($i, $columns);\n          }\n        }\n\n        // `$columns - 1` because offsetting by the width of an entire row isn't possible\n        @for $i from 0 through ($columns - 1) {\n          @if not ($infix == \"\" and $i == 0) { // Avoid emitting useless .offset-0\n            .offset#{$infix}-#{$i} {\n              @include make-col-offset($i, $columns);\n            }\n          }\n        }\n      }\n\n      // Gutters\n      //\n      // Make use of `.g-*`, `.gx-*` or `.gy-*` utilities to change spacing between the columns.\n      @each $key, $value in $gutters {\n        .g#{$infix}-#{$key},\n        .gx#{$infix}-#{$key} {\n          --#{$prefix}gutter-x: #{$value};\n        }\n\n        .g#{$infix}-#{$key},\n        .gy#{$infix}-#{$key} {\n          --#{$prefix}gutter-y: #{$value};\n        }\n      }\n    }\n  }\n}\n\n@mixin make-cssgrid($columns: $grid-columns, $breakpoints: $grid-breakpoints) {\n  @each $breakpoint in map-keys($breakpoints) {\n    $infix: breakpoint-infix($breakpoint, $breakpoints);\n\n    @include media-breakpoint-up($breakpoint, $breakpoints) {\n      @if $columns > 0 {\n        @for $i from 1 through $columns {\n          .g-col#{$infix}-#{$i} {\n            grid-column: auto / span $i;\n          }\n        }\n\n        // Start with `1` because `0` is and invalid value.\n        // Ends with `$columns - 1` because offsetting by the width of an entire row isn't possible.\n        @for $i from 1 through ($columns - 1) {\n          .g-start#{$infix}-#{$i} {\n            grid-column-start: $i;\n          }\n        }\n      }\n    }\n  }\n}\n","/**\n * Secondary sidebar on the right.\n * e.g., in-page table of contents.\n */\n.bd-sidebar-secondary {\n  display: flex;\n  order: 2;\n  flex-shrink: 0;\n  flex-direction: column;\n  position: sticky;\n  top: var(--pst-header-height);\n  max-height: calc(100vh - var(--pst-header-height));\n  padding: 2rem 1rem 1rem 1rem;\n  width: var(--pst-sidebar-secondary);\n  font-size: var(--pst-sidebar-font-size-mobile);\n  @include media-breakpoint-up($breakpoint-sidebar-secondary) {\n    font-size: var(--pst-sidebar-font-size);\n  }\n\n  // Color and border\n  background-color: var(--pst-color-background);\n  overflow-y: auto;\n}\n\n.sidebar-secondary-item {\n  padding: 0.5rem 0.5rem;\n  @include media-breakpoint-up($breakpoint-sidebar-secondary) {\n    border-left: 1px solid var(--pst-color-border);\n    padding-left: 1rem;\n  }\n\n  i {\n    padding-right: 0.5rem;\n  }\n}\n","/*******************************************************************************\n* Rules for the UX/UI of sidebar sliding drawers on mobile\n* Note that this sheet controls styles across many parts of the theme\n* It is aggregated into this one sheet instead of being split across\n* components in order to keep it easier to debug in one place.\n* It is broken up into major sections below.\n*/\n\n/*******************************************************************************\n* Buttons and overlays\n*/\ninput.sidebar-toggle {\n  display: none;\n}\n\n// Background overlays\nlabel.overlay {\n  background-color: black;\n  opacity: 0.5;\n  height: 0;\n  width: 0;\n  position: fixed;\n  top: 0;\n  left: 0;\n  transition: opacity $animation-time ease-out;\n  z-index: $zindex-modal-backdrop;\n}\n\ninput {\n  // Show the correct overlay when its input is checked\n  &#__primary:checked + label.overlay.overlay-primary,\n  &#__secondary:checked + label.overlay.overlay-secondary {\n    height: 100vh;\n    width: 100vw;\n  }\n\n  // Primary sidebar slides in from the left\n  &#__primary:checked ~ .bd-container .bd-sidebar-primary {\n    visibility: visible;\n    margin-left: 0;\n  }\n\n  // Secondary sidebar slides in from the right\n  &#__secondary:checked ~ .bd-container .bd-sidebar-secondary {\n    visibility: visible;\n    margin-right: 0;\n  }\n}\n\n/*******************************************************************************\n* Sidebar drawer behavior\n*/\n\n/**\n * Behavior for sliding drawer elements that will be toggled with an input\n *\n * NOTE: We use this mixin to define the toggle behavior on narrow screens,\n * And the wide-screen behavior of the sections is defined in their own section\n * .scss files.\n */\n@mixin sliding-drawer($side: \"left\") {\n  position: fixed;\n  top: 0;\n  z-index: $zindex-modal;\n  height: 100vh;\n  max-height: 100vh;\n  width: 75%;\n  flex-grow: 0.75;\n  max-width: 350px;\n  transition: visibility $animation-time ease-out,\n    margin $animation-time ease-out;\n  visibility: hidden;\n\n  @if $side == \"right\" {\n    margin-right: -75%;\n    right: 0;\n  } @else {\n    margin-left: -75%;\n    left: 0;\n  }\n}\n\n// Primary sidebar hides/shows at earlier widths\n@include media-breakpoint-up($breakpoint-sidebar-primary) {\n  label.sidebar-toggle.primary-toggle {\n    display: none;\n  }\n\n  input#__primary {\n    &:checked + label.overlay.overlay-primary {\n      height: 0;\n      width: 0;\n    }\n  }\n\n  .bd-sidebar-primary {\n    margin-left: 0;\n    visibility: visible;\n  }\n}\n\n.bd-sidebar-primary {\n  @include media-breakpoint-down($breakpoint-sidebar-primary) {\n    @include sliding-drawer(\"left\");\n  }\n}\n\n.bd-sidebar-secondary {\n  @include media-breakpoint-down($breakpoint-sidebar-secondary) {\n    @include sliding-drawer(\"right\");\n  }\n}\n","/**\n * Breadcrumbs for parent pages meant for the article header\n */\nul.bd-breadcrumbs {\n  list-style: none;\n  padding-left: 0;\n  display: flex;\n  flex-wrap: wrap;\n\n  // Font size slightly smaller to avoid cluttering up space too much\n  font-size: 0.8rem;\n\n  li.breadcrumb-item {\n    display: flex;\n    align-items: center;\n\n    // Style should look like heavier in-page links\n    // keeping visited in the default link colour\n    font-weight: bold;\n    a {\n      @include link-style-text;\n    }\n\n    // Items that aren't the home have a caret to the left\n    &:not(.breadcrumb-home):before {\n      font: var(--fa-font-solid);\n      font-size: 0.8rem;\n      content: var(--pst-breadcrumb-divider);\n      color: var(--pst-color-text-muted);\n      padding: 0 0.5rem;\n    }\n  }\n}\n","/**\n * Icon links in the navbar\n */\n\n.navbar-icon-links {\n  display: flex;\n  flex-direction: row;\n  column-gap: 1rem;\n  flex-wrap: wrap;\n\n  // Remove the padding so that we can define it with flexbox gap above\n  li.nav-item a.nav-link {\n    padding-left: 0;\n    padding-right: 0;\n    @include icon-navbar-hover;\n  }\n\n  // Spacing and centering\n  a span {\n    display: flex;\n    align-items: center;\n  }\n\n  // Icons styling\n  i {\n    &.fa-brands,\n    &.fa-regular,\n    &.fa-solid {\n      vertical-align: middle;\n      font-style: normal;\n      font-size: var(--pst-font-size-icon);\n    }\n\n    /* Social media buttons hard-code the brand color */\n    &.fa-square-twitter:before {\n      color: #55acee;\n    }\n\n    &.fa-square-gitlab:before {\n      color: #548;\n    }\n\n    &.fa-bitbucket:before {\n      color: #0052cc;\n    }\n  }\n\n  // Force images to be icon-sized\n  img.icon-link-image {\n    height: 1.5em;\n    border-radius: 0.2rem;\n  }\n}\n","/**\n * Logo in the navbar\n */\n\n.navbar-brand {\n  position: relative;\n  height: var(--pst-header-height);\n  max-height: var(--pst-header-height);\n  padding: 0.5rem 0;\n  width: auto;\n  margin: 0;\n  display: flex;\n  // Ensure that the logo stays the same length while other content shrinks\n  flex-shrink: 0;\n  align-items: center;\n  gap: 0.5rem;\n\n  // If there's no logo image, we use a p element w/ the site title\n  p {\n    margin-bottom: 0;\n  }\n\n  // If there's a logo, it'll be in an img block\n  img {\n    max-width: 100%;\n    height: 100%;\n    width: auto;\n  }\n\n  // remove underline from brand title on default state\n  a {\n    text-decoration: none;\n  }\n  &:hover {\n    @include link-style-hover;\n  }\n  &:visited {\n    &:hover {\n      @include link-style-hover;\n    }\n  }\n}\n","/**\n * Navigation text links in the navbar\n */\n.navbar-nav {\n  ul {\n    display: block;\n    list-style: none;\n\n    // Reduce padding of nested `ul` items a bit\n    ul {\n      padding: 0 0 0 1rem;\n    }\n  }\n\n  // Navbar links - do not have an underline by default\n  li {\n    display: flex;\n    flex-direction: column;\n\n    a {\n      display: flex;\n      align-items: center;\n      height: 100%;\n      padding-top: 0.25rem;\n      padding-bottom: 0.25rem;\n      @include link-style-text;\n    }\n  }\n\n  /**\n   * Togglable expand/collapse\n   * This is only applicable to the primary sidebar which has these checkboxes\n   */\n  .toctree-checkbox {\n    position: absolute;\n    display: none;\n  }\n\n  .toctree-checkbox {\n    ~ ul {\n      display: none;\n    }\n    ~ label .fa-chevron-down {\n      transform: rotate(0deg);\n    }\n  }\n  .toctree-checkbox:checked {\n    ~ ul {\n      display: block;\n    }\n    ~ label .fa-chevron-down {\n      transform: rotate(180deg);\n    }\n  }\n}\n","/**\n * The list of in-page TOC links\n */\n.page-toc {\n  .section-nav {\n    padding-left: 0;\n    border-bottom: none;\n\n    ul {\n      padding-left: 1rem;\n    }\n  }\n\n  // override bootstrap settings\n  .nav-link {\n    font-size: var(--pst-sidebar-font-size-mobile);\n    @include media-breakpoint-up($breakpoint-sidebar-secondary) {\n      font-size: var(--pst-sidebar-font-size);\n    }\n  }\n\n  .onthispage {\n    color: var(--pst-color-text-base);\n    font-weight: var(--pst-sidebar-header-font-weight);\n    margin-bottom: 0.5rem;\n  }\n}\n","/**\n* Previous / Next navigation buttons\n**/\n.prev-next-area {\n  width: 100%;\n\n  p {\n    margin: 0 0.3em;\n    line-height: 1.3em;\n  }\n\n  i {\n    font-size: 1.2em;\n  }\n\n  a {\n    // So that buttons align with icons\n    display: flex;\n    align-items: center;\n    border: none;\n    padding: 10px;\n    max-width: 45%;\n    overflow-x: hidden;\n    color: var(--pst-color-text-muted);\n    text-decoration: none;\n\n    p.prev-next-title {\n      @include link-style-default;\n      font-weight: var(--pst-admonition-font-weight-heading);\n      font-size: 1.1em;\n    }\n\n    &:hover p.prev-next-title {\n      @include link-style-hover;\n    }\n    // Exception here - keep visited in the default link colour\n    // it still should hover on the default link hover colour\n    &:visited p.prev-next-title {\n      color: var(--pst-color-link);\n      &:hover {\n        color: var(--pst-color-link-hover);\n      }\n    }\n\n    .prev-next-info {\n      flex-direction: column;\n      margin: 0 0.5em;\n\n      .prev-next-subtitle {\n        text-transform: capitalize;\n      }\n    }\n\n    &.left-prev {\n      float: left;\n    }\n\n    &.right-next {\n      float: right;\n\n      div.prev-next-info {\n        text-align: right;\n      }\n    }\n  }\n}\n","/**\n * Search field\n **/\n.bd-search {\n  position: relative;\n  padding-left: 0.5rem;\n  gap: 0.5rem;\n  background-color: var(--pst-color-background);\n  border-radius: $admonition-border-radius;\n  border: 1px solid var(--pst-color-border);\n  color: var(--pst-color-text-base);\n\n  // Background should always be same color regardless of active or not\n  &:active {\n    background-color: var(--pst-color-background);\n    color: var(--pst-color-text-muted);\n  }\n\n  .icon {\n    position: absolute;\n    color: var(--pst-color-border);\n    left: 25px;\n  }\n\n  .fa-solid.fa-magnifying-glass {\n    position: absolute;\n    left: calc((2.5rem - 0.7em) / 2);\n    color: var(--pst-color-text-muted);\n  }\n\n  input {\n    // Inner-text of the search bar\n    &::placeholder {\n      color: var(--pst-color-text-muted);\n    }\n\n    // Remove the little \"x\" that pops up when you start typing\n    &::-webkit-search-cancel-button,\n    &::-webkit-search-decoration {\n      -webkit-appearance: none;\n      appearance: none;\n    }\n  }\n\n  // Shows off the keyboard shortcuts for the button\n  .search-button__kbd-shortcut {\n    display: flex;\n    position: absolute;\n    right: 0.5rem;\n    color: var(--pst-color-border);\n  }\n}\n\n.form-control {\n  background-color: var(--pst-color-background);\n  color: var(--pst-color-text-base);\n\n  &:focus,\n  &:focus-visible {\n    border: none;\n    box-shadow: none;\n    outline: 3px solid var(--pst-color-accent);\n    background-color: var(--pst-color-background);\n    color: var(--pst-color-text-muted);\n  }\n}\n\n/**\n * Search button - located in the navbar\n */\n\n// Search link icon should be a bit bigger since it is separate from icon links\n.search-button {\n  display: flex;\n  align-items: center;\n  align-content: center;\n  color: var(--pst-color-text-muted);\n  border-radius: 0;\n  @include icon-navbar-hover;\n  @include focus-indicator;\n\n  i {\n    font-size: 1.3rem;\n  }\n}\n\n// __search-container will only show up when we use the search pop-up bar\n.search-button__search-container,\n.search-button__overlay {\n  display: none;\n}\n.search-button__wrapper.show {\n  .search-button__search-container {\n    display: flex;\n    // Center in middle of screen just underneath header\n    position: fixed;\n    z-index: $zindex-modal;\n    top: 30%;\n    left: 50%;\n    transform: translate(-50%, -50%);\n    right: 1rem;\n    margin-top: 0.5rem;\n    width: 90%;\n    max-width: 800px;\n  }\n\n  .search-button__overlay {\n    display: flex;\n    position: fixed;\n    z-index: $zindex-modal-backdrop;\n    background-color: black;\n    opacity: 0.5;\n    width: 100%;\n    height: 100%;\n    top: 0px;\n    left: 0px;\n  }\n\n  form.bd-search {\n    flex-grow: 1;\n    padding-top: 0;\n    padding-bottom: 0;\n  }\n\n  // Font and input text a bit bigger\n  svg,\n  input {\n    font-size: var(--pst-font-size-icon);\n  }\n}\n\n/**\n * The search button component that looks like a field.\n * Lives at components/search-button-field.html\n */\n.search-button-field {\n  display: inline-flex;\n  align-items: center;\n  border: var(--pst-color-border) solid 1px;\n  border-radius: 1.5em;\n  color: var(--pst-color-text-muted);\n  padding: 0.5em;\n  background-color: var(--pst-color-surface);\n\n  &:hover {\n    border: 2px solid var(--pst-color-link-hover);\n  }\n  &:focus-visible {\n    border: 2px solid var(--pst-color-accent);\n  }\n\n  // The keyboard shotcut text\n  .search-button__default-text {\n    font-size: var(--bs-nav-link-font-size);\n    font-weight: var(--bs-nav-link-font-weight);\n    margin-right: 0.5em;\n    margin-left: 0.5em;\n  }\n\n  .kbd-shortcut__modifier {\n    font-size: 0.75em;\n  }\n\n  // Ensures that all the text lines up in the middle\n  > * {\n    align-items: center;\n  }\n\n  // Only the icon should be visible on narrow screens\n  > :not(svg) {\n    display: none;\n\n    @include media-breakpoint-up(lg) {\n      display: flex;\n    }\n  }\n}\n","/**\n * The 'Hide Search Matches' button.\n * This only shows up when a person lands on a page after clicking a search result.\n * Clicking it removes the highlighting of the search term from the page.\n * We want it to behave like a button.\n */\ndiv#searchbox {\n  // Leave `#searchbox` rules empty so that it doesn't show at all when it is empty\n  p.highlight-link {\n    margin: 1rem 0;\n    width: fit-content;\n\n    // A bit more margin on wide screens to mimic article behavior\n    @include media-breakpoint-up($breakpoint-sidebar-secondary) {\n      margin-left: 2rem;\n    }\n\n    // Put outer shadow on this one so that we can darken the link w/ an inner shadow\n    @include box-shadow();\n\n    // Style the button to look like a Sphinx Design button\n    a {\n      border-radius: 0.25rem;\n      font-size: 1.25rem;\n      padding: 0.75rem;\n      background-color: var(--pst-color-primary);\n      color: var(--pst-color-primary-text);\n      text-decoration: none;\n\n      // The box shadow is inset so that it darkens the button on hover\n      transition: box-shadow 0.25s ease-out;\n      &:hover {\n        box-shadow: inset 0px 0px 50px 50px rgba(0, 0, 0, 0.25);\n      }\n\n      &:before {\n        content: var(--pst-icon-search-minus);\n        color: unset;\n        font: var(--fa-font-solid);\n        margin-right: 0.5rem;\n      }\n    }\n  }\n}\n","/*********************************************\n* SASS Mixins\n*********************************************/\n\n/**\n * A consistent box shadow style we apply across elements.\n */\n@mixin box-shadow() {\n  box-shadow: 0 0.2rem 0.5rem var(--pst-color-shadow),\n    0 0 0.0625rem var(--pst-color-shadow) !important;\n}\n\n/**\n   * Set background of some cell outputs to white-ish to make sure colors work\n   * This is because many libraries make output that only looks good on white\n   */\n@mixin cell-output-background {\n  color: var(--pst-color-on-background);\n  background-color: var(--pst-color-text-base);\n  border-radius: 0.25rem;\n  padding: 0.5rem;\n}\n","/**\n * Light/dark theme switcher\n */\n\n.theme-switch-button {\n  // overide bootstrap settings\n  margin: 0 -0.5rem;\n  padding: 0; // We pad the `span` not the container\n  color: var(--pst-color-text-muted);\n  border-radius: 0;\n  @include focus-indicator;\n\n  span {\n    display: none;\n    padding: 0.5em;\n\n    @include icon-navbar-hover;\n    &:active {\n      text-decoration: none;\n      color: var(--pst-color-link-hover);\n    }\n  }\n}\n\nhtml[data-mode=\"auto\"] .theme-switch-button span[data-mode=\"auto\"] {\n  display: flex;\n}\nhtml[data-mode=\"light\"] .theme-switch-button span[data-mode=\"light\"] {\n  display: flex;\n}\nhtml[data-mode=\"dark\"] .theme-switch-button span[data-mode=\"dark\"] {\n  display: flex;\n}\n","button.btn.version-switcher__button {\n  border-color: var(--pst-color-border);\n  color: var(--pst-color-text-base);\n  // Add a margin on narrow screens to avoid feeling cramped\n  margin-bottom: 1em;\n  @include media-breakpoint-up($breakpoint-sidebar-primary) {\n    margin-bottom: unset;\n  }\n\n  @include link-style-hover;\n  @include focus-indicator;\n  &:active {\n    color: var(--pst-color-text-base);\n    border-color: var(--pst-color-border);\n  }\n}\n\n.version-switcher__menu {\n  border-color: var(--pst-color-border);\n  border-radius: var(--bs-dropdown-border-radius);\n\n  a.list-group-item {\n    background-color: var(--pst-color-on-background);\n    color: var(--pst-color-text-base);\n    padding: 0.75rem 1.25rem;\n\n    &:not(:last-child) {\n      border-bottom: 1px solid var(--pst-color-border);\n    }\n    @include link-style-hover;\n    &:hover {\n      background-color: var(--pst-color-surface);\n    }\n    &.active {\n      @include link-sidebar-current;\n      position: relative;\n      z-index: 1;\n\n      span:before {\n        content: \"\";\n        width: 100%;\n        height: 100%;\n        position: absolute;\n        z-index: -1;\n        left: 0;\n        top: 0;\n      }\n    }\n  }\n}\n\n// Font behavior on mobile\nbutton.version-switcher__button,\n.version-switcher__menu {\n  font-size: 1.1em; // A bit smaller than other menu font\n  z-index: $zindex-modal; // higher than the sidebars\n  @include media-breakpoint-up($breakpoint-sidebar-primary) {\n    font-size: unset;\n  }\n}\n","/* Collapsing of the TOC sidebar while scrolling */\n/* Nav: hide second level (shown on .active) */\n\nnav.page-toc {\n  // A little extra space before the buttons\n  margin-bottom: 1rem;\n}\n\n.bd-toc .nav,\n.list-caption {\n  .nav {\n    display: none;\n\n    // So we can manually specify a level as visible in the config\n    &.visible {\n      display: block;\n    }\n  }\n\n  > .active > ul {\n    display: block;\n  }\n}\n\n// Each entry of the in-page TOC\n.toc-entry {\n  display: block;\n  a > code {\n    color: var(--pst-color-text-muted);\n  }\n\n  a.nav-link {\n    display: block;\n    padding: 0.125rem 0;\n\n    // Padding w/ negative margin so the top TOC item highlight overlaps w/ the TOC border\n    padding-left: 1rem;\n    margin-left: -1rem;\n\n    @include link-sidebar;\n\n    &.active {\n      @include link-sidebar-current;\n      background-color: transparent;\n\n      &:hover {\n        color: var(--pst-color-link-hover);\n      }\n    }\n  }\n}\n","div.versionadded,\ndiv.versionchanged,\ndiv.deprecated {\n  vertical-align: middle;\n  margin: 1.5625em auto;\n  padding: 0 0.6rem 0 0.6rem;\n  overflow: hidden;\n  page-break-inside: avoid;\n  border-left: 0.2rem solid;\n  border-color: var(--pst-color-info);\n  border-radius: $admonition-border-radius;\n  background-color: var(--pst-color-on-background);\n  @include box-shadow();\n  position: relative;\n\n  > p {\n    margin-bottom: 0.6rem;\n    margin-top: 0.6rem;\n  }\n}\n\ndiv.versionadded {\n  border-color: var(--pst-color-success);\n  background-color: var(--pst-color-success-bg);\n}\n\ndiv.versionchanged {\n  border-color: var(--pst-color-warning);\n  background-color: var(--pst-color-warning-bg);\n}\n\ndiv.deprecated {\n  border-color: var(--pst-color-danger);\n  background-color: var(--pst-color-danger-bg);\n}\n\nspan.versionmodified {\n  font-weight: 600;\n\n  &:before {\n    margin-right: 0.6rem;\n    color: var(--pst-color-info);\n    font: var(--fa-font-solid);\n    content: var(--pst-icon-versionmodified-default);\n  }\n}\n\nspan.versionmodified.added {\n  &:before {\n    color: var(--pst-color-success);\n    content: var(--pst-icon-versionmodified-added);\n  }\n}\n\nspan.versionmodified.changed {\n  &:before {\n    color: var(--pst-color-warning);\n    content: var(--pst-icon-versionmodified-changed);\n  }\n}\n\nspan.versionmodified.deprecated {\n  &:before {\n    color: var(--pst-color-danger);\n    content: var(--pst-icon-versionmodified-deprecated);\n  }\n}\n",".sidebar-indices-items {\n  display: flex;\n  flex-direction: column;\n  border-top: 1px solid var(--pst-color-border);\n\n  @include media-breakpoint-up($breakpoint-sidebar-primary) {\n    border-top: none;\n  }\n\n  .sidebar-indices-items__title {\n    font-weight: var(--pst-sidebar-header-font-weight);\n    font-size: var(--pst-sidebar-header-font-size);\n    color: var(--pst-color-text-base);\n    margin-bottom: 0.5rem;\n  }\n\n  ul.indices-link {\n    margin-right: -1rem;\n    list-style: none;\n    padding: 0;\n\n    li > a {\n      display: block;\n      padding: 0.25rem 0;\n      color: var(--pst-color-text-muted);\n\n      &:hover {\n        color: var(--pst-color-primary);\n        text-decoration: none;\n        background-color: transparent;\n      }\n    }\n  }\n}\n",".bd-sidebar-primary div#rtd-footer-container {\n  position: sticky;\n  bottom: -1rem;\n  margin: -1rem; // ignore sidebar padding\n\n  .rst-versions.rst-badge {\n    position: unset;\n    font-size: 0.9em;\n    font-family: var(--pst-font-family-base);\n    max-width: unset;\n\n    .rst-current-version {\n      display: flex;\n      align-items: center;\n      gap: 0.2rem;\n      height: 2.5rem;\n      transition: background-color 0.2s ease-out;\n      background-color: var(--pst-color-background);\n      color: var(--pst-color-success);\n      border-top: 1px solid var(--pst-color-border);\n    }\n\n    .fa.fa-book {\n      color: var(--pst-color-text-muted);\n      margin-right: auto;\n\n      &::after {\n        color: var(--pst-color-text-base);\n        content: \"Read The Docs\";\n        font-family: var(--pst-font-family-base);\n        font-weight: var(--pst-admonition-font-weight-heading);\n      }\n    }\n    .fa.fa-caret-down {\n      color: var(--pst-color-text-muted);\n    }\n  }\n\n  .rst-versions.rst-badge.shift-up {\n    .rst-current-version {\n      border-bottom: 1px solid var(--pst-color-border);\n    }\n  }\n\n  .rst-other-versions {\n    background-color: var(--pst-color-surface);\n    color: var(--pst-color-text-base);\n\n    dl {\n      dd a {\n        color: var(--pst-color-text-muted);\n      }\n    }\n\n    hr {\n      background-color: var(--pst-color-border);\n    }\n\n    small a {\n      color: var(--pst-color-link);\n    }\n\n    input {\n      padding-left: 0.5rem;\n      border: 1px solid var(--pst-color-border);\n      background-color: var(--pst-color-surface);\n    }\n  }\n}\n","/**\n * Admonitions and blocks of styled content.\n * Admonitions CSS originally inspired by https://squidfunk.github.io/mkdocs-material/getting-started/\n */\n$admonition-border-radius: 0.25rem;\ndiv.admonition,\n.admonition {\n  margin: 1.5625em auto;\n  padding: 0 0.6rem 0.8rem 0.6rem;\n  overflow: hidden;\n  page-break-inside: avoid;\n  border-left: 0.2rem solid;\n  border-color: var(--pst-color-info);\n  border-radius: $admonition-border-radius;\n  background-color: var(--pst-color-on-background);\n  @include box-shadow();\n\n  // Last item should have no spacing since we'll control that w/ padding\n  *:last-child {\n    margin-bottom: 0;\n  }\n\n  // Items after the title should be indented\n  p.admonition-title ~ * {\n    margin-left: 1.4rem;\n    margin-right: 1.4rem;\n  }\n\n  // Lists need to have left margin so they don't spill into it\n  > ol,\n  > ul {\n    margin-left: 1em;\n  }\n\n  // Defaults for all admonitions\n  > .admonition-title {\n    margin: 0 -0.6rem;\n    padding: 0.4rem 0.6rem 0.4rem 2rem;\n    font-weight: var(--pst-admonition-font-weight-heading);\n    position: relative;\n    @include legacy-backdrop-placeholder;\n    background-color: var(--pst-color-info-bg);\n    // now that we use solid colors we want the title on top\n    z-index: 1;\n\n    &:after {\n      position: absolute;\n      left: 0.5rem;\n      width: 1rem;\n      height: 1rem;\n      color: var(--pst-color-info);\n      font: var(--fa-font-solid);\n      line-height: inherit;\n      content: var(--pst-icon-admonition-default);\n      opacity: 1;\n    }\n\n    // Next element after title needs some extra upper-space\n    + * {\n      margin-top: 0.4em;\n    }\n  }\n\n  &.attention {\n    border-color: var(--pst-color-attention);\n    > .admonition-title {\n      background-color: var(--pst-color-attention-bg);\n\n      &:after {\n        color: var(--pst-color-attention);\n        content: var(--pst-icon-admonition-attention);\n      }\n    }\n  }\n\n  &.caution {\n    border-color: var(--pst-color-warning);\n    > .admonition-title {\n      background-color: var(--pst-color-warning-bg);\n\n      &:after {\n        color: var(--pst-color-warning);\n        content: var(--pst-icon-admonition-caution);\n      }\n    }\n  }\n\n  &.warning {\n    border-color: var(--pst-color-warning);\n    > .admonition-title {\n      background-color: var(--pst-color-warning-bg);\n\n      &:after {\n        color: var(--pst-color-warning);\n        content: var(--pst-icon-admonition-warning);\n      }\n    }\n  }\n\n  &.danger {\n    border-color: var(--pst-color-danger);\n    > .admonition-title {\n      background-color: var(--pst-color-danger-bg);\n\n      &:after {\n        color: var(--pst-color-danger);\n        content: var(--pst-icon-admonition-danger);\n      }\n    }\n  }\n\n  &.error {\n    border-color: var(--pst-color-danger);\n    > .admonition-title {\n      background-color: var(--pst-color-danger-bg);\n\n      &:after {\n        color: var(--pst-color-danger);\n        content: var(--pst-icon-admonition-error);\n      }\n    }\n  }\n\n  &.hint {\n    border-color: var(--pst-color-success);\n    > .admonition-title {\n      background-color: var(--pst-color-success-bg);\n\n      &:after {\n        color: var(--pst-color-success);\n        content: var(--pst-icon-admonition-hint);\n      }\n    }\n  }\n\n  &.tip {\n    border-color: var(--pst-color-success);\n    > .admonition-title {\n      background-color: var(--pst-color-success-bg);\n\n      &:after {\n        color: var(--pst-color-success);\n        content: var(--pst-icon-admonition-tip);\n      }\n    }\n  }\n\n  &.important {\n    border-color: var(--pst-color-attention);\n    > .admonition-title {\n      background-color: var(--pst-color-attention-bg);\n\n      &:after {\n        color: var(--pst-color-attention);\n        content: var(--pst-icon-admonition-important);\n      }\n    }\n  }\n\n  &.note {\n    border-color: var(--pst-color-info);\n    > .admonition-title {\n      background-color: var(--pst-color-info-bg);\n\n      &:after {\n        color: var(--pst-color-info);\n        content: var(--pst-icon-admonition-note);\n      }\n    }\n  }\n\n  &.seealso {\n    border-color: var(--pst-color-success);\n    > .admonition-title {\n      background-color: var(--pst-color-success-bg);\n\n      &:after {\n        color: var(--pst-color-success);\n        content: var(--pst-icon-admonition-seealso);\n      }\n    }\n  }\n\n  &.admonition-todo {\n    border-color: var(--pst-color-secondary);\n    > .admonition-title {\n      background-color: var(--pst-color-secondary-bg);\n\n      &:after {\n        color: var(--pst-color-secondary);\n        content: var(--pst-icon-admonition-todo);\n      }\n    }\n  }\n\n  /**\n   * Special-case for a `sidebar` class that makes the admonition float to\n   * the right like the {sidebar} directive.\n   */\n  &.sidebar {\n    max-width: 40%;\n    float: right;\n    clear: both;\n    margin-left: 0.5rem;\n    margin-top: 0;\n\n    // Undo the .sidebar directive border\n    border-width: 0 0 0 0.2rem;\n\n    // TODO: these semantic-color-names border-color rules might no longer be\n    //       needed when we drop support for Sphinx 4 / docutils 0.17\n    &.attention,\n    &.important {\n      border-color: var(--pst-color-attention);\n    }\n\n    &.caution,\n    &.warning {\n      border-color: var(--pst-color-warning);\n    }\n\n    &.danger,\n    &.error {\n      border-color: var(--pst-color-danger);\n    }\n\n    &.hint,\n    &.tip,\n    &.seealso {\n      border-color: var(--pst-color-success);\n    }\n\n    &.note,\n    &.todo {\n      border-color: var(--pst-color-info);\n    }\n\n    // No inner margin since we have less horizontal space w/ the sidebar\n    p.admonition-title ~ * {\n      margin-left: 0rem;\n      margin-right: 0rem;\n    }\n  }\n}\n\n/**************************************************************\n * Similar content blocks that are not technically admonitions.\n */\n\n/**\n * Topics and the {contents} directive\n */\n// Docutils <= 0.17\ndiv.topic,\ndiv.topic.contents,\n// Docutils >= 0.18\nnav.contents,\naside.topic {\n  display: flex;\n  flex-direction: column;\n  background-color: var(--pst-color-surface);\n  border-color: var(--pst-color-border);\n  border-radius: $admonition-border-radius;\n  padding: 1rem 1.25rem;\n  @include box-shadow();\n\n  .topic-title {\n    margin: 0 0 0.5rem 0;\n  }\n\n  // Over-ride text color to ensure enough contrast\n  p {\n    color: var(--pst-color-on-surface) !important;\n  }\n\n  // Over-ride large default padding\n  ul.simple {\n    padding-left: 1rem;\n\n    ul {\n      // So that sub-lists will have a bit less padding\n      padding-left: 2em;\n    }\n  }\n}\n\n/**\n * Sidebar directive\n */\naside.sidebar {\n  border: 1px solid var(--pst-color-border);\n  background-color: var(--pst-color-surface);\n  border-radius: $admonition-border-radius;\n  // to match the admonition-styled sidebars:\n  margin-left: 0.5rem;\n  padding: 0;\n  > *:last-child {\n    padding-bottom: 1rem;\n  }\n\n  p.sidebar-title {\n    position: relative;\n    margin-bottom: 0;\n    padding-top: 0.5rem;\n    padding-bottom: 0.5rem;\n    border-bottom: 1px solid var(--pst-color-border);\n    font-family: var(--pst-font-family-heading);\n    font-weight: var(--pst-admonition-font-weight-heading);\n  }\n\n  // Add margin to the first non-`.sidebar-title` item\n  > *:not(.sidebar-title):first-child,\n  > p.sidebar-title + * {\n    margin-top: 1rem;\n  }\n\n  > * {\n    padding-left: 1rem;\n    padding-right: 1rem;\n  }\n}\n\n/**\n * Rubrics look kind of like section headers\n */\np.rubric {\n  display: flex;\n  flex-direction: column;\n}\n\n/**\n * Seealso is kind of like a vertically-collapsed admonition\n */\n.seealso dd {\n  margin-top: 0;\n  margin-bottom: 0;\n}\n","/**\n * Miscellaneous color functions and mixins\n**/\n\n// loading the math module\n@use \"sass:math\";\n\n// We must add ::before pseudo-element to some theme components (such as admonitions)\n// because users were instructed to customize the background color this way.\n@mixin legacy-backdrop-placeholder {\n  &:before {\n    content: \"\";\n    width: 100%;\n    height: 100%;\n    position: absolute;\n    left: 0;\n    top: 0;\n    z-index: -1;\n    // So that hovering over the text within background is still possible.\n    // Otherwise the background overlays the text and you cannot click or select easily.\n    // ref: https://developer.mozilla.org/en-US/docs/Web/CSS/pointer-events\n    pointer-events: none;\n  }\n}\n\n/**\n* Function to get items from nested maps\n*/\n// @param {Map} $map - Map\n// @param {Arglist} $keys - Keys to fetc\n// @return {*}\n@function map-deep-get($map, $keys...) {\n  @each $key in $keys {\n    $map: map-get($map, $key);\n  }\n  @return $map;\n}\n\n/**\n  * Function to check if the color needs converting to a \"color\" type\n  * if it is a string we cannot use other color manipulation functions\n  * It is used to create the sphinx-design colours as these are often interpolated\n  */\n// @param {String/Color} $color - Color definition from map\n// @return {Color} - Color type (in hex)\n@function check-color($color) {\n  @if type-of($color) == string {\n    $color: from-hex($color);\n  }\n  @return $color;\n}\n\n/**\n  * Function to convert the string representation of a color to a color type (hex)\n  */\n// @param {String} $string - String representation of a color\n@function from-hex($string) {\n  $string-lower: to-lower-case($string);\n  $r: \"\";\n  $g: \"\";\n  $b: \"\";\n  $hex: \"0\" \"1\" \"2\" \"3\" \"4\" \"5\" \"6\" \"7\" \"8\" \"9\" \"a\" \"b\" \"c\" \"d\" \"e\" \"f\";\n  $length: str-length($string);\n  $max: if($length == 4, 1, 2);\n\n  // Check for length accuracy\n  @if $length != 4 and $length != 7 {\n    @return $string;\n  }\n\n  // Loop from the second character (omitting #)\n  @for $i from 2 through $length {\n    $c: str-slice($string-lower, $i, $i);\n\n    // If wrong character, return\n    @if index($hex, $c) == null {\n      @return $string;\n    }\n\n    @if str-length($r) < $max {\n      $r: $r + $c;\n    } @else if str-length($g) < $max {\n      $g: $g + $c;\n    } @else if str-length($b) < $max {\n      $b: $b + $c;\n    }\n  }\n\n  @if $length == 4 {\n    $r: $r + $r;\n    $g: $g + $g;\n    $b: $b + $b;\n  }\n\n  @return rgb(_hex-to-dec($r), _hex-to-dec($g), _hex-to-dec($b));\n}\n\n@function _hex-to-dec($string) {\n  $hex: \"0\" \"1\" \"2\" \"3\" \"4\" \"5\" \"6\" \"7\" \"8\" \"9\" \"a\" \"b\" \"c\" \"d\" \"e\" \"f\";\n  $string: to-lower-case($string);\n  $length: str-length($string);\n\n  $dec: 0;\n  @for $i from 1 through $length {\n    $factor: 1 + (15 * ($length - $i));\n    $index: index($hex, str-slice($string, $i, $i));\n    $dec: $dec + $factor * ($index - 1);\n  }\n\n  @return $dec;\n}\n","// Style API docs from sphinx' autodoc / autosummary\n\n/*******************************************************************************\n* Styling for field lists\n*/\n\n/* grey highlighting of 'parameter' and 'returns' field */\ntable.field-list {\n  border-collapse: separate;\n  border-spacing: 10px;\n  margin-left: 1px;\n\n  th.field-name {\n    padding: 1px 8px 1px 5px;\n    white-space: nowrap;\n    background-color: var(--pst-color-surface);\n  }\n\n  /* italic font for parameter types */\n  td.field-body {\n    p {\n      font-style: italic;\n\n      > strong {\n        font-style: normal;\n      }\n    }\n\n    /* reduced space around parameter description */\n    blockquote {\n      border-left: none;\n      margin: 0em 0em 0.3em;\n      padding-left: 30px;\n    }\n  }\n}\n\n/*******************************************************************************\n* Styling for autosummary tables\n*/\n\n.table.autosummary {\n  // The first column (with the signature) should not wrap\n  td:first-child {\n    white-space: nowrap;\n  }\n}\n\n/* overriding basic.css to use our own monospace font */\n.sig {\n  font-family: var(--pst-font-family-monospace);\n}\n\n/* C++ specific styling - overriding the basic.css to avoid custom colors*/\n\n.sig-inline.c-texpr,\n.sig-inline.cpp-texpr {\n  font-family: unset;\n}\n\n.sig.c .k,\n.sig.c .kt,\n.sig.cpp .k,\n.sig.cpp .kt {\n  color: var(--pst-color-text-base);\n}\n\n.sig.c .m,\n.sig.cpp .m {\n  color: var(--pst-color-text-base);\n}\n\n.sig.c .s,\n.sig.c .sc,\n.sig.cpp .s,\n.sig.cpp .sc {\n  color: var(--pst-color-text-base);\n}\n\n// addition\n\n// .sig.c .sig-name .n,\n// .sig.cpp .sig-name .n {\n//   color: var(--pst-color-inline-code);\n// }\n\n.sig-name {\n  color: var(--pst-color-inline-code);\n}\n\n.sig-param .o,\n.sig-param .default_value {\n  color: var(--pst-color-text-muted);\n  font-weight: normal;\n}\n\n// change target color for dark theme\ndt:target,\nspan.highlighted {\n  background-color: var(--pst-color-target);\n}\n\n.viewcode-back {\n  font-family: var(--pst-font-family-base);\n}\n\n.viewcode-block:target {\n  border-top: 1px solid var(--pst-color-border);\n  border-bottom: 1px solid var(--pst-color-border);\n  position: relative;\n  background-color: var(--pst-color-target);\n}\n\n/*******************************************************************************\n* Styling for autosummary titles like \"parameters\" and \"returns\"\n*/\n\n// the API selector\n// from https://github.com/pradyunsg/furo/blob/main/src/furo/assets/styles/content/_api.sass#L6)\ndl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(.simple) {\n  //increase margin bottom after the dl elements\n  margin-bottom: 3rem;\n\n  dd {\n    margin-left: 2rem;\n\n    // Fix until this will be solved to Sphinx https://github.com/sphinx-doc/sphinx/issues/10815\n    & > dl.simple > dt {\n      display: flex;\n    }\n  }\n\n  dl.field-list {\n    display: grid;\n    grid-template-columns: unset;\n  }\n\n  dt.field-odd,\n  dt.field-even {\n    margin-top: 0.2rem;\n    margin-bottom: 0.1rem;\n    background-color: var(--pst-color-surface);\n  }\n}\n","/**\n * Code block styling\n * Note that we inherit a lot of styling from Bootstrap so not many rules here.\n */\n\n// General code block behavior\n// Unset bootstrap behavior\ndiv[class*=\"highlight-\"],\ndiv.highlight,\ndiv.literal-block-wrapper {\n  display: flex;\n  flex-direction: column;\n  width: unset;\n  border-radius: $admonition-border-radius;\n}\n\n// Code blocks with captions\n// There's a wrapper when the code block has a title\ndiv.literal-block-wrapper {\n  border: 1px solid var(--pst-color-border);\n  border-radius: $admonition-border-radius;\n\n  // This is where the title goes\n  div.code-block-caption {\n    margin: 0;\n    border-bottom: 1px solid var(--pst-color-border);\n    padding: 0.5rem;\n    font-size: 1rem;\n    font-weight: var(--pst-font-weight-caption);\n\n    a.headerlink {\n      font-size: inherit;\n    }\n  }\n\n  // Remove the upper border radius since we want it to connect with the title\n  // Remove the box shadow so the wrapper gets the shadow instead\n  div[class*=\"highlight-\"] {\n    margin: 0;\n    border-radius: 0;\n    pre {\n      border: none;\n      box-shadow: none;\n    }\n  }\n}\n\n/**\n * In-line code\n */\ncode.literal {\n  padding: 0.1rem 0.25rem;\n  background-color: var(--pst-color-surface);\n  border: 1px solid var(--pst-color-border);\n  border-radius: 0.25rem;\n}\n\na > code {\n  color: var(--pst-color-inline-code-links);\n}\n\n// Fix for Sphinx's \"highlight\" directive - this is an issue with our accessible pygments theme\n// and the colour we are using for the background of the code blocks.\nhtml[data-theme=\"light\"] .highlight .nf {\n  color: #0078a1 !important;\n}\n\n// Minimum opacity needed for linenos to be WCAG AA conformant\nspan.linenos {\n  opacity: 0.8 !important;\n}\n","figure {\n  a.headerlink {\n    // So that header link doesn't push caption to be off-center.\n    position: absolute;\n    font-size: inherit;\n  }\n  // Default headerlink hover doesn't trigger on figures\n  &:hover a.headerlink {\n    visibility: visible;\n  }\n\n  figcaption {\n    font-family: var(--pst-font-family-heading);\n    font-weight: var(--pst-font-weight-caption);\n    color: var(--pst-color-text-muted);\n    margin-left: auto;\n    margin-right: auto;\n\n    table.table {\n      width: fit-content;\n      margin-left: auto;\n      margin-right: auto;\n    }\n  }\n}\n","// For consistency, add bracket around footnotes/citations which are\n// cited more than once. E.g. [Newton](1,2) instead of Newton(1,2)\ndt.label > span.brackets:not(:only-child):before {\n  content: \"[\";\n}\n\ndt.label > span.brackets:not(:only-child):after {\n  content: \"]\";\n}\n\n// Make footnote as a superscript\na.footnote-reference {\n  vertical-align: super;\n  font-size: small;\n}\n\n// Docutils 0.18 uses an `aside.footnote` container with different internal structure\naside.footnote {\n  margin-bottom: 0.5rem;\n  &:last-child {\n    margin-bottom: 1rem;\n  }\n  span.label,\n  span.backrefs {\n    font-weight: bold;\n  }\n\n  &:target {\n    background-color: var(--pst-color-target);\n  }\n}\n","/**\n * Hacky fixes that don't fit cleanly into other sections\n */\n\n// Ensure user highlighting/selecting behaves properly\n// From https://stackoverflow.com/a/34372191\ntable.highlighttable td.linenos,\nspan.linenos,\ndiv.doctest > div.highlight span.gp {\n  /* gp: Generic.Prompt */\n  user-select: none;\n  -webkit-user-select: text; /* Safari fallback only */\n  -webkit-user-select: none; /* Chrome/Safari */\n  -moz-user-select: none; /* Firefox */\n  -ms-user-select: none; /* IE10+ */\n}\n","// Override bootstrap by restoring the basic theme default.\ndd {\n  margin-top: 3px;\n  margin-bottom: 10px;\n  margin-left: 30px;\n}\n\nol,\nul {\n  padding-inline-start: 2rem;\n  li > p:first-child {\n    margin-bottom: 0.25rem;\n    margin-top: 0.25rem;\n  }\n}\n","// GitHub blockquote style\nblockquote {\n  padding: 1em 1em;\n  color: var(--pst-color-text-muted);\n  border-left: 0.25em solid var(--pst-color-border);\n  border-radius: $admonition-border-radius;\n  position: relative;\n\n  p {\n    color: var(--pst-color-text-base);\n  }\n\n  // remove padding from included line-block to avoid duplication\n  .line-block {\n    margin: 0 0;\n  }\n\n  // remove margin bottom for the last p\n  p:last-child {\n    margin-bottom: 0;\n  }\n\n  @include legacy-backdrop-placeholder;\n  background-color: var(--pst-color-surface);\n\n  //hack to make the text in the blockquote selectable\n  &:before {\n    z-index: -1;\n  }\n}\n","/**\n * Span-level styling within content\n */\n\nspan.guilabel {\n  border: 1px solid var(--pst-color-info);\n  color: var(--pst-color-info);\n  font-size: 80%;\n  font-weight: 700;\n  border-radius: 4px;\n  padding: 2.4px 6px;\n  margin: auto 2px;\n  position: relative;\n  @include legacy-backdrop-placeholder;\n  background-color: var(--pst-color-info-bg);\n}\n\na.reference.download:before {\n  content: var(--pst-icon-download);\n  font: var(--fa-font-solid);\n  font-size: 0.8em;\n  padding: 0 0.25em;\n  color: var(--pst-color-text-muted);\n}\n","/**\n * Tables\n */\n\n// ensure table will fit in the article width and make them y-scrollable\ntable {\n  display: table;\n  overflow: auto;\n\n  // default to table-center\n  margin-left: auto;\n  margin-right: auto;\n\n  &.table-right {\n    margin-right: 0;\n  }\n\n  &.table-left {\n    margin-left: 0;\n  }\n}\n\n// customize table caption from bootstrap\n// to display them on top and centered\ntable caption {\n  text-align: center;\n  caption-side: top;\n  color: var(--pst-color-text-muted);\n}\n\n// MyST Markdown tables use these classes to control alignment\nth,\ntd {\n  &.text-align\\:left {\n    text-align: left;\n  }\n\n  &.text-align\\:right {\n    text-align: right;\n  }\n\n  &.text-align\\:center {\n    text-align: center;\n  }\n}\n\n// override bootstrap background colors\n.table {\n  --bs-table-bg: transparent;\n}\n","/**\n * Style the toctree component in pages (avoid modifying the navbars)\n */\n.toctree-wrapper {\n  p.caption {\n    font-size: 1.5em;\n    margin-bottom: 0em;\n  }\n\n  & > ul {\n    padding-left: 0;\n  }\n\n  li[class^=\"toctree-l\"] {\n    list-style: none;\n    margin-bottom: 0.2em;\n\n    & > a {\n      list-style: none;\n      font-size: 1.1em;\n    }\n\n    & > ul {\n      list-style: none;\n      padding-inline-start: 1.5em;\n    }\n  }\n\n  // slightly bigger font for l1\n  .toctree-l1 > a {\n    font-size: 1.3em;\n  }\n}\n\ndiv.topic.contents,  // Docutils <= 0.17\nnav.contents  // Docutils >= 0.18\n{\n  // Style similarly to toctree\n  ul.simple {\n    list-style: none;\n    padding-left: 0;\n  }\n}\n","/**\n * Mathematics via MathJax.\n *\n * This is designed for MathJax v3\n * ref: https://www.sphinx-doc.org/en/master/usage/extensions/math.html#module-sphinx.ext.mathjax\n */\n\n// Applies to all math elements\nspan.math,\ndiv.math {\n  align-items: center;\n  display: flex;\n  max-width: 100%;\n  // This will be over-ridden for the y-direction and divs\n  overflow: hidden;\n}\n\n// Inline-only\nspan.math {\n  display: inline-flex;\n}\n\n// Block-level only\ndiv.math {\n  gap: 0.5em;\n  // So that the eqno shows up after the equation\n  flex-direction: row-reverse;\n\n  // The equation number / link\n  span.eqno a.headerlink {\n    position: relative;\n    font-size: 1em;\n  }\n\n  // The math container\n  mjx-container {\n    flex-grow: 1;\n    padding-bottom: 0.2rem;\n    overflow: auto;\n\n    // Set height to 0 so that it does not cause scrollbars to appear\n    // ref: https://github.com/mathjax/MathJax/issues/2521\n    mjx-assistive-mml {\n      height: 0;\n    }\n  }\n}\n","/**\n * ABlog\n * ref: https://ablog.readthedocs.io/\n */\n\n/**\n * Sidebar template components\n */\n.ablog-sidebar-item {\n  h2,\n  h3 {\n    font-size: var(--pst-sidebar-header-font-size);\n    // Remove unnecessary vertical whitespace\n    margin-top: 0.5rem;\n\n    // The headers are all links, but this makes them hard to parse\n    // So we change the colors to make them look like headers\n    a {\n      color: var(--pst-color-text-base);\n    }\n  }\n\n  ul {\n    // No bullet points for the primary sidebar items\n    list-style: none;\n    padding-left: 0;\n    // Otherwise a scrollbar randomly shows up\n    overflow-y: hidden;\n    // List of recent post items\n    display: flex;\n    flex-direction: column;\n    gap: 0.5em;\n    margin-bottom: 0;\n\n    // The ablog cloud should move horizontally\n    &.ablog-cloud {\n      flex-direction: row;\n      flex-flow: wrap;\n      gap: 0.5rem;\n\n      // Vertical-align tag clouds\n      li {\n        // Center the tag cloud items\n        display: flex;\n        align-items: center;\n      }\n    }\n  }\n}\n\n/**\n * Previous / next buttons at the bottom\n */\n.ablog__prev-next {\n  font-size: 1.2em;\n  display: flex;\n  padding: 1rem 0;\n\n  // The bottom previous / next arrows\n  > span {\n    // To ensure that the whole thing fits on one line even if there are long titles\n    display: flex;\n    max-width: 45%;\n\n    // Links within each span have the collection of icon + text\n    a {\n      display: flex;\n      align-items: center;\n      margin-left: auto;\n      gap: 1rem;\n      line-height: 1.5rem;\n\n      i:before {\n        color: var(--pst-color-text-base);\n      }\n    }\n  }\n\n  // The first span is for the previous page and aligns to the left\n  span.ablog__prev {\n    i.fa-arrow-circle-left:before {\n      content: var(--pst-icon-angle-left);\n    }\n  }\n\n  // The second span is just an empty space so we remove it because we're\n  // positioning with flex\n  span.ablog__spacer {\n    display: none;\n  }\n\n  // The third span is aligned to the right\n  span.ablog__next {\n    margin-left: auto;\n    text-align: right;\n\n    i.fa-arrow-circle-right:before {\n      content: var(--pst-icon-angle-right);\n    }\n  }\n}\n\n/**\n * {postlist} directive and posts page\n */\n.ablog__collection,\n.postlist {\n  padding-left: 0;\n\n  .ablog-post {\n    list-style: none;\n\n    // Post metadata tags (author, links ,etc) should be a bit smaller\n    .ablog-archive {\n      display: flex;\n      flex-direction: row;\n      flex-wrap: wrap;\n      gap: 1rem;\n      list-style: none;\n      font-size: 0.75rem;\n      padding-left: 0;\n    }\n\n    // Title line should be a bit bigger and bold to stand out\n    .ablog-post-title {\n      margin-top: 0;\n      font-size: 1.25rem;\n\n      a {\n        font-weight: bold;\n      }\n    }\n\n    // Read more button should be a bit bigger\n    .ablog-post-expand {\n      margin-bottom: 0.5rem;\n    }\n  }\n}\n","/**\n * Special cases for Bootstrap functionality\n */\n\n// Bootstrap adds margin to their general container class. However, sphinx/docutils\n// can also generate output with the container class, but in those cases we should\n// not add the margin from bootstrap. Same for max-width.\n.docutils.container {\n  padding-left: unset;\n  padding-right: unset;\n  margin-left: unset;\n  margin-right: unset;\n  max-width: unset;\n  width: unset;\n}\n","/**\n * Sphinx Copybutton\n * ref: https://sphinx-copybutton.readthedocs.io/\n */\n\ndiv.highlight button.copybtn {\n  // Nicer spacing\n  display: flex;\n  align-items: center;\n  justify-content: center;\n\n  // Removes the button background so we more naturally blend with the code cell.\n  background-color: unset;\n\n  // Don't over-ride the success color\n  &:not(.success) {\n    color: var(--pst-color-muted);\n  }\n  border: none;\n  background-color: var(--pst-color-surface);\n\n  &:hover {\n    &:not(.success) {\n      color: var(--pst-color-text);\n      background-color: var(--pst-color-shadow);\n    }\n  }\n\n  // Tooltip styling\n  &.o-tooltip--left:after {\n    color: var(--pst-color-text);\n    background-color: var(--pst-color-surface);\n  }\n}\n","// adapt ethical ad to the theme\n#ethical-ad-placement {\n  .ethical-sidebar a,\n  .ethical-sidebar a:visited,\n  .ethical-sidebar a:hover,\n  .ethical-sidebar a:active,\n  .ethical-footer a,\n  .ethical-footer a:visited,\n  .ethical-footer a:hover,\n  .ethical-footer a:active {\n    color: var(--pst-color-text-base);\n  }\n\n  .ethical-sidebar,\n  .ethical-footer {\n    background-color: var(--pst-color-background);\n    border: 1px solid var(--pst-color-border);\n    border-radius: 5px;\n    color: var(--pst-color-text-base);\n    font-size: 14px;\n    line-height: 20px;\n  }\n}\n","/**\n * Styles for various Sphinx execution libraries.\n * For now, where these define output sections, we simply revert their background\n * to be a \"light theme\" background. This ensures that inputs/outputs behave similarly,\n * because the CSS is often controlled by each package.\n * In the future, we might add dark theme support for specific packages.\n */\n\n/******************************************************************************\n * Jupyter Sphinx\n */\n\n.bd-content div.jupyter_container {\n  // We don't want borders around the whole container, just around code cells\n  border: none;\n  background-color: unset;\n  box-shadow: none;\n\n  // Code cells should have the same style as our other code objects\n  div.output,\n  div.highlight {\n    border-radius: 0.25rem;\n  }\n  div.highlight {\n    background-color: var(--pst-color-surface);\n  }\n\n  // Ensure the style is the same as our code cells. Jupyter Sphinx makes it tiny.\n  .cell_input,\n  .cell_output {\n    border-radius: 0.25rem;\n    pre {\n      padding: 1rem;\n    }\n  }\n}\n","/**\n * Special-cases for packages in the PyData ecosystem\n */\n\n// xarray output display in bootstrap\n.xr-wrap[hidden] {\n  display: block !important;\n}\n","/*******************************************************************************\n* master color map. Only the colors that actually differ between light and dark\n* themes are specified separately.\n*\n* To see the full list of colors see https://www.figma.com/file/rUrrHGhUBBIAAjQ82x6pz9/PyData-Design-system---proposal-for-implementation-(2)?node-id=1234%3A765&t=ifcFT1JtnrSshGfi-1\n*/\n\n/**\n* Function to get items from nested maps\n*/\n// @param {Map} $map - Map\n// @param {Arglist} $keys - Keys to fetch\n// @return {*}\n@function map-deep-get($map, $keys...) {\n  @each $key in $keys {\n    $map: map-get($map, $key);\n  }\n  @return $map;\n}\n\n/* Assign base colors for the PyData theme */\n$color-palette: (\n  // Primary color\n  \"teal\":\n    (\n      \"50\": #f4fbfc,\n      \"100\": #e9f6f8,\n      \"200\": #d0ecf1,\n      \"300\": #abdde6,\n      \"400\": #3fb1c5,\n      \"500\": #0a7d91,\n      \"600\": #085d6c,\n      \"700\": #064752,\n      \"800\": #042c33,\n      \"900\": #021b1f,\n    ),\n  // Secondary color\n  \"violet\":\n    (\n      \"50\": #f4eefb,\n      \"100\": #e0c7ff,\n      \"200\": #d5b4fd,\n      \"300\": #b780ff,\n      \"400\": #9c5ffd,\n      \"500\": #8045e5,\n      \"600\": #6432bd,\n      \"700\": #4b258f,\n      \"800\": #341a61,\n      \"900\": #1e0e39,\n    ),\n  // Neutrals\n  \"gray\":\n    (\n      \"50\": #f9f9fa,\n      \"100\": #f3f4f5,\n      \"200\": #e5e7ea,\n      \"300\": #d1d5da,\n      \"400\": #9ca4af,\n      \"500\": #677384,\n      \"600\": #48566b,\n      \"700\": #29313d,\n      \"800\": #222832,\n      \"900\": #14181e,\n    ),\n  // Accent color\n  \"pink\":\n    (\n      \"50\": #fcf8fd,\n      \"100\": #fcf0fa,\n      \"200\": #f8dff5,\n      \"300\": #f3c7ee,\n      \"400\": #e47fd7,\n      \"500\": #c132af,\n      \"600\": #912583,\n      \"700\": #6e1c64,\n      \"800\": #46123f,\n      \"900\": #2b0b27,\n    ),\n  \"foundation\": (\n    \"white\": #ffffff,\n    // gray-900\n    \"black\": #14181e,\n  )\n);\n\n:root {\n  // Add theme colours to the html root element\n  @each $group-color, $color in $color-palette {\n    @each $color-name, $definition in $color {\n      --pst-#{$group-color}-#{$color-name}: #{$definition};\n    }\n  }\n}\n\n// Static SCSS variables used thoroughout the theme\n// Minimum contrast ratio used for the theme.\n// Acceptable values for WCAG 2.0 are 3, 4.5 and 7.\n// See https://www.w3.org/TR/WCAG20/#visual-audio-contrast-contrast\n// 4.5 - is for text that is 14pt or less\n$min-contrast-ratio-4: 4.5;\n// 3 is for text that is 18pt or bold, or for non-text elements\n$min-contrast-ratio-3: 3;\n\n// Customize the light and dark text colors for use in our color contrast function.\n$foundation-black: #14181e;\n$foundation-white: #ffffff;\n// This is a custom - calculated  color between gray 100 and 200 - to reduce\n// the contrast ratio (avoid a jarring effect)\n$base-light-text: #ced6dd;\n// used in sphinx_design - gray 100\n$foundation-light-gray: #f3f4f5;\n// used in sphinx_design - gray 700\n$foundation-muted-gray: #29313d;\n// used in sphinx_design - gray 800\n$foundation-dark-gray: #222832;\n\n$pst-semantic-colors: (\n  \"primary\": (\n    \"light\": #{map-deep-get($color-palette, \"teal\", \"500\")},\n    \"bg-light\": #{map-deep-get($color-palette, \"teal\", \"200\")},\n    \"dark\": #{map-deep-get($color-palette, \"teal\", \"400\")},\n    \"bg-dark\": #{map-deep-get($color-palette, \"teal\", \"800\")},\n  ),\n  \"secondary\": (\n    \"light\": #{map-deep-get($color-palette, \"violet\", \"500\")},\n    \"bg-light\": #{map-deep-get($color-palette, \"violet\", \"100\")},\n    \"dark\": #{map-deep-get($color-palette, \"violet\", \"400\")},\n    \"bg-dark\": #{map-deep-get($color-palette, \"violet\", \"800\")},\n  ),\n  \"accent\": (\n    \"light\": #{map-deep-get($color-palette, \"pink\", \"500\")},\n    \"bg-light\": #{map-deep-get($color-palette, \"pink\", \"200\")},\n    \"dark\": #{map-deep-get($color-palette, \"pink\", \"400\")},\n    \"bg-dark\": #{map-deep-get($color-palette, \"pink\", \"800\")},\n  ),\n  \"info\": (\n    \"light\": #276be9,\n    \"bg-light\": #dce7fc,\n    \"dark\": #79a3f2,\n    \"bg-dark\": #06245d,\n  ),\n  \"warning\": (\n    \"light\": #f66a0a,\n    \"bg-light\": #f8e3d0,\n    \"dark\": #ff9245,\n    \"bg-dark\": #652a02,\n  ),\n  \"success\": (\n    \"light\": #00843f,\n    \"bg-light\": #d6ece1,\n    \"dark\": #5fb488,\n    \"bg-dark\": #002f17,\n  ),\n  // This is is based on the warning color\n  \"attention\":\n    (\n      \"light\": var(--pst-color-warning),\n      \"bg-light\": var(--pst-color-warning-bg),\n      \"dark\": var(--pst-color-warning),\n      \"bg-dark\": var(--pst-color-warning-bg),\n    ),\n  \"danger\": (\n    \"light\": #d72d47,\n    \"bg-light\": #f9e1e4,\n    \"dark\": #e78894,\n    \"bg-dark\": #4e111b,\n  ),\n  \"text-base\": (\n    \"light\": #{map-deep-get($color-palette, \"gray\", \"800\")},\n    \"dark\": $base-light-text,\n  ),\n  \"text-muted\": (\n    \"light\": #{map-deep-get($color-palette, \"gray\", \"600\")},\n    \"dark\": #{map-deep-get($color-palette, \"gray\", \"400\")},\n  ),\n  \"heading-color\": (\n    \"light\": #{$foundation-white},\n    \"dark\": #{$foundation-black},\n  ),\n  \"shadow\": (\n    \"light\": rgba(0, 0, 0, 0.1),\n    \"dark\": rgba(0, 0, 0, 0.2),\n  ),\n  \"border\": (\n    \"light\": #{map-deep-get($color-palette, \"gray\", \"300\")},\n    \"dark\": #{map-deep-get($color-palette, \"gray\", \"600\")},\n  ),\n  \"border-muted\": (\n    \"light\": rgba(23, 23, 26, 0.2),\n    \"dark\": #{map-deep-get($color-palette, \"gray\", \"700\")},\n  ),\n  \"inline-code\": (\n    \"light\": #{map-deep-get($color-palette, \"pink\", \"600\")},\n    \"dark\": #{map-deep-get($color-palette, \"pink\", \"300\")},\n  ),\n  \"inline-code-links\": (\n    // need to make sure there is enough contrast against the code bg\n    \"light\": #{map-deep-get($color-palette, \"teal\", \"600\")},\n    // keep primary color for dark mode\n    \"dark\": #{map-deep-get($color-palette, \"teal\", \"400\")},\n  ),\n  \"target\": (\n    \"light\": #f3cf95,\n    \"dark\": #675c04,\n  ),\n  // DEPTH COLORS - you can see the elevation colours and shades\n  // in the Figma file https://www.figma.com/file/rUrrHGhUBBIAAjQ82x6pz9/PyData-Design-system---proposal-for-implementation-(2)?node-id=1492%3A922&t=sQeQZehkOzposYEg-1\n  // background: color of the canvas / the furthest back layer\n  \"background\":\n    (\n      \"light\": #{map-deep-get($color-palette, \"foundation\", \"white\")},\n      \"dark\": #{map-deep-get($color-palette, \"foundation\", \"black\")},\n    ),\n  // on-background: provides slight contrast against background\n  // (by use of shadows in light theme)\n  \"on-background\":\n    (\n      \"light\": #{map-deep-get($color-palette, \"foundation\", \"white\")},\n      \"dark\": #{map-deep-get($color-palette, \"gray\", \"800\")},\n    ),\n  \"surface\": (\n    \"light\": #{map-deep-get($color-palette, \"gray\", \"100\")},\n    \"dark\": #{map-deep-get($color-palette, \"gray\", \"700\")},\n  ),\n  // on_surface: object on top of surface object (without shadows)\n  \"on-surface\":\n    (\n      \"light\": #{map-deep-get($color-palette, \"gray\", \"800\")},\n      \"dark\": $foundation-light-gray,\n    ),\n);\n\n/*******************************************************************************\n* write the color rules for each theme (light/dark)\n*/\n\n/* NOTE:\n * Mixins enable us to reuse the same definitions for the different modes\n * https://sass-lang.com/documentation/at-rules/mixin\n * #{something} inserts a variable into a CSS selector or property name\n * https://sass-lang.com/documentation/interpolation\n */\n@mixin theme-colors($mode) {\n  // check if this color is defined differently for light/dark\n  @each $col-name, $definition in $pst-semantic-colors {\n    @if type-of($definition) == map {\n      @each $key, $val in $definition {\n        @if str-index($key, $mode) != null {\n          // since now we define the bg colours in the semantic colours and not\n          // by changing opacity, we need to check if the key contains bg and the\n          // correct mode (light/dark)\n          @if str-index($key, \"bg\") != null {\n            --pst-color-#{$col-name}-bg: #{$val};\n          } @else {\n            --pst-color-#{$col-name}: #{$val};\n          }\n        }\n      }\n    } @else {\n      --pst-color-#{$col-name}: #{$definition};\n    }\n  }\n\n  // assign the \"duplicate\" colors (ones that just reference other variables)\n  & {\n    --pst-color-link: var(--pst-color-primary);\n    --pst-color-link-hover: var(--pst-color-secondary);\n  }\n  // adapt to light/dark-specific content\n  @if $mode == \"light\" {\n    .only-dark,\n    .only-dark ~ figcaption {\n      display: none !important;\n    }\n  } @else {\n    .only-light,\n    .only-light ~ figcaption {\n      display: none !important;\n    }\n    /* Adjust images in dark mode (unless they have class .only-dark or\n     * .dark-light, in which case assume they're already optimized for dark\n     * mode).\n     */\n    img:not(.only-dark):not(.dark-light) {\n      filter: brightness(0.8) contrast(1.2);\n    }\n    /* Give images a light background in dark mode in case they have\n    *  transparency and black text (unless they have class .only-dark or .dark-light, in\n    *  which case assume they're already optimized for dark mode).\n    */\n    .bd-content img:not(.only-dark):not(.dark-light) {\n      background: rgb(255, 255, 255);\n      border-radius: 0.25rem;\n    }\n    // MathJax SVG outputs should be filled to same color as text.\n    .MathJax_SVG * {\n      fill: var(--pst-color-text-base);\n    }\n  }\n}\n\n/* Defaults to light mode if data-theme is not set */\nhtml:not([data-theme]) {\n  @include theme-colors(\"light\");\n}\n\n/* NOTE: @each {...} is like a for-loop\n * https://sass-lang.com/documentation/at-rules/control/each\n */\n@each $mode in (light, dark) {\n  html[data-theme=\"#{$mode}\"] {\n    @include theme-colors($mode);\n    color-scheme: $mode;\n  }\n}\n\n// assign classes too, for runtime use of theme colors\n@each $col-name, $definition in $pst-semantic-colors {\n  .pst-color-#{$col-name} {\n    color: var(--pst-color-#{$col-name});\n  }\n}\n","/*******************************************************************************\n * Special-cases for the sphinx-design library, mainly to make it compatible\n * with the dark/light themes of pydata-sphinx-theme.\n *\n * NOTE: sphinx-design uses !important quite liberally, so here we must do the\n * same for our overrides to have any effect.\n */\n@use \"../variables/color\" as pst-color;\n@use \"sass:meta\";\n@use \"sass:color\";\n\n/*******************************************************************************\n  * Color and variables\n  *\n  * This is a list of the semantic color names from sphinx-design (we only\n  * need to override variables that sphinx-design has actually defined).\n  * https://github.com/executablebooks/sphinx-design/blob/9226a12a/style/_colors.scss#L31-L43\n  */\n$sd-semantic-color-names: (\n  \"primary\",\n  \"secondary\",\n  \"success\",\n  \"info\",\n  \"warning\",\n  \"danger\",\n  \"light\",\n  \"muted\",\n  \"dark\",\n  \"black\",\n  \"white\"\n);\n\n/**\n  * Here we create some extra --pst-color-* variables and use\n  * them to override the value of the corresponding sphinx-design variables.\n  * This is easier than re-writing the sphinx-design rules. Even easier would be\n  * directly assigning our values to the --sd-color-* variables, but then our\n  * downstream users couldn't override *our* colors and have it affect buttons\n  * and badges.\n  *\n  * First, define the extra keys needed to cover the full range of semantic\n  * color names used in sphinx-design, then merge them with the names we\n  * already define for our own needs.\n  * see https://sphinx-design.readthedocs.io/en/latest/css_variables.html\n  */\n$extra-semantic-colors: (\n  \"white\": $foundation-white,\n  \"light\": (\n    light: $foundation-light-gray,\n    bg-light: color.scale($foundation-light-gray, $lightness: 30%),\n    dark: $foundation-light-gray,\n    bg-dark: color.scale($foundation-light-gray, $lightness: -30%),\n  ),\n  \"muted\": (\n    light: $foundation-muted-gray,\n    bg-light: color.scale($foundation-muted-gray, $lightness: 30%),\n    dark: $foundation-light-gray,\n    bg-dark: color.scale($foundation-muted-gray, $lightness: -30%),\n  ),\n  \"dark\": $foundation-dark-gray,\n  \"black\": $foundation-black,\n);\n\n$all-colors: map-merge($pst-semantic-colors, $extra-semantic-colors);\n\n@mixin create-sd-colors($value, $name) {\n  // define the pst variables, so that downstream user overrides will work\n  --pst-color-#{$name}: #{$value};\n  // we are now using a11y-combination to calculate the text color - this is based\n  // on the WCAG color contrast guidelines\n  --pst-color-#{$name}-text: #{a11y-combination($value)};\n  //TODO: highlight seems to be used for buttons @trallard to fix on a11y follow-up work\n  --pst-color-#{$name}-highlight: #{darken($value, 15%)};\n  // override the sphinx-design variables\n  --sd-color-#{$name}: var(--pst-color-#{$name});\n  --sd-color-#{$name}-text: var(--pst-color-#{$name}-text);\n  //TODO: highlight seems to be used for buttons @trallard to fix on a11y follow-up work\n  --sd-color-#{$name}-highlight: var(--pst-color-#{$name}-highlight);\n}\n\n// Now we override the --sd-color-* variables.\n@each $mode in (light, dark) {\n  html[data-theme=\"#{$mode}\"] {\n    // check if this color is defined differently for light/dark\n    @each $name in $sd-semantic-color-names {\n      $definition: map-get($all-colors, $name);\n      @if type-of($definition) == map {\n        @each $key, $value in $definition {\n          @if str-index($key, $mode) != null {\n            // since now we define the bg colours in the semantic colours and not\n            // by changing opacity, we need to check if the key contains bg and the\n            // correct mode (light/dark)\n            @if str-index($key, \"bg\") != null {\n              --sd-color-#{$name}-bg: #{$value};\n              // create local variable\n              $bg-var: --sd-color-#{$name}-bg;\n              $value: check-color($value);\n              --sd-color-#{$name}-bg-text: #{a11y-combination($value)};\n            } @else {\n              $value: check-color($value);\n              @include create-sd-colors($value, $name);\n            }\n          }\n        }\n      } @else {\n        $value: map-get($all-colors, $name);\n        @include create-sd-colors($value, $name);\n      }\n    }\n  }\n}\n\n// Make sure the color border variables are set using our variables\n@each $mode in (light, dark) {\n  html[data-theme=\"#{$mode}\"] {\n    --sd-color-card-border: var(--pst-color-border);\n  }\n}\n\n/*******************************************************************************\n  * shadows\n  */\nhtml[data-theme=\"light\"] {\n  .sd-shadow-xs,\n  .sd-shadow-sm,\n  .sd-shadow-md,\n  .sd-shadow-lg {\n    @include box-shadow();\n  }\n}\n\n/*******************************************************************************\n  * cards\n  */\n\n.bd-content .sd-card {\n  border: 1px solid var(--pst-color-border);\n\n  // TODO - --pst-color-panel-background is not defined... where is this coming from?\n  .sd-card-header {\n    background-color: var(--pst-color-panel-background);\n    border-bottom: 1px solid var(--pst-color-border);\n  }\n  .sd-card-footer {\n    background-color: var(--pst-color-panel-background);\n    border-top: 1px solid var(--pst-color-border);\n  }\n\n  .sd-card-body {\n    background-color: var(--pst-color-panel-background);\n  }\n}\n/*******************************************************************************\n  * tabs\n  */\n\n.bd-content .sd-tab-set {\n  > input {\n    // Active tab label\n    &:checked + label {\n      border-color: transparent transparent var(--pst-color-primary); // top LR bottom\n      color: var(--pst-color-primary);\n    }\n\n    // Hover label\n    &:not(:checked) + label:hover {\n      border-color: var(--pst-color-secondary);\n      color: var(--pst-color-secondary);\n    }\n  }\n\n  // Tab label\n  > label {\n    color: var(--pst-color-text-muted);\n    border-top: 0.125rem solid transparent; // so hover isn't just color change\n    padding-top: 0.5em; // same as bottom padding, so hover overline looks OK\n    // Hovered label\n    html &:hover {\n      color: var(--pst-color-secondary);\n      border-color: var(--pst-color-secondary);\n    }\n  }\n}\n\n/*******************************************************************************\n* Dropdowns\n*/\n\ndetails.sd-dropdown {\n  // Remove all borders to over-ride SD behavior, and we'll add our own later\n  border: 0px !important;\n  summary.sd-card-header {\n    border: 0 !important;\n    & + div.sd-summary-content {\n      border: 0;\n    }\n  }\n  // Drop shadow should behave same as admonitions\n  @include box-shadow();\n\n  // Header is where the \"clickable\" box goes\n  summary.sd-card-header {\n    display: flex;\n    align-items: center;\n    position: relative; // So background color works\n    font-weight: 600;\n    padding-top: 0.5rem;\n    padding-bottom: 0.5rem;\n\n    // Set a variable that we can re-use for colors later\n    // We must set this in the current and content sibling container\n    // so that it is defined in both places\n    --pst-sd-dropdown-color: var(--pst-gray-500);\n    --pst-sd-dropdown-bg-color: var(--pst-color-surface);\n    & + div.sd-summary-content {\n      --pst-sd-dropdown-color: var(--sd-color-card-border);\n    }\n    @each $name in $sd-semantic-color-names {\n      &.sd-bg-#{$name} {\n        --pst-sd-dropdown-color: var(--sd-color-#{$name});\n        --pst-sd-dropdown-bg-color: var(--sd-color-#{$name}-bg);\n        // Otherwise it won't be defined in the sibling element\n        & + div.sd-summary-content {\n          --pst-sd-dropdown-color: var(--sd-color-#{$name});\n          --pst-sd-dropdown-bg-color: var(--sd-color-#{$name}-bg);\n        }\n      }\n      &.sd-bg-text-#{$name} {\n        // Use the WCAG conformant text color\n        color: var(--sd-color-#{$name}-bg-text) !important;\n      }\n    }\n\n    @include legacy-backdrop-placeholder;\n    background-color: var(--pst-sd-dropdown-bg-color) !important;\n\n    // Add a left border with the same structure as our admonitions\n    border-left: 0.2rem solid var(--pst-sd-dropdown-color) !important;\n    & + div.sd-summary-content {\n      border-left: 0.2rem solid var(--pst-sd-dropdown-color) !important;\n      border-bottom-left-radius: calc(0.25rem - 1px);\n      background-color: var(--pst-color-on-background);\n    }\n    span.sd-summary-icon {\n      display: inline-flex;\n      align-items: center;\n      color: var(--pst-sd-dropdown-color) !important;\n      svg {\n        opacity: 1;\n      }\n    }\n\n    // Positioning of the caret\n    .sd-summary-up,\n    .sd-summary-down {\n      top: 0.7rem;\n    }\n  }\n}\n","/**\n * Sphinx togglebutton\n */\n\n.bd-content {\n  // Admonition toggles\n  .admonition {\n    button.toggle-button {\n      color: inherit;\n    }\n  }\n\n  // Details buttons\n  details.toggle-details {\n    // Over-ride border color to re-use our primary color\n    summary {\n      border-left: 3px solid var(--pst-color-primary);\n    }\n  }\n}\n","/**\n * Styles for various Sphinx execution libraries to display pre-executed notebooks.\n * For now, where these define output sections, we simply revert their background\n * to be a \"light theme\" background. This ensures that inputs/outputs behave similarly,\n * because the CSS is often controlled by each package.\n * In the future, we might add dark theme support for specific packages.\n */\n\n/*******************************************************************************\n * nbsphinx\n */\nhtml div.rendered_html\n// NBsphinx ipywidgets output selector\nhtml .jp-RenderedHTMLCommon {\n  table {\n    table-layout: auto;\n  }\n}\n\n// Dark theme special-cases\nhtml[data-theme=\"dark\"] .bd-content {\n  .nboutput {\n    .output_area.rendered_html {\n      @include cell-output-background;\n    }\n\n    .output_area.stderr {\n      background: var(--pst-color-danger);\n    }\n  }\n}\n\n// Add extra padding to the final item in an nbsphinx container\ndiv.nblast.container {\n  margin-bottom: 1rem;\n}\n\n/*******************************************************************************\n * myst NB\n */\n\ndiv.cell_output .output {\n  max-width: 100%;\n  overflow-x: auto;\n}\n\n// Dark theme special-cases\nhtml[data-theme=\"dark\"] .bd-content {\n  div.cell_output {\n    img,\n    .text_html {\n      @include cell-output-background;\n    }\n  }\n}\n\n// Prevent tables from scrunching together\n.bd-content {\n  div.cell_input {\n    display: flex;\n    flex-direction: column;\n    justify-content: stretch;\n  }\n\n  div.cell_input,\n  div.output {\n    border-radius: $admonition-border-radius;\n  }\n\n  div.output {\n    table {\n      table-layout: auto;\n    }\n  }\n}\n","/**\n * style for the various mapping libs based on leaflet (folium, geemap, ipyleaflet)\n * mainly ensure the good display of the maps in both themes and avoid the customization\n * of the tiles\n */\n\n/**\n * avoid border override from pydata-sphinx-theme\n * minimal selctor to get the priority\n */\nhtml[data-theme=\"dark\"] .bd-content img.leaflet-tile.leaflet-tile-loaded {\n  border-radius: 0;\n  padding: 0;\n}\n","/**\n * /search.html page special-cases\n */\n\n.bd-search-container {\n  /*******************************************\n  * Search results\n  */\n  // Whitespace\n  div#search-results {\n    > h2 {\n      font-size: var(--pst-font-size-icon);\n      margin-top: 0;\n    }\n\n    p.search-summary {\n      color: var(--pst-color-text-muted);\n    }\n  }\n\n  ul.search {\n    margin: 0;\n    list-style: none;\n\n    li {\n      background-image: none;\n      padding: 1rem 0;\n      margin: 1rem 0;\n      border-top: 1px solid var(--pst-color-text-muted);\n\n      // First link is the page title, it should be a bit bigger\n      > a {\n        font-size: 1.2em;\n      }\n\n      div.context,\n      p.context {\n        color: var(--pst-color-text-base);\n        margin: 0.5em 0 0 0;\n\n        // Add a # before page section titles to make it clear they are sections\n        a:before {\n          content: \"#\";\n          padding-right: 0.2em;\n          color: var(--pst-color-text-muted);\n        }\n      }\n    }\n  }\n}\n"],"names":[],"sourceRoot":""}
\ No newline at end of file
diff --git a/_static/styles/sphinx-book-theme.css b/_static/styles/sphinx-book-theme.css
new file mode 100644
index 0000000..56c23f1
--- /dev/null
+++ b/_static/styles/sphinx-book-theme.css
@@ -0,0 +1,8 @@
+/*! sphinx-book-theme CSS
+ * BSD 3-Clause License
+ * Copyright (c) 2020, EBP
+ * All rights reserved.
+ *
+ * This follows the 7-1 pattern described here:
+ * https://sass-guidelin.es/#architecture
+ */html[data-theme=dark],html[data-theme=light]{--pst-font-size-base:none;--pst-color-secondary:#e89217}html[data-theme=light]{--sbt-color-announcement:#616161;--pst-color-primary:#176de8}html[data-theme=dark]{--pst-color-primary:#528fe4;--sbt-color-announcement:#616161;--pst-color-background:#121212}html{scroll-padding-top:4rem}.sbt-scroll-pixel-helper{position:absolute;width:0;height:0;top:0;left:0}.d-n,.onlyprint{display:none}@media print{.onlyprint{display:block!important}}@media print{.noprint{display:none!important}}.bd-article-container h1,.bd-article-container h2,.bd-article-container h3,.bd-article-container h4,.bd-article-container h5,.bd-article-container p.caption{color:var(--pst-color-muted)}.bd-article-container h1,.bd-article-container h2{font-weight:500}a.brackets:before{color:inherit;font-family:inherit;margin-right:0}table{position:relative}@media print{.bd-main .bd-content{margin-left:2rem;height:auto}.bd-main .bd-content #jb-print-docs-body{margin-left:0}.bd-main .bd-content #jb-print-docs-body h1{font-size:3em;text-align:center;margin-bottom:0}.bd-main .bd-content .bd-article{padding-top:0}.bd-main .bd-content .bd-article h1:first-of-type{display:none}.bd-main .bd-content .container{min-width:0!important}.bd-main .bd-content h1{margin-top:1em;margin-bottom:1em}.bd-main .bd-content h1,.bd-main .bd-content h2,.bd-main .bd-content h3,.bd-main .bd-content h4{break-after:avoid;color:#000}.bd-main .bd-content table{break-inside:avoid}.bd-main .bd-content pre{word-wrap:break-word}.bd-main .bd-content a.headerlink{display:none}.bd-main .bd-content aside.margin,.bd-main .bd-content aside.sidebar,.bd-main .bd-content blockquote.epigraph{border:none}.bd-main .bd-content .footer{margin-top:1em}.bd-main .bd-content #jb-print-toc{margin-bottom:1.5rem;margin-left:0}.bd-main .bd-content #jb-print-toc .section-nav{border-left:0!important;list-style-type:disc!important;margin-left:3em!important}.bd-main .bd-content #jb-print-toc .section-nav a{text-decoration:none!important}.bd-main .bd-content #jb-print-toc .section-nav li{display:list-item!important}.bd-main .bd-content #jb-print-toc .section-nav .nav{display:none}.bd-main .bd-footer-content{display:none!important}}.bd-header-announcement{background-color:var(--sbt-color-announcement);color:#fff}.bd-main .bd-content{justify-content:left}.bd-main .bd-content .bd-article-container{padding:0;overflow-x:unset;min-width:0}@media (min-width:1200px){.bd-main .bd-content .bd-article-container{max-width:calc(100% - var(--pst-sidebar-secondary))}}.bd-main .bd-content .bd-article-container .bd-article{padding-right:2rem;padding-left:2rem}@media (max-width:768px){.bd-main .bd-content .bd-article-container .bd-article{padding-right:1rem;padding-left:1rem}}.bd-main .bd-content .bd-article-container details.above-input summary,.bd-main .bd-content .bd-article-container details.below-input summary{border-left:3px solid var(--pst-color-primary)}@media (min-width:768px){label.sidebar-toggle.primary-toggle{display:inline-block}}@media (max-width:768px){label.sidebar-toggle.primary-toggle{margin-bottom:0}}@media (min-width:992px){label.sidebar-toggle.secondary-toggle{display:none}}@media (max-width:768px){label.sidebar-toggle.secondary-toggle{margin-bottom:0}}.bd-header-article{display:flex;align-items:center;position:sticky;top:0;background-color:var(--pst-color-background);transition:left .2s;font-size:.9em;padding:0 1rem;z-index:1020}@media (max-width:768px){.bd-header-article{padding:0 .5rem;height:3.5rem}}.scrolled .bd-header-article{box-shadow:0 6px 6px -6px var(--pst-color-shadow)}.bd-header-article .header-article__inner{padding:0}.bd-header-article .header-article-items{display:flex;align-items:center;height:3rem;width:100%}.bd-header-article .header-article-item{display:flex;align-items:center}.bd-header-article .article-header-buttons{display:flex}.bd-header-article .btn{font-size:1.3rem;color:var(--pst-color-text-muted);border:none;padding:0 .5rem;display:flex;align-items:center}.bd-header-article .btn svg{width:1.3rem}.bd-header-article .btn.show,.bd-header-article .btn:hover{color:var(--pst-color-text-base);border:none}.bd-header-article .btn.show+.dropdown-menu,.bd-header-article .btn:hover+.dropdown-menu{display:block}.bd-header-article .btn:focus{box-shadow:none}.bd-header-article .btn.dropdown-toggle:after{display:none}.bd-header-article div.dropdown{display:flex;align-items:center}.bd-header-article .theme-switch-button{margin:0}.bd-header-article .theme-switch-button button,.bd-header-article .theme-switch-button i,.bd-header-article .theme-switch-button span{padding:0}.bd-header-article .theme-switch-button i,.bd-header-article .theme-switch-button span{transition:color .25s ease-out}.bd-header-article .theme-switch-button:active,.bd-header-article .theme-switch-button:hover{background-color:unset!important}.bd-header-article .theme-switch-button:active i,.bd-header-article .theme-switch-button:active span,.bd-header-article .theme-switch-button:hover i,.bd-header-article .theme-switch-button:hover span{color:var(--pst-color-text-base)}.bd-header-article .dropdown-menu{top:2rem;transform:translateX(-75%);box-shadow:0 .2rem .5rem var(--pst-color-shadow),0 0 .0625rem var(--pst-color-shadow)!important;border-color:var(--pst-color-border);background-color:var(--pst-color-background);color:var(--pst-color-text-muted)}.bd-header-article .dropdown-menu:hover{display:block}.bd-header-article .dropdown-menu .dropdown-item{display:inline-flex;align-items:center;padding-left:.5em;font-size:1em}.bd-header-article .dropdown-menu .dropdown-item:hover{text-decoration:none;background-color:initial;color:var(--pst-color-text-base)}.bd-header-article .dropdown-menu .dropdown-item span img{height:1em}.bd-header-article .dropdown-menu .dropdown-item span.btn__icon-container{width:1.7em;align-items:center;display:inline-flex;justify-content:center}.bd-header{position:inherit}.bd-header label.sidebar-toggle{display:none}.bd-sidebar-primary{top:0;max-height:100vh;padding:1rem;transition:margin-left .25s ease 0s,opacity .25s ease 0s,visibility .25s ease 0s}@media (max-width:768px){.bd-sidebar-primary{z-index:1081}}.bd-sidebar-primary .sidebar-primary-items__start{border-top:none}@media (min-width:992px){.bd-sidebar-primary{flex-basis:20%}}@media (min-width:992px){input#__primary:checked~.bd-container .bd-sidebar-primary{margin-left:-20%;visibility:hidden;opacity:0}}.bd-sidebar-secondary{top:0}@media (max-width:992px){.bd-sidebar-secondary{z-index:1081}}.bd-sidebar-secondary .sidebar-secondary-items{padding:0;display:flex;gap:.5rem}.bd-sidebar-secondary .sidebar-secondary-items .sidebar-secondary-item{padding-top:0;padding-bottom:0}.bd-sidebar-secondary .onthispage{height:3rem;min-height:3rem;display:flex;gap:.5rem;align-items:center;margin:0;color:var(--pst-color-muted)}@media (min-width:992px){.bd-sidebar-secondary{background:var(--pst-color-background);height:fit-content;transition:max-height .4s ease;z-index:2;padding:0}.bd-sidebar-secondary .toc-item{border-left-color:var(--pst-color-surface);padding-top:0}.bd-sidebar-secondary .toc-item nav.page-toc{margin-bottom:0;transition:opacity .4s ease}.bd-sidebar-secondary.hide:not(:hover){max-height:3rem;overflow-y:hidden}.scrolled .bd-sidebar-secondary.hide:not(:hover){box-shadow:0 6px 6px -6px rgba(0,0,0,.3)}.bd-sidebar-secondary.hide:not(:hover) .onthispage:after{opacity:1;content:"\f107";font-family:Font Awesome\ 5 Free;font-weight:900;padding-left:.5em;transition:opacity .3s ease}.bd-sidebar-secondary.hide:not(:hover) nav.page-toc{opacity:0}}footer{font-size:var(--sbt-font-size-small-1)}footer.bd-footer-content{display:flex;flex-wrap:wrap;padding:15px;border-top:1px solid #ccc;font-size:87.5%}footer.bd-footer-content .bd-footer-content__inner{padding-left:0}footer.bd-footer-content .bd-footer-content__inner p{margin-bottom:0}.bd-footer-article{padding:0 1rem}@media (max-width:768px){.bd-footer-article{padding:0 .5rem}}#pst-back-to-top{font-size:.8rem}@media (min-width:1200px){#pst-back-to-top{display:none!important}}.bd-sidebar-primary .navbar-icon-links{column-gap:.5rem}.bd-sidebar-primary .navbar-icon-links .nav-link i,.bd-sidebar-primary .navbar-icon-links .nav-link span{font-size:1.2rem}.bd-sidebar-primary .navbar-icon-links .nav-link img{font-size:.8rem}.navbar-brand{height:unset;max-height:unset;flex-direction:column;justify-content:center;gap:.25rem}.navbar-brand:hover{text-decoration:none}.navbar-brand .logo__title{font-size:1.25rem;white-space:normal;text-align:center}.navbar-brand .logo__image{height:unset}.bd-search-container{margin:2em}.bd-search-container #search-results h2:first-child{display:none}.search-button-field{width:100%;font-size:.9rem;display:none}.search-button-field .search-button__kbd-shortcut{margin-left:auto}@media (min-width:992px){.search-button{display:none!important}.search-button-field{display:flex}}div#searchbox{padding-right:2rem;padding-left:2rem}@media (max-width:768px){div#searchbox{padding-right:1rem;padding-left:1rem}}@media (min-width:768px){div#searchbox p.highlight-link{margin-left:0}div#searchbox p.highlight-link a{font-size:1rem}}img{max-width:100%}img.align-center{margin-left:auto;margin-right:auto;display:block}img.align-left{clear:left;float:left;margin-right:1em}img.align-right{clear:right;float:right;margin-left:1em}div.figure{width:100%;margin-bottom:1em;text-align:center}div.figure.align-left{text-align:left}div.figure.align-left p.caption{margin-left:0}div.figure.align-right{text-align:right}div.figure.align-right p.caption{margin-right:0}div.figure p.caption{margin:.5em 10%}div.figure.margin-caption p.caption,div.figure.margin p.caption{margin:.5em 0}div.figure.margin-caption p.caption{text-align:left}div.figure span.caption-number{font-weight:700}div.figure span{font-size:.9rem}label.margin-toggle{margin-bottom:0}label.margin-toggle.marginnote-label{display:none}label.margin-toggle sup{user-select:none}@media (max-width:992px){label.margin-toggle{cursor:pointer;color:#0071bc}label.margin-toggle.marginnote-label{display:inline}label.margin-toggle.marginnote-label:after{content:"\2295"}}input.margin-toggle{display:none}@media (max-width:992px){input.margin-toggle:checked+.marginnote,input.margin-toggle:checked+.sidenote{display:block;float:left;left:1rem;clear:both;width:95%;margin:1rem 2.5%;position:relative}}span.marginnote,span.sidenote{z-index:2;position:relative;width:40%;float:right;background-color:unset;font-size:.9em;margin-left:.5rem;border-left:none}span.marginnote sup,span.sidenote sup{user-select:none}@media (min-width:992px),print{span.marginnote,span.sidenote{width:33%;margin:0 -36% 0 0;clear:right}span.marginnote p.sidebar-title,span.sidenote p.sidebar-title{margin-bottom:-1rem;border-bottom:none;padding-left:0}span.marginnote p.sidebar-title~*,span.sidenote p.sidebar-title~*{padding-left:0;padding-right:0}}@media (max-width:992px){span.marginnote,span.sidenote{display:none}}aside.sidebar .note{margin:1rem;padding:0 0 1rem}aside.sidebar .admonition-title{margin:0 -1rem 0 0}aside.sidebar.margin .sidebar-title:empty{display:none}aside.sidebar.margin .admonition{margin:.5rem;padding-left:0;padding-right:0}aside.sidebar.margin .admonition .admonition-title{margin-left:0;margin-right:0}@media (min-width:992px){aside.sidebar.margin{border:none}aside.sidebar.margin .admonition{margin:1rem 0;padding:0 0 1rem}}.cell.tag_margin,.cell.tag_popout,.margin.docutils.container,aside.margin,div.margin,figure.margin{z-index:2;position:relative;width:40%;float:right;background-color:unset;font-size:.9em;margin-left:.5rem}@media (min-width:992px),print{.cell.tag_margin,.cell.tag_popout,.margin.docutils.container,aside.margin,div.margin,figure.margin{width:33%;margin:0 -36% 0 0;clear:right}.cell.tag_margin p.sidebar-title,.cell.tag_popout p.sidebar-title,.margin.docutils.container p.sidebar-title,aside.margin p.sidebar-title,div.margin p.sidebar-title,figure.margin p.sidebar-title{margin-bottom:-1rem;border-bottom:none;padding-left:0}.cell.tag_margin p.sidebar-title~*,.cell.tag_popout p.sidebar-title~*,.margin.docutils.container p.sidebar-title~*,aside.margin p.sidebar-title~*,div.margin p.sidebar-title~*,figure.margin p.sidebar-title~*{padding-left:0;padding-right:0}}.cell.tag_margin div.cell.tag_margin .cell_output,.cell.tag_popout div.cell.tag_margin .cell_output,.margin.docutils.container div.cell.tag_margin .cell_output,aside.margin div.cell.tag_margin .cell_output,div.margin div.cell.tag_margin .cell_output,figure.margin div.cell.tag_margin .cell_output{padding-left:0}div.figure.margin-caption figcaption,div.figure.margin-caption p.caption,figure.margin-caption figcaption{z-index:2;position:relative;width:40%;float:right;background-color:unset;font-size:.9em;margin-left:.5rem}@media (min-width:992px),print{div.figure.margin-caption figcaption,div.figure.margin-caption p.caption,figure.margin-caption figcaption{width:33%;margin:0 -36% 0 0;clear:right}div.figure.margin-caption figcaption p.sidebar-title,div.figure.margin-caption p.caption p.sidebar-title,figure.margin-caption figcaption p.sidebar-title{margin-bottom:-1rem;border-bottom:none;padding-left:0}div.figure.margin-caption figcaption p.sidebar-title~*,div.figure.margin-caption p.caption p.sidebar-title~*,figure.margin-caption figcaption p.sidebar-title~*{padding-left:0;padding-right:0}}.margin-caption figcaption{text-align:left}div.cell.tag_full-width,div.cell.tag_full_width,div.full-width,div.full_width{z-index:2;position:relative}@media (min-width:992px){div.cell.tag_full-width,div.cell.tag_full_width,div.full-width,div.full_width{max-width:136%;width:136%}}blockquote.epigraph,blockquote.highlights,blockquote.pull-quote{font-size:1.25em;border-left:none;background-color:var(--pst-color-background)}blockquote div>p+p.attribution{font-style:normal;font-size:.9em;text-align:right;color:#6c757d;padding-right:2em}div[class*=highlight-],pre{clear:none}div.cell.tag_output_scroll div.cell_output,div.cell.tag_scroll-input div.cell_input,div.cell.tag_scroll-output div.cell_output{max-height:24em;overflow-y:auto}@media only print{div.utterances,hypothesis-sidebar{display:none}}.thebelab-cell{border:none!important;margin-right:.5em!important}.thebelab-cell .thebelab-input{padding-left:10px!important}.cell.docutils.container{padding-right:0!important}button.thebe-launch-button{height:2.5em;font-size:1em}
\ No newline at end of file
diff --git a/_static/styles/theme.css b/_static/styles/theme.css
new file mode 100644
index 0000000..4519dd9
--- /dev/null
+++ b/_static/styles/theme.css
@@ -0,0 +1,2 @@
+/* Provided by Sphinx's 'basic' theme, and included in the final set of assets */
+@import "../basic.css";
diff --git a/_static/tabs.css b/_static/tabs.css
new file mode 100644
index 0000000..957ba60
--- /dev/null
+++ b/_static/tabs.css
@@ -0,0 +1,89 @@
+.sphinx-tabs {
+  margin-bottom: 1rem;
+}
+
+[role="tablist"] {
+  border-bottom: 1px solid #a0b3bf;
+}
+
+.sphinx-tabs-tab {
+  position: relative;
+  font-family: Lato,'Helvetica Neue',Arial,Helvetica,sans-serif;
+  color: #1D5C87;
+  line-height: 24px;
+  margin: 0;
+  font-size: 16px;
+  font-weight: 400;
+  background-color: rgba(255, 255, 255, 0);
+  border-radius: 5px 5px 0 0;
+  border: 0;
+  padding: 1rem 1.5rem;
+  margin-bottom: 0;
+}
+
+.sphinx-tabs-tab[aria-selected="true"] {
+  font-weight: 700;
+  border: 1px solid #a0b3bf;
+  border-bottom: 1px solid white;
+  margin: -1px;
+  background-color: white;
+}
+
+.sphinx-tabs-tab:focus {
+  z-index: 1;
+  outline-offset: 1px;
+}
+
+.sphinx-tabs-panel {
+  position: relative;
+  padding: 1rem;
+  border: 1px solid #a0b3bf;
+  margin: 0px -1px -1px -1px;
+  border-radius: 0 0 5px 5px;
+  border-top: 0;
+  background: white;
+}
+
+.sphinx-tabs-panel.code-tab {
+  padding: 0.4rem;
+}
+
+.sphinx-tab img {
+	margin-bottom: 24 px;
+}
+
+/* Dark theme preference styling */
+
+@media (prefers-color-scheme: dark) {
+  body[data-theme="auto"] .sphinx-tabs-panel {
+    color: white;
+    background-color: rgb(50, 50, 50);
+  }
+
+  body[data-theme="auto"] .sphinx-tabs-tab {
+    color: white;
+    background-color: rgba(255, 255, 255, 0.05);
+  }
+
+  body[data-theme="auto"] .sphinx-tabs-tab[aria-selected="true"] {
+    border-bottom: 1px solid rgb(50, 50, 50);
+    background-color: rgb(50, 50, 50);
+  }
+}
+
+/* Explicit dark theme styling */
+
+body[data-theme="dark"] .sphinx-tabs-panel {
+  color: white;
+  background-color: rgb(50, 50, 50);
+}
+
+body[data-theme="dark"] .sphinx-tabs-tab {
+  color: white;
+  background-color: rgba(255, 255, 255, 0.05);
+}
+
+body[data-theme="dark"] .sphinx-tabs-tab[aria-selected="true"] {
+  border-bottom: 2px solid rgb(50, 50, 50);
+  background-color: rgb(50, 50, 50);
+}
diff --git a/_static/tabs.js b/_static/tabs.js
new file mode 100644
index 0000000..48dc303
--- /dev/null
+++ b/_static/tabs.js
@@ -0,0 +1,145 @@
+try {
+  var session = window.sessionStorage || {};
+} catch (e) {
+  var session = {};
+}
+
+window.addEventListener("DOMContentLoaded", () => {
+  const allTabs = document.querySelectorAll('.sphinx-tabs-tab');
+  const tabLists = document.querySelectorAll('[role="tablist"]');
+
+  allTabs.forEach(tab => {
+    tab.addEventListener("click", changeTabs);
+  });
+
+  tabLists.forEach(tabList => {
+    tabList.addEventListener("keydown", keyTabs);
+  });
+
+  // Restore group tab selection from session
+  const lastSelected = session.getItem('sphinx-tabs-last-selected');
+  if (lastSelected != null) selectNamedTabs(lastSelected);
+});
+
+/**
+ * Key focus left and right between sibling elements using arrows
+ * @param  {Node} e the element in focus when key was pressed
+ */
+function keyTabs(e) {
+    const tab = e.target;
+    let nextTab = null;
+    if (e.keyCode === 39 || e.keyCode === 37) {
+      tab.setAttribute("tabindex", -1);
+      // Move right
+      if (e.keyCode === 39) {
+        nextTab = tab.nextElementSibling;
+        if (nextTab === null) {
+          nextTab = tab.parentNode.firstElementChild;
+        }
+      // Move left
+      } else if (e.keyCode === 37) {
+        nextTab = tab.previousElementSibling;
+        if (nextTab === null) {
+          nextTab = tab.parentNode.lastElementChild;
+        }
+      }
+    }
+
+    if (nextTab !== null) {
+      nextTab.setAttribute("tabindex", 0);
+      nextTab.focus();
+    }
+}
+
+/**
+ * Select or deselect clicked tab. If a group tab
+ * is selected, also select tab in other tabLists.
+ * @param  {Node} e the element that was clicked
+ */
+function changeTabs(e) {
+  // Use this instead of the element that was clicked, in case it's a child
+  const notSelected = this.getAttribute("aria-selected") === "false";
+  const positionBefore = this.parentNode.getBoundingClientRect().top;
+  const notClosable = !this.parentNode.classList.contains("closeable");
+
+  deselectTabList(this);
+
+  if (notSelected || notClosable) {
+    selectTab(this);
+    const name = this.getAttribute("name");
+    selectNamedTabs(name, this.id);
+
+    if (this.classList.contains("group-tab")) {
+      // Persist during session
+      session.setItem('sphinx-tabs-last-selected', name);
+    }
+  }
+
+  const positionAfter = this.parentNode.getBoundingClientRect().top;
+  const positionDelta = positionAfter - positionBefore;
+  // Scroll to offset content resizing
+  window.scrollTo(0, window.scrollY + positionDelta);
+}
+
+/**
+ * Select tab and show associated panel.
+ * @param  {Node} tab tab to select
+ */
+function selectTab(tab) {
+  tab.setAttribute("aria-selected", true);
+
+  // Show the associated panel
+  document
+    .getElementById(tab.getAttribute("aria-controls"))
+    .removeAttribute("hidden");
+}
+
+/**
+ * Hide the panels associated with all tabs within the
+ * tablist containing this tab.
+ * @param  {Node} tab a tab within the tablist to deselect
+ */
+function deselectTabList(tab) {
+  const parent = tab.parentNode;
+  const grandparent = parent.parentNode;
+
+  Array.from(parent.children)
+  .forEach(t => t.setAttribute("aria-selected", false));
+
+  Array.from(grandparent.children)
+    .slice(1)  // Skip tablist
+    .forEach(panel => panel.setAttribute("hidden", true));
+}
+
+/**
+ * Select grouped tabs with the same name, but no the tab
+ * with the given id.
+ * @param  {Node} name name of grouped tab to be selected
+ * @param  {Node} clickedId id of clicked tab
+ */
+function selectNamedTabs(name, clickedId=null) {
+  const groupedTabs = document.querySelectorAll(`.sphinx-tabs-tab[name="${name}"]`);
+  const tabLists = Array.from(groupedTabs).map(tab => tab.parentNode);
+
+  tabLists
+    .forEach(tabList => {
+      // Don't want to change the tabList containing the clicked tab
+      const clickedTab = tabList.querySelector(`[id="${clickedId}"]`);
+      if (clickedTab === null ) {
+        // Select first tab with matching name
+        const tab = tabList.querySelector(`.sphinx-tabs-tab[name="${name}"]`);
+        deselectTabList(tab);
+        selectTab(tab);
+      }
+    })
+}
+
+if (typeof exports === 'undefined') {
+  exports = {};
+}
+
+exports.keyTabs = keyTabs;
+exports.changeTabs = changeTabs;
+exports.selectTab = selectTab;
+exports.deselectTabList = deselectTabList;
+exports.selectNamedTabs = selectNamedTabs;
diff --git a/_static/togglebutton.css b/_static/togglebutton.css
new file mode 100644
index 0000000..54a6787
--- /dev/null
+++ b/_static/togglebutton.css
@@ -0,0 +1,160 @@
+/**
+ * Admonition-based toggles
+ */
+
+/* Visibility of the target */
+.admonition.toggle .admonition-title ~ * {
+    transition: opacity .3s, height .3s;
+}
+
+/* Toggle buttons inside admonitions so we see the title */
+.admonition.toggle {
+    position: relative;
+}
+
+/* Titles should cut off earlier to avoid overlapping w/ button */
+.admonition.toggle .admonition-title {
+    padding-right: 25%;
+    cursor: pointer;
+}
+
+/* Hovering will cause a slight shift in color to make it feel interactive */
+.admonition.toggle .admonition-title:hover {
+    box-shadow: inset 0 0 0px 20px rgb(0 0 0 / 1%);
+}
+
+/* Hovering will cause a slight shift in color to make it feel interactive */
+.admonition.toggle .admonition-title:active {
+    box-shadow: inset 0 0 0px 20px rgb(0 0 0 / 3%);
+}
+
+/* Remove extra whitespace below the admonition title when hidden */
+.admonition.toggle-hidden {
+    padding-bottom: 0;
+}
+
+.admonition.toggle-hidden .admonition-title {
+    margin-bottom: 0;
+}
+
+/* hides all the content of a page until de-toggled */
+.admonition.toggle-hidden .admonition-title ~ * {
+    height: 0;
+    margin: 0;
+    opacity: 0;
+    visibility: hidden;
+}
+
+/* General button style and position*/
+button.toggle-button {
+    /**
+     * Background and shape. By default there's no background
+     * but users can style as they wish
+     */  
+    background: none;
+    border: none;
+    outline: none;
+
+    /* Positioning just inside the admonition title */
+    position: absolute;
+    right: 0.5em;
+    padding: 0px;
+    border: none;
+    outline: none;
+}
+
+/* Display the toggle hint on wide screens */
+@media (min-width: 768px) {
+    button.toggle-button.toggle-button-hidden:before {
+        content: attr(data-toggle-hint);  /* This will be filled in by JS */
+        font-size: .8em;
+        align-self: center;
+    }
+}
+
+/* Icon behavior */
+.tb-icon {
+    transition: transform .2s ease-out;
+    height: 1.5em;
+    width: 1.5em;
+    stroke: currentColor;  /* So that we inherit the color of other text */
+}
+
+/* The icon should point right when closed, down when open. */
+/* Open */
+.admonition.toggle button .tb-icon {
+    transform: rotate(90deg);
+}
+
+/* Closed */
+.admonition.toggle button.toggle-button-hidden .tb-icon {
+    transform: rotate(0deg);
+}
+
+/* With details toggles, we don't rotate the icon so it points right */
+details.toggle-details .tb-icon {
+    height: 1.4em;
+    width: 1.4em;
+    margin-top: 0.1em;  /* To center the button vertically */
+}
+
+
+/**
+ * Details-based toggles.
+ * In this case, we wrap elements with `.toggle` in a details block.
+ */
+
+/* Details blocks */
+details.toggle-details {
+    margin: 1em 0;
+}
+
+
+details.toggle-details summary {
+    display: flex;
+    align-items: center;
+    cursor: pointer;
+    list-style: none;
+    border-radius: .2em;
+    border-left: 3px solid #1976d2;
+    background-color: rgb(204 204 204 / 10%);
+    padding: 0.2em 0.7em 0.3em 0.5em; /* Less padding on left because the SVG has left margin */
+    font-size: 0.9em;
+}
+
+details.toggle-details summary:hover {
+    background-color: rgb(204 204 204 / 20%);
+}
+
+details.toggle-details summary:active {
+    background: rgb(204 204 204 / 28%);
+}
+
+.toggle-details__summary-text {
+    margin-left: 0.2em;
+}
+
+details.toggle-details[open] summary {
+    margin-bottom: .5em;
+}
+
+details.toggle-details[open] summary .tb-icon {
+    transform: rotate(90deg);
+}
+
+details.toggle-details[open] summary ~ * {
+    animation: toggle-fade-in .3s ease-out;
+}
+
+@keyframes toggle-fade-in {
+  from {opacity: 0%;}
+  to {opacity: 100%;}
+}
+
+/* Print rules - we hide all toggle button elements at print */
+@media print {
+    /* Always hide the summary so the button doesn't show up */
+    details.toggle-details summary {
+        display: none;
+    }
+}
\ No newline at end of file
diff --git a/_static/togglebutton.js b/_static/togglebutton.js
new file mode 100644
index 0000000..215a7ee
--- /dev/null
+++ b/_static/togglebutton.js
@@ -0,0 +1,187 @@
+/**
+ * Add Toggle Buttons to elements
+ */
+
+let toggleChevron = `
+<svg xmlns="http://www.w3.org/2000/svg" class="tb-icon toggle-chevron-right" width="44" height="44" viewBox="0 0 24 24" stroke-width="1.5" stroke="#000000" fill="none" stroke-linecap="round" stroke-linejoin="round">
+<path stroke="none" d="M0 0h24v24H0z" fill="none"/>
+<polyline points="9 6 15 12 9 18" />
+</svg>`;
+
+var initToggleItems = () => {
+  var itemsToToggle = document.querySelectorAll(togglebuttonSelector);
+  console.log(`[togglebutton]: Adding toggle buttons to ${itemsToToggle.length} items`)
+  // Add the button to each admonition and hook up a callback to toggle visibility
+  itemsToToggle.forEach((item, index) => {
+    if (item.classList.contains("admonition")) {
+      // If it's an admonition block, then we'll add a button inside
+      // Generate unique IDs for this item
+      var toggleID = `toggle-${index}`;
+      var buttonID = `button-${toggleID}`;
+
+      item.setAttribute('id', toggleID);
+      if (!item.classList.contains("toggle")){
+        item.classList.add("toggle");
+      }
+      // This is the button that will be added to each item to trigger the toggle
+      var collapseButton = `
+        <button type="button" id="${buttonID}" class="toggle-button" data-target="${toggleID}" data-button="${buttonID}" data-toggle-hint="${toggleHintShow}" aria-label="Toggle hidden content">
+            ${toggleChevron}
+        </button>`;
+
+      title = item.querySelector(".admonition-title")
+      title.insertAdjacentHTML("beforeend", collapseButton);
+      thisButton = document.getElementById(buttonID);
+
+      // Add click handlers for the button + admonition title (if admonition)
+      admonitionTitle = document.querySelector(`#${toggleID} > .admonition-title`)
+      if (admonitionTitle) {
+        // If an admonition, then make the whole title block clickable
+        admonitionTitle.addEventListener('click', toggleClickHandler);
+        admonitionTitle.dataset.target = toggleID
+        admonitionTitle.dataset.button = buttonID
+      } else {
+        // If not an admonition then we'll listen for the button click
+        thisButton.addEventListener('click', toggleClickHandler);
+      }
+
+      // Now hide the item for this toggle button unless explicitly noted to show
+      if (!item.classList.contains("toggle-shown")) {
+        toggleHidden(thisButton);
+      }
+    } else {
+      // If not an admonition, wrap the block in a <details> block
+      // Define the structure of the details block and insert it as a sibling
+      var detailsBlock = `
+        <details class="toggle-details">
+            <summary class="toggle-details__summary">
+              ${toggleChevron}
+              <span class="toggle-details__summary-text">${toggleHintShow}</span>
+            </summary>
+        </details>`;
+      item.insertAdjacentHTML("beforebegin", detailsBlock);
+
+      // Now move the toggle-able content inside of the details block
+      details = item.previousElementSibling
+      details.appendChild(item)
+      item.classList.add("toggle-details__container")
+
+      // Set up a click trigger to change the text as needed
+      details.addEventListener('click', (click) => {
+        let parent = click.target.parentElement;
+        if (parent.tagName.toLowerCase() == "details") {
+          summary = parent.querySelector("summary");
+          details = parent;
+        } else {
+          summary = parent;
+          details = parent.parentElement;
+        }
+        // Update the inner text for the proper hint
+        if (details.open) {
+          summary.querySelector("span.toggle-details__summary-text").innerText = toggleHintShow;
+        } else {
+          summary.querySelector("span.toggle-details__summary-text").innerText = toggleHintHide;
+        }
+        
+      });
+
+      // If we have a toggle-shown class, open details block should be open
+      if (item.classList.contains("toggle-shown")) {
+        details.click();
+      }
+    }
+  })
+};
+
+// This should simply add / remove the collapsed class and change the button text
+var toggleHidden = (button) => {
+  target = button.dataset['target']
+  var itemToToggle = document.getElementById(target);
+  if (itemToToggle.classList.contains("toggle-hidden")) {
+    itemToToggle.classList.remove("toggle-hidden");
+    button.classList.remove("toggle-button-hidden");
+  } else {
+    itemToToggle.classList.add("toggle-hidden");
+    button.classList.add("toggle-button-hidden");
+  }
+}
+
+var toggleClickHandler = (click) => {
+  // Be cause the admonition title is clickable and extends to the whole admonition
+  // We only look for a click event on this title to trigger the toggle.
+
+  if (click.target.classList.contains("admonition-title")) {
+    button = click.target.querySelector(".toggle-button");
+  } else if (click.target.classList.contains("tb-icon")) {
+    // We've clicked the icon and need to search up one parent for the button
+    button = click.target.parentElement;
+  } else if (click.target.tagName == "polyline") {
+    // We've clicked the SVG elements inside the button, need to up 2 layers
+    button = click.target.parentElement.parentElement;
+  } else if (click.target.classList.contains("toggle-button")) {
+    // We've clicked the button itself and so don't need to do anything
+    button = click.target;
+  } else {
+    console.log(`[togglebutton]: Couldn't find button for ${click.target}`)
+  }
+  target = document.getElementById(button.dataset['button']);
+  toggleHidden(target);
+}
+
+// If we want to blanket-add toggle classes to certain cells
+var addToggleToSelector = () => {
+  const selector = "";
+  if (selector.length > 0) {
+    document.querySelectorAll(selector).forEach((item) => {
+      item.classList.add("toggle");
+    })
+  }
+}
+
+// Helper function to run when the DOM is finished
+const sphinxToggleRunWhenDOMLoaded = cb => {
+  if (document.readyState != 'loading') {
+    cb()
+  } else if (document.addEventListener) {
+    document.addEventListener('DOMContentLoaded', cb)
+  } else {
+    document.attachEvent('onreadystatechange', function() {
+      if (document.readyState == 'complete') cb()
+    })
+  }
+}
+sphinxToggleRunWhenDOMLoaded(addToggleToSelector)
+sphinxToggleRunWhenDOMLoaded(initToggleItems)
+
+/** Toggle details blocks to be open when printing */
+if (toggleOpenOnPrint == "true") {
+  window.addEventListener("beforeprint", () => {
+    // Open the details
+    document.querySelectorAll("details.toggle-details").forEach((el) => {
+      el.dataset["togglestatus"] = el.open;
+      el.open = true;
+    });
+  
+    // Open the admonitions
+    document.querySelectorAll(".admonition.toggle.toggle-hidden").forEach((el) => {
+      console.log(el);
+      el.querySelector("button.toggle-button").click();
+      el.dataset["toggle_after_print"] = "true";
+    });
+  });
+  window.addEventListener("afterprint", () => {
+    // Re-close the details that were closed
+    document.querySelectorAll("details.toggle-details").forEach((el) => {
+      el.open = el.dataset["togglestatus"] == "true";
+      delete el.dataset["togglestatus"];
+    });
+  
+    // Re-close the admonition toggle buttons
+    document.querySelectorAll(".admonition.toggle").forEach((el) => {
+      if (el.dataset["toggle_after_print"] == "true") {
+        el.querySelector("button.toggle-button").click();
+        delete el.dataset["toggle_after_print"];
+      }
+    });
+  });
+}
diff --git a/_static/twemoji.css b/_static/twemoji.css
new file mode 100644
index 0000000..878d070
--- /dev/null
+++ b/_static/twemoji.css
@@ -0,0 +1,6 @@
+img.emoji {
+    height: 1em;
+    width: 1em;
+    margin: 0 .05em 0 .1em;
+    vertical-align: -0.1em;
+}
diff --git a/_static/twemoji.js b/_static/twemoji.js
new file mode 100644
index 0000000..91bc868
--- /dev/null
+++ b/_static/twemoji.js
@@ -0,0 +1,10 @@
+function addEvent(element, eventName, fn) {
+    if (element.addEventListener)
+        element.addEventListener(eventName, fn, false);
+    else if (element.attachEvent)
+        element.attachEvent('on' + eventName, fn);
+}
+
+addEvent(window, 'load', function() {
+    twemoji.parse(document.body, {'folder': 'svg', 'ext': '.svg'});
+});
diff --git a/_static/vendor/fontawesome/6.5.1/LICENSE.txt b/_static/vendor/fontawesome/6.5.1/LICENSE.txt
new file mode 100644
index 0000000..39e18e3
--- /dev/null
+++ b/_static/vendor/fontawesome/6.5.1/LICENSE.txt
@@ -0,0 +1,165 @@
+Fonticons, Inc. (https://fontawesome.com)
+
+--------------------------------------------------------------------------------
+
+Font Awesome Free License
+
+Font Awesome Free is free, open source, and GPL friendly. You can use it for
+commercial projects, open source projects, or really almost whatever you want.
+Full Font Awesome Free license: https://fontawesome.com/license/free.
+
+--------------------------------------------------------------------------------
+
+# Icons: CC BY 4.0 License (https://creativecommons.org/licenses/by/4.0/)
+
+The Font Awesome Free download is licensed under a Creative Commons
+Attribution 4.0 International License and applies to all icons packaged
+as SVG and JS file types.
+
+--------------------------------------------------------------------------------
+
+# Fonts: SIL OFL 1.1 License
+
+In the Font Awesome Free download, the SIL OFL license applies to all icons
+packaged as web and desktop font files.
+
+Copyright (c) 2023 Fonticons, Inc. (https://fontawesome.com)
+with Reserved Font Name: "Font Awesome".
+
+This Font Software is licensed under the SIL Open Font License, Version 1.1.
+This license is copied below, and is also available with a FAQ at:
+http://scripts.sil.org/OFL
+
+SIL OPEN FONT LICENSE
+Version 1.1 - 26 February 2007
+
+PREAMBLE
+The goals of the Open Font License (OFL) are to stimulate worldwide
+development of collaborative font projects, to support the font creation
+efforts of academic and linguistic communities, and to provide a free and
+open framework in which fonts may be shared and improved in partnership
+with others.
+
+The OFL allows the licensed fonts to be used, studied, modified and
+redistributed freely as long as they are not sold by themselves. The
+fonts, including any derivative works, can be bundled, embedded,
+redistributed and/or sold with any software provided that any reserved
+names are not used by derivative works. The fonts and derivatives,
+however, cannot be released under any other type of license. The
+requirement for fonts to remain under this license does not apply
+to any document created using the fonts or their derivatives.
+
+DEFINITIONS
+"Font Software" refers to the set of files released by the Copyright
+Holder(s) under this license and clearly marked as such. This may
+include source files, build scripts and documentation.
+
+"Reserved Font Name" refers to any names specified as such after the
+copyright statement(s).
+
+"Original Version" refers to the collection of Font Software components as
+distributed by the Copyright Holder(s).
+
+"Modified Version" refers to any derivative made by adding to, deleting,
+or substituting — in part or in whole — any of the components of the
+Original Version, by changing formats or by porting the Font Software to a
+new environment.
+
+"Author" refers to any designer, engineer, programmer, technical
+writer or other person who contributed to the Font Software.
+
+PERMISSION & CONDITIONS
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of the Font Software, to use, study, copy, merge, embed, modify,
+redistribute, and sell modified and unmodified copies of the Font
+Software, subject to the following conditions:
+
+1) Neither the Font Software nor any of its individual components,
+in Original or Modified Versions, may be sold by itself.
+
+2) Original or Modified Versions of the Font Software may be bundled,
+redistributed and/or sold with any software, provided that each copy
+contains the above copyright notice and this license. These can be
+included either as stand-alone text files, human-readable headers or
+in the appropriate machine-readable metadata fields within text or
+binary files as long as those fields can be easily viewed by the user.
+
+3) No Modified Version of the Font Software may use the Reserved Font
+Name(s) unless explicit written permission is granted by the corresponding
+Copyright Holder. This restriction only applies to the primary font name as
+presented to the users.
+
+4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font
+Software shall not be used to promote, endorse or advertise any
+Modified Version, except to acknowledge the contribution(s) of the
+Copyright Holder(s) and the Author(s) or with their explicit written
+permission.
+
+5) The Font Software, modified or unmodified, in part or in whole,
+must be distributed entirely under this license, and must not be
+distributed under any other license. The requirement for fonts to
+remain under this license does not apply to any document created
+using the Font Software.
+
+TERMINATION
+This license becomes null and void if any of the above conditions are
+not met.
+
+DISCLAIMER
+THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
+OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE
+COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL
+DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM
+OTHER DEALINGS IN THE FONT SOFTWARE.
+
+--------------------------------------------------------------------------------
+
+# Code: MIT License (https://opensource.org/licenses/MIT)
+
+In the Font Awesome Free download, the MIT license applies to all non-font and
+non-icon files.
+
+Copyright 2023 Fonticons, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in the
+Software without restriction, including without limitation the rights to use, copy,
+modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
+and to permit persons to whom the Software is furnished to do so, subject to the
+following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
+INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
+PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+--------------------------------------------------------------------------------
+
+# Attribution
+
+Attribution is required by MIT, SIL OFL, and CC BY licenses. Downloaded Font
+Awesome Free files already contain embedded comments with sufficient
+attribution, so you shouldn't need to do anything additional when using these
+files normally.
+
+We've kept attribution comments terse, so we ask that you do not actively work
+to remove them from files, especially code. They're a great way for folks to
+learn about Font Awesome.
+
+--------------------------------------------------------------------------------
+
+# Brand Icons
+
+All brand icons are trademarks of their respective owners. The use of these
+trademarks does not indicate endorsement of the trademark holder by Font
+Awesome, nor vice versa. **Please do not use brand logos for any purpose except
+to represent the company, product, or service to which they refer.**
diff --git a/_static/vendor/fontawesome/6.5.1/css/all.min.css b/_static/vendor/fontawesome/6.5.1/css/all.min.css
new file mode 100644
index 0000000..5f2038f
--- /dev/null
+++ b/_static/vendor/fontawesome/6.5.1/css/all.min.css
@@ -0,0 +1,5 @@
+/*!
+ * Font Awesome Free 6.5.1 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */.fa{font-family:var(--fa-style-family,"Font Awesome 6 Free");font-weight:var(--fa-style,900)}.fa,.fa-brands,.fa-classic,.fa-regular,.fa-sharp,.fa-solid,.fab,.far,.fas{-moz-osx-font-smoothing:grayscale;-webkit-font-smoothing:antialiased;display:var(--fa-display,inline-block);font-style:normal;font-variant:normal;line-height:1;text-rendering:auto}.fa-classic,.fa-regular,.fa-solid,.far,.fas{font-family:Font Awesome\ 6 Free}.fa-brands,.fab{font-family:Font Awesome\ 6 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var(--fa-border-color,#eee);border-radius:var(--fa-border-radius,.1em);padding:var(--fa-border-padding,.2em .25em 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diff --git a/_static/vendor/fontawesome/6.5.1/js/all.min.js.LICENSE.txt b/_static/vendor/fontawesome/6.5.1/js/all.min.js.LICENSE.txt
new file mode 100644
index 0000000..ef6dda4
--- /dev/null
+++ b/_static/vendor/fontawesome/6.5.1/js/all.min.js.LICENSE.txt
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+/*!
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+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
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new file mode 100644
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diff --git a/_static/vendor/fontawesome/6.5.1/webfonts/fa-v4compatibility.ttf b/_static/vendor/fontawesome/6.5.1/webfonts/fa-v4compatibility.ttf
new file mode 100644
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diff --git a/_static/webpack-macros.html b/_static/webpack-macros.html
new file mode 100644
index 0000000..243a858
--- /dev/null
+++ b/_static/webpack-macros.html
@@ -0,0 +1,31 @@
+<!--
+  AUTO-GENERATED from webpack.config.js, do **NOT** edit by hand.
+  These are re-used in layout.html
+-->
+{# Load FontAwesome icons #}
+{% macro head_pre_icons() %}
+  <link href="{{ pathto('_static/vendor/fontawesome/6.5.1/css/all.min.css', 1) }}?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+  <link rel="preload" as="font" type="font/woff2" crossorigin href="{{ pathto('_static/vendor/fontawesome/6.5.1/webfonts/fa-solid-900.woff2', 1) }}" />
+<link rel="preload" as="font" type="font/woff2" crossorigin href="{{ pathto('_static/vendor/fontawesome/6.5.1/webfonts/fa-brands-400.woff2', 1) }}" />
+<link rel="preload" as="font" type="font/woff2" crossorigin href="{{ pathto('_static/vendor/fontawesome/6.5.1/webfonts/fa-regular-400.woff2', 1) }}" />
+{% endmacro %}
+
+{% macro head_pre_assets() %}
+  <!-- Loaded before other Sphinx assets -->
+  <link href="{{ pathto('_static/styles/theme.css', 1) }}?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+<link href="{{ pathto('_static/styles/bootstrap.css', 1) }}?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+<link href="{{ pathto('_static/styles/pydata-sphinx-theme.css', 1) }}?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+{% endmacro %}
+
+{% macro head_js_preload() %}
+  <!-- Pre-loaded scripts that we'll load fully later -->
+  <link rel="preload" as="script" href="{{ pathto('_static/scripts/bootstrap.js', 1) }}?digest=8d27b9dea8ad943066ae" />
+<link rel="preload" as="script" href="{{ pathto('_static/scripts/pydata-sphinx-theme.js', 1) }}?digest=8d27b9dea8ad943066ae" />
+  <script src="{{ pathto('_static/vendor/fontawesome/6.5.1/js/all.min.js', 1) }}?digest=8d27b9dea8ad943066ae"></script>
+{% endmacro %}
+
+{% macro body_post() %}
+  <!-- Scripts loaded after <body> so the DOM is not blocked -->
+  <script src="{{ pathto('_static/scripts/bootstrap.js', 1) }}?digest=8d27b9dea8ad943066ae"></script>
+<script src="{{ pathto('_static/scripts/pydata-sphinx-theme.js', 1) }}?digest=8d27b9dea8ad943066ae"></script>
+{% endmacro %}
\ No newline at end of file
diff --git a/basics/index.html b/basics/index.html
new file mode 100644
index 0000000..93c0d71
--- /dev/null
+++ b/basics/index.html
@@ -0,0 +1,539 @@
+
+<!DOCTYPE html>
+
+
+<html lang="en" data-content_root="../" >
+
+  <head>
+    <meta charset="utf-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="viewport" content="width=device-width, initial-scale=1" />
+
+    <title>Jupyterhub basic usage &#8212; eScience-2024  documentation</title>
+  
+  
+  
+  <script data-cfasync="false">
+    document.documentElement.dataset.mode = localStorage.getItem("mode") || "";
+    document.documentElement.dataset.theme = localStorage.getItem("theme") || "light";
+  </script>
+  
+  <!-- Loaded before other Sphinx assets -->
+  <link href="../_static/styles/theme.css?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+<link href="../_static/styles/bootstrap.css?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+<link href="../_static/styles/pydata-sphinx-theme.css?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+
+  
+  <link href="../_static/vendor/fontawesome/6.5.1/css/all.min.css?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+  <link rel="preload" as="font" type="font/woff2" crossorigin href="../_static/vendor/fontawesome/6.5.1/webfonts/fa-solid-900.woff2" />
+<link rel="preload" as="font" type="font/woff2" crossorigin href="../_static/vendor/fontawesome/6.5.1/webfonts/fa-brands-400.woff2" />
+<link rel="preload" as="font" type="font/woff2" crossorigin href="../_static/vendor/fontawesome/6.5.1/webfonts/fa-regular-400.woff2" />
+
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=a746c00c" />
+    <link rel="stylesheet" type="text/css" href="../_static/styles/sphinx-book-theme.css?v=384b581d" />
+    <link rel="stylesheet" type="text/css" href="../_static/graphviz.css?v=fd3f3429" />
+    <link rel="stylesheet" type="text/css" href="../_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css" />
+    <link rel="stylesheet" type="text/css" href="../_static/copybutton.css?v=76b2166b" />
+    <link rel="stylesheet" type="text/css" href="../_static/togglebutton.css?v=13237357" />
+    <link rel="stylesheet" type="text/css" href="../_static/css/sphinx-toolbox.css" />
+    <link rel="stylesheet" type="text/css" href="../_static/tabs.css?v=a5c4661c" />
+    <link rel="stylesheet" type="text/css" href="../_static/sphinx_toolbox_installation.css" />
+    <link rel="stylesheet" type="text/css" href="../_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css?v=0a3b3ea7" />
+  
+  <!-- Pre-loaded scripts that we'll load fully later -->
+  <link rel="preload" as="script" href="../_static/scripts/bootstrap.js?digest=8d27b9dea8ad943066ae" />
+<link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=8d27b9dea8ad943066ae" />
+  <script src="../_static/vendor/fontawesome/6.5.1/js/all.min.js?digest=8d27b9dea8ad943066ae"></script>
+
+    <script src="../_static/documentation_options.js?v=55b5f74b"></script>
+    <script src="../_static/doctools.js?v=9a2dae69"></script>
+    <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
+    <script src="../_static/clipboard.min.js?v=a7894cd8"></script>
+    <script src="../_static/copybutton.js?v=f281be69"></script>
+    <script src="../_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
+    <script>let toggleHintShow = 'Click to show';</script>
+    <script>let toggleHintHide = 'Click to hide';</script>
+    <script>let toggleOpenOnPrint = 'true';</script>
+    <script src="../_static/togglebutton.js?v=4a39c7ea"></script>
+    <script src="../_static/sphinx_toolbox_installation.js"></script>
+    <script src="../_static/design-tabs.js?v=36754332"></script>
+    <script>var togglebuttonSelector = '.toggle, .admonition.dropdown';</script>
+    <script>var togglebuttonSelector = '.toggle, .admonition.dropdown';</script>
+    <script>DOCUMENTATION_OPTIONS.pagename = 'basics/index';</script>
+    <link rel="icon" href="../_static/es-logo.ico"/>
+    <link rel="index" title="Index" href="../genindex/" />
+    <link rel="search" title="Search" href="../search/" />
+    <link rel="next" title="Starting and stopping your server" href="start_stop/" />
+    <link rel="prev" title="Sharing data" href="../course_workflow/data/" />
+  <meta name="viewport" content="width=device-width, initial-scale=1"/>
+  <meta name="docsearch:language" content="en"/>
+  </head>
+  
+  
+  <body data-bs-spy="scroll" data-bs-target=".bd-toc-nav" data-offset="180" data-bs-root-margin="0px 0px -60%" data-default-mode="">
+
+  
+  
+  <a id="pst-skip-link" class="skip-link" href="#main-content">Skip to main content</a>
+  
+  <div id="pst-scroll-pixel-helper"></div>
+  
+  <button type="button" class="btn rounded-pill" id="pst-back-to-top">
+    <i class="fa-solid fa-arrow-up"></i>
+    Back to top
+  </button>
+
+  
+  <input type="checkbox"
+          class="sidebar-toggle"
+          name="__primary"
+          id="__primary"/>
+  <label class="overlay overlay-primary" for="__primary"></label>
+  
+  <input type="checkbox"
+          class="sidebar-toggle"
+          name="__secondary"
+          id="__secondary"/>
+  <label class="overlay overlay-secondary" for="__secondary"></label>
+  
+  <div class="search-button__wrapper">
+    <div class="search-button__overlay"></div>
+    <div class="search-button__search-container">
+<form class="bd-search d-flex align-items-center"
+      action="../search/"
+      method="get">
+  <i class="fa-solid fa-magnifying-glass"></i>
+  <input type="search"
+         class="form-control"
+         name="q"
+         id="search-input"
+         placeholder="Search..."
+         aria-label="Search..."
+         autocomplete="off"
+         autocorrect="off"
+         autocapitalize="off"
+         spellcheck="false"/>
+  <span class="search-button__kbd-shortcut"><kbd class="kbd-shortcut__modifier">Ctrl</kbd>+<kbd>K</kbd></span>
+</form></div>
+  </div>
+  
+    <header class="bd-header navbar navbar-expand-lg bd-navbar">
+    </header>
+  
+
+  <div class="bd-container">
+    <div class="bd-container__inner bd-page-width">
+      
+      
+      
+      <div class="bd-sidebar-primary bd-sidebar">
+        
+
+  
+  <div class="sidebar-header-items sidebar-primary__section">
+    
+    
+    
+    
+  </div>
+  
+    <div class="sidebar-primary-items__start sidebar-primary__section">
+        <div class="sidebar-primary-item">
+
+  
+
+<a class="navbar-brand logo" href="../">
+  
+  
+  
+  
+  
+    
+    
+      
+    
+    
+    <img src="../_static/es-logo.png" class="logo__image only-light" alt="eScience-2024  documentation - Home"/>
+    <script>document.write(`<img src="../_static/es-logo.png" class="logo__image only-dark" alt="eScience-2024  documentation - Home"/>`);</script>
+  
+  
+</a></div>
+        <div class="sidebar-primary-item">
+
+ <script>
+ document.write(`
+   <button class="btn navbar-btn search-button-field search-button__button" title="Search" aria-label="Search" data-bs-placement="bottom" data-bs-toggle="tooltip">
+    <i class="fa-solid fa-magnifying-glass"></i>
+    <span class="search-button__default-text">Search</span>
+    <span class="search-button__kbd-shortcut"><kbd class="kbd-shortcut__modifier">Ctrl</kbd>+<kbd class="kbd-shortcut__modifier">K</kbd></span>
+   </button>
+ `);
+ </script></div>
+        <div class="sidebar-primary-item"><nav class="bd-links bd-docs-nav" aria-label="Main">
+    <div class="bd-toc-item navbar-nav active">
+        
+        <ul class="nav bd-sidenav bd-sidenav__home-link">
+            <li class="toctree-l1">
+                <a class="reference internal" href="../">
+                    eScience 2024 course
+                </a>
+            </li>
+        </ul>
+        <ul class="current nav bd-sidenav">
+<li class="toctree-l1"><a class="reference internal" href="../feide/">Jupyterhub access</a></li>
+<li class="toctree-l1 has-children"><a class="reference internal" href="../course_workflow/">Workflow for eScience2024 course</a><input checked class="toctree-checkbox" id="toctree-checkbox-1" name="toctree-checkbox-1" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-1"><i class="fa-solid fa-chevron-down"></i></label><ul>
+<li class="toctree-l2"><a class="reference internal" href="../course_workflow/workflow/">Basic setup</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../course_workflow/rules/">Basic Rules for the course</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../course_workflow/data/">Sharing data</a></li>
+</ul>
+</li>
+<li class="toctree-l1 current active has-children"><a class="current reference internal" href="#">Jupyterhub basic usage</a><input checked class="toctree-checkbox" id="toctree-checkbox-2" name="toctree-checkbox-2" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-2"><i class="fa-solid fa-chevron-down"></i></label><ul>
+<li class="toctree-l2"><a class="reference internal" href="start_stop/">Starting and stopping your server</a></li>
+<li class="toctree-l2"><a class="reference internal" href="lab/">The JupyterLab Interface</a></li>
+<li class="toctree-l2"><a class="reference internal" href="kernels/">Using different kernels in notebooks</a></li>
+</ul>
+</li>
+<li class="toctree-l1 has-children"><a class="reference internal" href="../data/">Data</a><input checked class="toctree-checkbox" id="toctree-checkbox-3" name="toctree-checkbox-3" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-3"><i class="fa-solid fa-chevron-down"></i></label><ul>
+<li class="toctree-l2"><a class="reference internal" href="../data/Intake-data-acess/">Acessing model data using intake-esm</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../data/local-data/">Local shared data</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../data/ACTRIS-data/">ACTRIS data</a></li>
+</ul>
+</li>
+<li class="toctree-l1 has-children"><a class="reference internal" href="../learning/">Learning Corner</a><input checked class="toctree-checkbox" id="toctree-checkbox-4" name="toctree-checkbox-4" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-4"><i class="fa-solid fa-chevron-down"></i></label><ul>
+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/cool_stuff/">Building notebooks directly</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/from_ebas_using_xarray/">Using xarray to read EBAS data</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/masked_and_weighted_average/">Using masks and computing weighted average</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/projections/">Using cartopy and projections for plotting</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/some-xarray-pandas-presentation_Sara/">Some tips with xarray and pandas</a></li>
+
+
+
+
+
+
+
+<li class="toctree-l2"><a class="reference internal" href="../learning/us-links/">Useful links</a></li>
+
+</ul>
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+    <h1>Using different kernels in notebooks</h1>
+    <!-- Table of contents -->
+    <div id="print-main-content">
+        <div id="jb-print-toc">
+            
+            <div>
+                <h2> Contents </h2>
+            </div>
+            <nav aria-label="Page">
+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#available-kernels">Available kernels</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#using-the-conda-environments-outside-of-the-course">Using the conda environments outside of the course</a></li>
+</ul>
+            </nav>
+        </div>
+    </div>
+</div>
+
+              
+                
+<div id="searchbox"></div>
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+                  
+  <section id="using-different-kernels-in-notebooks">
+<h1>Using different kernels in notebooks<a class="headerlink" href="#using-different-kernels-in-notebooks" title="Link to this heading">#</a></h1>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>We are using <code class="docutils literal notranslate"><span class="pre">mamba</span></code> here which is a drop in replacement for <code class="docutils literal notranslate"><span class="pre">conda</span></code> that is generally faster. All commands that work with <code class="docutils literal notranslate"><span class="pre">mamba</span></code> should also work with <code class="docutils literal notranslate"><span class="pre">conda</span></code>.</p>
+</div>
+<p>We provide different conda environments as kernels for processing jupyternotebooks.
+You can see them in the launcher when you create a new notebook or choose one in the drop-dowmn menu in the top right corner.
+If you want to check which packages are included in the environment you can find the names of the environments available by doing: <code class="docutils literal notranslate"><span class="pre">mamba</span> <span class="pre">env</span> <span class="pre">list</span></code>.
+To list packages and their versions within the environment use the following command: <code class="docutils literal notranslate"><span class="pre">mamba</span> <span class="pre">env</span> <span class="pre">export</span> <span class="pre">-n</span> <span class="pre">environment_name</span> <span class="pre">--no-builds</span></code>.</p>
+<section id="available-kernels">
+<h2>Available kernels<a class="headerlink" href="#available-kernels" title="Link to this heading">#</a></h2>
+<ul>
+<li><p><strong>minimal</strong>: bare python3.11 environment</p></li>
+<li><p><strong>base</strong>: contains basic packages (mostly not useful for data processing)</p></li>
+<li><p><strong>pangeo-notebook</strong>: environment, built from <a class="reference external" href="https://github.com/pangeo-data/pangeo-docker-images/tree/2024.04.05/pangeo-notebook">Pangeo nootbook v2024.04.05</a> extended with <code class="docutils literal notranslate"><span class="pre">rioxarray</span></code>, <code class="docutils literal notranslate"><span class="pre">pyrcel</span></code> and <code class="docutils literal notranslate"><span class="pre">geocat</span></code> packages.</p></li>
+<li><p><strong>ml-notebook</strong>: environment, built from <a class="reference external" href="https://github.com/pangeo-data/pangeo-docker-images/tree/2024.04.05/ml-notebook">Pangeo ml-nootbook v2024.04.05</a> with added packages:</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="s1">&#39;gpflow&#39;</span>
+<span class="s1">&#39;scikit-learn&#39;</span>
+<span class="s1">&#39;tf-keras&#39;</span>
+<span class="s1">&#39;tensorflow-probability&#39;</span>
+<span class="s1">&#39;tensorflow&#39;</span>
+<span class="s1">&#39;iris&#39;</span>
+<span class="s1">&#39;tqdm&#39;</span>
+<span class="s1">&#39;cis&#39;</span>
+<span class="s1">&#39;ESEM&#39;</span>
+<span class="s1">&#39;pyaro&#39;</span>
+</pre></div>
+</div>
+</li>
+<li><p><strong>pyaero-notebook</strong>: This <a class="reference external" href="https://raw.githubusercontent.com/metno/pyaerocom/v0.17.1/pyaerocom_env.yml">environment</a>  includes various packages for <code class="docutils literal notranslate"><span class="pre">pyaerocom</span></code>.</p>
+<div class="admonition warning">
+<p class="admonition-title">Warning</p>
+<p>This is environment contains older versions of packages to allow the latest  <code class="docutils literal notranslate"><span class="pre">pyaerocom</span></code> to work. If you don’t require any specific packages from this environment,
+you should use the <code class="docutils literal notranslate"><span class="pre">pangeo-notebook</span></code> or <code class="docutils literal notranslate"><span class="pre">ml-notebook</span></code> kernel instead.</p>
+</div>
+</li>
+</ul>
+</section>
+<section id="using-the-conda-environments-outside-of-the-course">
+<h2>Using the conda environments outside of the course<a class="headerlink" href="#using-the-conda-environments-outside-of-the-course" title="Link to this heading">#</a></h2>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>Too learn more about what conda does and how to make your data analysis reproduce able, check out the code-refinery lesson on <a class="reference external" href="https://carpentries-incubator.github.io/introduction-to-conda-for-data-scientists/01-getting-started-with-conda/index.html">conda-for-data-scientists</a>.</p>
+</div>
+<p>You can also pipe it to a file to view later or to create same environment somewhere else: <code class="docutils literal notranslate"><span class="pre">mamba</span> <span class="pre">env</span> <span class="pre">export</span> <span class="pre">-n</span> <span class="pre">&lt;environment</span> <span class="pre">name&gt;</span> <span class="pre">&gt;</span> <span class="pre">environment.yml</span></code>. To leave out the build information use add <code class="docutils literal notranslate"><span class="pre">--no-builds</span></code>.
+To create an environment out of this file: <code class="docutils literal notranslate"><span class="pre">mamba</span> <span class="pre">-n</span> <span class="pre">environment_name</span> <span class="pre">-f</span> <span class="pre">environment.yml</span></code>.</p>
+<div class="toggle admonition attention" id="platform-specific-environments">
+<p class="admonition-title">Attention</p>
+<p>The exported environment may be platform specific, f.e. you will see <code class="docutils literal notranslate"><span class="pre">platform:</span> <span class="pre">linux-64</span></code>.
+Recreating the environment on another platform might not work since some of the packages might not be available for your target platform.
+In that case, it’s recommended to use containers to reproduce the environment. However it is possible to export platform independent environments by using the <code class="docutils literal notranslate"><span class="pre">--no-builds</span></code>.
+Furthermore, conda-lock can be used to create a lock file that solves the dependencies for different platforms and can then be used to recreate the environment on another platform.</p>
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+                  
+  <section id="the-jupyterlab-interface">
+<h1>The JupyterLab Interface<a class="headerlink" href="#the-jupyterlab-interface" title="Link to this heading">#</a></h1>
+<p>By default, you will get the web-based user interface for Project Jupyter that is called <a class="reference external" href="https://jupyterlab.readthedocs.io/en/stable/">JupyterLab</a>.</p>
+<section id="menu-bar">
+<h2>Menu Bar<a class="headerlink" href="#menu-bar" title="Link to this heading">#</a></h2>
+<p>The menu bar at the top of JupyterLab has top-level menus that expose actions available in JupyterLab with
+their keyboard shortcuts. The default menus are:</p>
+<ul class="simple">
+<li><p><strong>File</strong>: actions related to files and directories</p></li>
+<li><p><strong>Edit</strong>: actions related to editing documents and other activities</p></li>
+<li><p><strong>View</strong>: actions that alter the appearance of JupyterLab</p></li>
+<li><p><strong>Run</strong>: actions for running code in different activities such as notebooks and code consoles</p></li>
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+<li><p><strong>Settings</strong>: common settings and an advanced settings editor</p></li>
+<li><p><strong>Help</strong>: a list of JupyterLab and kernel help links</p></li>
+</ul>
+</section>
+<section id="left-sidebar">
+<h2>Left Sidebar<a class="headerlink" href="#left-sidebar" title="Link to this heading">#</a></h2>
+<p>The left sidebar contains a number of commonly-used tabs, such as a file browser, a list of running
+kernels and terminals, the command palette, and a list of tabs in the main work area:</p>
+<p>If you move your mouse on the other icon of this left sidebar, a short information is given on its functionality.</p>
+<p>If you click on the “stop button” icon, you can see what is currently running on your server and you can click on
+“SHUT DOWN” to stop a running Python notebook or Terminal.</p>
+<p>### Start a new Terminal</p>
+<p>Similarly, you can start a new Terminal by clicking on “Terminal” in the Launcher.</p>
+</section>
+<section id="tips">
+<h2>Tips<a class="headerlink" href="#tips" title="Link to this heading">#</a></h2>
+<blockquote>
+<div><p>If the <strong>Launcher</strong> tab does not exist
+anymore in your JupyterLab, you can start a new one in “<strong>File</strong> –&gt; <strong>New Launcher</strong>”.</p>
+</div></blockquote>
+</section>
+<section id="create-a-new-python-3-notebook">
+<h2>Create a new python 3 notebook<a class="headerlink" href="#create-a-new-python-3-notebook" title="Link to this heading">#</a></h2>
+<p>Go back to the <strong>File Browser</strong> left sidebar tab and in the launcher select <strong>Python 3</strong> under the Notebook
+section:</p>
+<p>By default, your new notebook is named as “<strong>Untitled.ipynb</strong>”:</p>
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+<li><p><strong>ipynb</strong> is the extension for any Jupyter notebook and you should make sure all your notebooks get this extension (otherwise it is not recognized as a Jupyter notebook)</p></li>
+<li><p>you can rename your jupyter notebook with the tab “File –&gt; Rename Notebook…” or
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+    <h1>Contribute to this page</h1>
+    <!-- Table of contents -->
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+            
+            <div>
+                <h2> Contents </h2>
+            </div>
+            <nav aria-label="Page">
+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#the-recommended-workflow-for-development">The recommended workflow for development</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#locally-build-this-page">Locally build this page</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#after-you-are-done-with-your-changes">After you are done with your changes:</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#reviewing-prs">Reviewing PRs</a></li>
+</ul>
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+</div>
+
+              
+                
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+                  
+  <section id="contribute-to-this-page">
+<h1>Contribute to this page<a class="headerlink" href="#contribute-to-this-page" title="Link to this heading">#</a></h1>
+<section id="the-recommended-workflow-for-development">
+<h2>The recommended workflow for development<a class="headerlink" href="#the-recommended-workflow-for-development" title="Link to this heading">#</a></h2>
+<ol class="arabic simple">
+<li><p>Fork the repository to your Github account and fetch upstream to receive the newest commits.</p></li>
+<li><p>Alternatively, you should just clone this repo if you are part of the <strong>eScience2024</strong> team, this way the branches you create will get</p></li>
+<li><p>Perform the development in a newly-created branch (other than <code class="docutils literal notranslate"><span class="pre">master</span></code>) in your repository.</p></li>
+<li><p>Note that since we are using <code class="docutils literal notranslate"><span class="pre">myst-parser</span></code> both <code class="docutils literal notranslate"><span class="pre">.rst</span></code> and <code class="docutils literal notranslate"><span class="pre">.md</span></code> can be used.</p></li>
+<li><p>Build the page in the command line to test the introduced modifications by following the instructions below.</p></li>
+</ol>
+<section id="locally-build-this-page">
+<h3>Locally build this page<a class="headerlink" href="#locally-build-this-page" title="Link to this heading">#</a></h3>
+<p>Before filling a pull-request you should check that the changes introduced by you still make the site build. Therefore, you should always <a class="reference external" href="https://coderefinery.github.io/sphinx-lesson/contributing-to-a-lesson/#build-and-test-locally">build and test locally</a> before you ask for a pull request.</p>
+<p>To automatically update the documentation locally during development:</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$[~/PROJECT_ROOT] sphinx-autobuild docs/ _build
+</pre></div>
+</div>
+<p>Using venv or conda is highly recommended. Also, when you are pulling from <code class="docutils literal notranslate"><span class="pre">master</span></code>, please don’t forget to update your environment with <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">-r</span> <span class="pre">requirements.txt</span></code> since those might have been changed since you last built the page locally.</p>
+</section>
+</section>
+<section id="after-you-are-done-with-your-changes">
+<h2>After you are done with your changes:<a class="headerlink" href="#after-you-are-done-with-your-changes" title="Link to this heading">#</a></h2>
+<ol class="arabic simple">
+<li><p>Merge or rebase on <code class="docutils literal notranslate"><span class="pre">upstream/master</span></code> (<code class="docutils literal notranslate"><span class="pre">master</span></code> if  you work within this repo) and resolve conflicts.</p></li>
+<li><p>Check with <code class="docutils literal notranslate"><span class="pre">sphinx-autobuild</span></code> to see if the page builds and looks as intended.</p></li>
+<li><p>Create a pull request to the <code class="docutils literal notranslate"><span class="pre">master</span></code> branch. Give a short description of what you have added.</p></li>
+</ol>
+<p>The static webpage is hosted on Github and automatically built by pushing changes to the <code class="docutils literal notranslate"><span class="pre">master</span></code> branch. The built webpage is displayed when selecting the <code class="docutils literal notranslate"><span class="pre">gh-pages</span></code> branch. This process is automatic. A guide to the principles can be found <a class="reference external" href="https://pythonrepo.com/repo/executablebooks-sphinx-autobuild-python-documentation">here</a>.</p>
+<p>If you have any questions, look in the Issues (including closed), if you don’t find an answer - create a new one.</p>
+<blockquote>
+<div><p><strong>NOTE</strong> If workflow above is too hard for you, there is a Github button in the top-right corner.</p>
+</div></blockquote>
+</section>
+<section id="reviewing-prs">
+<h2>Reviewing PRs<a class="headerlink" href="#reviewing-prs" title="Link to this heading">#</a></h2>
+<ol class="arabic simple">
+<li><p>Checkout branch that is getting pulled.</p></li>
+<li><p>Build locally.</p></li>
+<li><p>Add commits locally to fix things.</p></li>
+<li><p>Add comments  in the pull request.</p></li>
+<li><p>Merge the PR (if you have rights and are happy with the changes).</p></li>
+</ol>
+<p>The web-page will get updated in a few minutes through github actions.</p>
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+</section>
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+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#locally-build-this-page">Locally build this page</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#after-you-are-done-with-your-changes">After you are done with your changes:</a></li>
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diff --git a/course_workflow/data/index.html b/course_workflow/data/index.html
new file mode 100644
index 0000000..ac2482e
--- /dev/null
+++ b/course_workflow/data/index.html
@@ -0,0 +1,536 @@
+
+<!DOCTYPE html>
+
+
+<html lang="en" data-content_root="../../" >
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+<h1>Sharing data<a class="headerlink" href="#sharing-data" title="Link to this heading">#</a></h1>
+<p>Small size data (&lt;10 Mb) can be shared directly through the <a class="reference external" href="https://github.com/MetOs-UiO/eScience2024-projects">eScience2024-projects repo</a>.</p>
+<p>Larger data will be put into read-only <code class="docutils literal notranslate"><span class="pre">~/shared-craas1-nn9989k-geo4992/data/</span></code> by request (ask &#64;mvdebolsiy to copy it there).</p>
+<p>If you want to share something real quick with members of your group: you can access other user’s home directories at <code class="docutils literal notranslate"><span class="pre">~/shared-craas1-ns9989k-geo4992/dataporten-home/fc-3auid-3a&lt;feide-user-id&gt;/</span></code>.
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diff --git a/course_workflow/index.html b/course_workflow/index.html
new file mode 100644
index 0000000..612096a
--- /dev/null
+++ b/course_workflow/index.html
@@ -0,0 +1,545 @@
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+<div class="toctree-wrapper compound">
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+<li class="toctree-l1"><a class="reference internal" href="workflow/">Basic setup</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="workflow/#fork-projects-repository">1. Fork projects repository</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="workflow/#sharing-your-work-within-the-group">4. Sharing your work within the group</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="rules/">Basic Rules for the course</a></li>
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diff --git a/course_workflow/rules/index.html b/course_workflow/rules/index.html
new file mode 100644
index 0000000..332c44f
--- /dev/null
+++ b/course_workflow/rules/index.html
@@ -0,0 +1,543 @@
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+<h1>Basic Rules for the course<a class="headerlink" href="#basic-rules-for-the-course" title="Link to this heading">#</a></h1>
+<blockquote>
+<div><ol class="arabic simple">
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+<li><p>Do not store data in that folder unless it is &lt; 10 Mb. See <a class="reference internal" href="../data/"><span class="doc">Sharing Data</span></a>.</p></li>
+<li><p>Do not download large number of files/large datasets into your home directory.</p></li>
+<li><p>Do not try to make files in the read-only folders (you will get errors on save). Mind where your File browser is when making new notebook/starting new Launcher.</p></li>
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+    <h1>Basic setup</h1>
+    <!-- Table of contents -->
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+        <div id="jb-print-toc">
+            
+            <div>
+                <h2> Contents </h2>
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+            <nav aria-label="Page">
+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#fork-projects-repository">1. Fork projects repository</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#get-gitgub-access-token">2. Get GitGub Access token</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#setup-git-and-clone-on-jupyterhub">3. Setup git and clone on jupyterhub</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#sharing-your-work-within-the-group">4. Sharing your work within the group</a></li>
+</ul>
+            </nav>
+        </div>
+    </div>
+</div>
+
+              
+                
+<div id="searchbox"></div>
+                <article class="bd-article">
+                  
+  <section id="basic-setup">
+<h1>Basic setup<a class="headerlink" href="#basic-setup" title="Link to this heading">#</a></h1>
+<section id="fork-projects-repository">
+<h2>1. Fork projects repository<a class="headerlink" href="#fork-projects-repository" title="Link to this heading">#</a></h2>
+<p>Before you start working on your group projects. You should fork <a class="reference external" href="https://github.com/MetOs-UiO/eScience2024-projects">eScience2024-projects repo</a>.
+To make a fork, go to the repo page. There you will see a <code class="docutils literal notranslate"><span class="pre">fork</span></code> button <img alt="fbutton" src="../../_images/fork_button.png" />. Click on it to create a copy of this repository in your github user space.
+<strong>Uncheck</strong> <code class="docutils literal notranslate"><span class="pre">Copy</span> <span class="pre">the</span> <span class="pre">main</span> <span class="pre">branch</span> <span class="pre">only</span></code> if you do not want to miss on other branches currently on the original repo.</p>
+<a class="reference internal image-reference" href="../../_images/fork-create.png"><img alt="Fork Creation page" src="../../_images/fork-create.png" style="width: 700px;" /></a>
+</section>
+<section id="get-gitgub-access-token">
+<h2>2. Get GitGub Access token<a class="headerlink" href="#get-gitgub-access-token" title="Link to this heading">#</a></h2>
+<p>From <a class="reference external" href="https://docs.github.com/en/enterprise-server&#64;3.9/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens">GitHub documentation</a>.</p>
+<ul class="simple">
+<li><p>Go to Github.</p></li>
+<li><p>Click on your your profile image in the top-right.</p></li>
+<li><p>Click <code class="docutils literal notranslate"><span class="pre">Settings</span></code></p></li>
+<li><p>Click <code class="docutils literal notranslate"><span class="pre">Developer</span> <span class="pre">Settings</span></code></p></li>
+<li><p>Click <code class="docutils literal notranslate"><span class="pre">Personel</span> <span class="pre">access</span> <span class="pre">tokens-&gt;Tokens</span> <span class="pre">(classic)</span></code></p></li>
+<li><p>Click <code class="docutils literal notranslate"><span class="pre">Generate</span> <span class="pre">new</span> <span class="pre">token</span></code></p></li>
+<li><p>Click <code class="docutils literal notranslate"><span class="pre">Generate</span> <span class="pre">new</span> <span class="pre">token</span> <span class="pre">(classic)</span></code></p></li>
+<li><p>Authenticate</p></li>
+<li><p>Make a note</p></li>
+<li><p>Click on <code class="docutils literal notranslate"><span class="pre">repo</span></code>, <code class="docutils literal notranslate"><span class="pre">user</span></code></p></li>
+<li><p>Click <code class="docutils literal notranslate"><span class="pre">generate</span></code></p></li>
+<li><p>Save token somewhere, treat it as a password</p></li>
+</ul>
+</section>
+<section id="setup-git-and-clone-on-jupyterhub">
+<h2>3. Setup git and clone on jupyterhub<a class="headerlink" href="#setup-git-and-clone-on-jupyterhub" title="Link to this heading">#</a></h2>
+<p>After you have forked the projects repo you should login to <a class="reference external" href="https://escience2024.craas1.sigma2.no">Jupyterhub</a>.
+There, you would need to clone your fork and create your first branch you would be working on. See <a class="reference internal" href="../../git_integration/git_jlab/"><span class="doc">Starting with git on the jupyterhub</span></a>.</p>
+<div class="toggle admonition attention">
+<p class="admonition-title">Attention</p>
+<p>If you have already accessed <a class="reference external" href="https://escience2024-test.craas1.sigma2.no">test sever</a>, you should move to <a class="reference external" href="https://escience2024.craas1.sigma2.no">https://escience2024.craas1.sigma2.no</a>.
+Test server is only there for testing and will get shutdown.</p>
+</div>
+<ul>
+<li><p>Open terminal through Launcher.</p></li>
+<li><p>Type this commands filling in your <strong>github</strong> username and email (without <code class="docutils literal notranslate"><span class="pre">&lt;&gt;</span></code>):</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>config<span class="w"> </span>--global<span class="w"> </span>user.name<span class="w"> </span><span class="s2">&quot;&lt;your_username&gt;&quot;</span>
+git<span class="w"> </span>config<span class="w"> </span>--global<span class="w"> </span>user.email<span class="w"> </span><span class="s2">&quot;&lt;your_email&gt;&quot;</span>
+</pre></div>
+</div>
+</li>
+<li><p>Clone <strong>your fork</strong> of  projects repository:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>clone<span class="w"> </span>https://github.com/&lt;your_username&gt;/eScience2024-projects
+</pre></div>
+</div>
+</li>
+<li><p>Go into your clone:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="nb">cd</span><span class="w"> </span>eScience2024-projects
+</pre></div>
+</div>
+</li>
+<li><p>Add upstream repository (See <a class="reference internal" href="../../git_integration/remotes/"><span class="doc">Setting up remotes</span></a>):</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>remote<span class="w"> </span>add<span class="w"> </span>upstream<span class="w"> </span>https://github.com/MetOs-UiO/eScience2024-projects
+git<span class="w"> </span>fetch<span class="w"> </span>--all
+</pre></div>
+</div>
+</li>
+<li><p>Make your first branch with a sensible name (what are you going to work on):</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>checkout<span class="w"> </span>upstream/master
+git<span class="w"> </span>switch<span class="w"> </span>-c<span class="w"> </span>&lt;sensible-branch-name&gt;
+git<span class="w"> </span>push<span class="w"> </span>&lt;sensible-branch-name&gt;<span class="w"> </span>origin/&lt;sensible-branch-name&gt;
+</pre></div>
+</div>
+</li>
+</ul>
+</section>
+<section id="sharing-your-work-within-the-group">
+<h2>4. Sharing your work within the group<a class="headerlink" href="#sharing-your-work-within-the-group" title="Link to this heading">#</a></h2>
+<p>Within your fork, you should put all your code in your <code class="docutils literal notranslate"><span class="pre">Group#</span></code> folder.</p>
+<p>When you need to share your work with the others within your group you need to make a <a class="reference internal" href="../../git_integration/github-work/"><span class="doc">Pull Request</span></a> to the <a class="reference external" href="https://github.com/MetOs-UiO/eScience2024-projects">upstream repo</a> <code class="docutils literal notranslate"><span class="pre">main</span></code> branch.</p>
+<p>After a Teaching assistant responsible for you group has merged your PR to <code class="docutils literal notranslate"><span class="pre">upstream/main</span></code> other members of your group can pull these changes into branches on their forks to work on.</p>
+<p>In addition, you will most likely want to create new branches based on the updated <code class="docutils literal notranslate"><span class="pre">upstream/main</span></code>. See <a class="reference internal" href="../../git_integration/remotes/"><span class="doc">Setting up remotes</span></a>.</p>
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+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#get-gitgub-access-token">2. Get GitGub Access token</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#setup-git-and-clone-on-jupyterhub">3. Setup git and clone on jupyterhub</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#sharing-your-work-within-the-group">4. Sharing your work within the group</a></li>
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diff --git a/data/ACTRIS-data/index.html b/data/ACTRIS-data/index.html
new file mode 100644
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@@ -0,0 +1,566 @@
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+<li class="toctree-l2"><a class="reference internal" href="../../basics/kernels/">Using different kernels in notebooks</a></li>
+</ul>
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+<li class="toctree-l1 current active has-children"><a class="reference internal" href="../">Data</a><input checked class="toctree-checkbox" id="toctree-checkbox-3" name="toctree-checkbox-3" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-3"><i class="fa-solid fa-chevron-down"></i></label><ul class="current">
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+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#access-via-thredds-server-from-nilu">Access via thredds server from NILU</a></li>
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+<h1>ACTRIS data<a class="headerlink" href="#actris-data" title="Link to this heading">#</a></h1>
+<section id="access-via-thredds-server-from-nilu">
+<h2>Access via thredds server from NILU<a class="headerlink" href="#access-via-thredds-server-from-nilu" title="Link to this heading">#</a></h2>
+<p>Check examples 5-11 in ACTRIS Virtual Research Environment repository
+<a class="reference external" href="https://github.com/ACTRIS-Data-Centre/actris-jupyter-hub">ACTRIS and EBAS example notebooks</a></p>
+</section>
+<section id="check-availability-via-actris-web-interface">
+<h2>Check availability via ACTRIS web interface<a class="headerlink" href="#check-availability-via-actris-web-interface" title="Link to this heading">#</a></h2>
+<p><a class="reference external" href="https://ebas-data.nilu.no">https://ebas-data.nilu.no</a></p>
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+  class="btn btn-sm btn-fullscreen-button"
+  title="Fullscreen mode"
+  data-bs-placement="bottom" data-bs-toggle="tooltip"
+>
+  
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+<span class="btn__icon-container">
+  <i class="fas fa-expand"></i>
+  </span>
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+
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+<script>
+document.write(`
+  <button class="btn btn-sm navbar-btn theme-switch-button" title="light/dark" aria-label="light/dark" data-bs-placement="bottom" data-bs-toggle="tooltip">
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+    <span class="theme-switch nav-link" data-mode="dark"><i class="fa-solid fa-moon fa-lg"></i></span>
+    <span class="theme-switch nav-link" data-mode="auto"><i class="fa-solid fa-circle-half-stroke fa-lg"></i></span>
+  </button>
+`);
+</script>
+
+
+<script>
+document.write(`
+  <button class="btn btn-sm navbar-btn search-button search-button__button" title="Search" aria-label="Search" data-bs-placement="bottom" data-bs-toggle="tooltip">
+    <i class="fa-solid fa-magnifying-glass fa-lg"></i>
+  </button>
+`);
+</script>
+<label class="sidebar-toggle secondary-toggle btn btn-sm" for="__secondary"title="Toggle secondary sidebar" data-bs-placement="bottom" data-bs-toggle="tooltip">
+    <span class="fa-solid fa-list"></span>
+</label>
+</div></div>
+      
+    </div>
+  
+</div>
+</div>
+              
+              
+
+<div id="jb-print-docs-body" class="onlyprint">
+    <h1>Acessing model data using intake-esm</h1>
+    <!-- Table of contents -->
+    <div id="print-main-content">
+        <div id="jb-print-toc">
+            
+            <div>
+                <h2> Contents </h2>
+            </div>
+            <nav aria-label="Page">
+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#reading-and-browsing-the-catalog">Reading and browsing the catalog</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#browsing-the-catalog-comparing-the-change-in-aod-over-the-historical-period-across-cmip6-models">Browsing the catalog: Comparing the change in AOD over the historical period across CMIP6 models</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#loading-the-data-and-plotting">Loading the data and plotting</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#exporting-a-subset-of-the-catalog">Exporting a subset of the catalog</a></li>
+</ul>
+</li>
+</ul>
+            </nav>
+        </div>
+    </div>
+</div>
+
+              
+                
+<div id="searchbox"></div>
+                <article class="bd-article">
+                  
+  <section id="acessing-model-data-using-intake-esm">
+<h1>Acessing model data using intake-esm<a class="headerlink" href="#acessing-model-data-using-intake-esm" title="Link to this heading">#</a></h1>
+<p>To access the CMIP6 model data and CESM-PPE data we created intake catalogs to help browse and subset the data. The catalogs are stored in shared folder <code class="docutils literal notranslate"><span class="pre">/mnt/craas1-ns9989k-geo4992/data/intake-catalogs/</span></code></p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Importing the required packages</span>
+<span class="kn">import</span> <span class="nn">intake</span>
+<span class="kn">import</span> <span class="nn">xarray</span> <span class="k">as</span> <span class="nn">xr</span>
+<span class="kn">import</span> <span class="nn">intake_esm</span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+</pre></div>
+</div>
+</div>
+</div>
+<section id="reading-and-browsing-the-catalog">
+<h2>Reading and browsing the catalog<a class="headerlink" href="#reading-and-browsing-the-catalog" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Open the catalog</span>
+
+<span class="c1"># col = intake.open_esm_datastore(&#39;https://storage.googleapis.com/cmip6/pangeo-cmip6.json&#39;) # Remote Pangeo</span>
+
+<span class="n">col</span> <span class="o">=</span> <span class="n">intake</span><span class="o">.</span><span class="n">open_esm_datastore</span><span class="p">(</span><span class="s1">&#39;/mnt/craas1-ns9989k-geo4992/data/catalogs/cmip6.json&#39;</span><span class="p">)</span> <span class="c1"># Local data stored on NIRD</span>
+<span class="n">col</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><p><strong>cmip6 catalog with 155 dataset(s) from 536945 asset(s)</strong>:</p> <div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>unique</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>variable_id</th>
+      <td>583</td>
+    </tr>
+    <tr>
+      <th>table_id</th>
+      <td>24</td>
+    </tr>
+    <tr>
+      <th>source_id</th>
+      <td>75</td>
+    </tr>
+    <tr>
+      <th>experiment_id</th>
+      <td>94</td>
+    </tr>
+    <tr>
+      <th>member_id</th>
+      <td>190</td>
+    </tr>
+    <tr>
+      <th>grid_label</th>
+      <td>11</td>
+    </tr>
+    <tr>
+      <th>time_range</th>
+      <td>9100</td>
+    </tr>
+    <tr>
+      <th>activity_id</th>
+      <td>18</td>
+    </tr>
+    <tr>
+      <th>institution_id</th>
+      <td>35</td>
+    </tr>
+    <tr>
+      <th>version</th>
+      <td>577</td>
+    </tr>
+    <tr>
+      <th>path</th>
+      <td>536945</td>
+    </tr>
+    <tr>
+      <th>dcpp_init_year</th>
+      <td>0</td>
+    </tr>
+    <tr>
+      <th>derived_variable_id</th>
+      <td>0</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+<p>Under the hood <code class="docutils literal notranslate"><span class="pre">intake-esm</span></code> uses a large table csv, which contains some metadata and the paths of where to find it. The data can be stored both locally or in a remote cloud storage i.e <code class="docutils literal notranslate"><span class="pre">pangeo-cloud</span></code>.</p>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>Since the paths listed in the csv table are absolute, notebook starting from the same catalog can be run from any directory, without needing to change the in side the notebook paths.</p>
+</div>
+<section id="browsing-the-catalog-comparing-the-change-in-aod-over-the-historical-period-across-cmip6-models">
+<h3>Browsing the catalog: Comparing the change in AOD over the historical period across CMIP6 models<a class="headerlink" href="#browsing-the-catalog-comparing-the-change-in-aod-over-the-historical-period-across-cmip6-models" title="Link to this heading">#</a></h3>
+<p>The keywords when browsing is columns of the table, e.g. <code class="docutils literal notranslate"><span class="pre">variable_id</span></code>, <code class="docutils literal notranslate"><span class="pre">source_uid</span></code> etc. To list all the keys available for a given key word you can use the <code class="docutils literal notranslate"><span class="pre">col.unique()['&lt;keyword&gt;']</span></code> function.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">col</span> <span class="o">=</span> <span class="n">col</span><span class="o">.</span><span class="n">search</span><span class="p">(</span>
+    <span class="n">variable_id</span><span class="o">=</span><span class="s1">&#39;od550aer&#39;</span><span class="p">,</span>
+    <span class="n">experiment_id</span><span class="o">=</span><span class="s1">&#39;histSST&#39;</span>
+<span class="p">)</span>
+<span class="n">col</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><p><strong>cmip6 catalog with 9 dataset(s) from 190 asset(s)</strong>:</p> <div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>unique</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>variable_id</th>
+      <td>1</td>
+    </tr>
+    <tr>
+      <th>table_id</th>
+      <td>1</td>
+    </tr>
+    <tr>
+      <th>source_id</th>
+      <td>9</td>
+    </tr>
+    <tr>
+      <th>experiment_id</th>
+      <td>1</td>
+    </tr>
+    <tr>
+      <th>member_id</th>
+      <td>4</td>
+    </tr>
+    <tr>
+      <th>grid_label</th>
+      <td>3</td>
+    </tr>
+    <tr>
+      <th>time_range</th>
+      <td>185</td>
+    </tr>
+    <tr>
+      <th>activity_id</th>
+      <td>2</td>
+    </tr>
+    <tr>
+      <th>institution_id</th>
+      <td>9</td>
+    </tr>
+    <tr>
+      <th>version</th>
+      <td>9</td>
+    </tr>
+    <tr>
+      <th>path</th>
+      <td>190</td>
+    </tr>
+    <tr>
+      <th>dcpp_init_year</th>
+      <td>0</td>
+    </tr>
+    <tr>
+      <th>derived_variable_id</th>
+      <td>0</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+<p>Models available for this request:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">col</span><span class="o">.</span><span class="n">unique</span><span class="p">()[</span><span class="s1">&#39;source_id&#39;</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&#39;CNRM-ESM2-1&#39;,
+ &#39;MPI-ESM-1-2-HAM&#39;,
+ &#39;MIROC6&#39;,
+ &#39;UKESM1-0-LL&#39;,
+ &#39;MRI-ESM2-0&#39;,
+ &#39;GISS-E2-1-G&#39;,
+ &#39;CESM2-WACCM&#39;,
+ &#39;GFDL-ESM4&#39;,
+ &#39;EC-Earth3-AerChem&#39;]
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+</section>
+<section id="loading-the-data-and-plotting">
+<h2>Loading the data and plotting<a class="headerlink" href="#loading-the-data-and-plotting" title="Link to this heading">#</a></h2>
+<div class="admonition warning">
+<p class="admonition-title">Warning</p>
+<p>The catalog can be huge, always query and subset catalog before loading the data. Preferably down to level of experiment and variable.</p>
+</div>
+<p>The <code class="docutils literal notranslate"><span class="pre">.to_dataset_dict</span></code> function can accept an optional preprocessing function which can be used to harmonize the datasets, temporal resampling, or slicing.
+Below we made a preprocessing function for resampling the data into annual means and calculate the global average to allow for easily plotting the time series.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">resample_calculate_and_global_avg</span><span class="p">(</span><span class="n">ds</span><span class="p">):</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Function to resample the data to annual mean and calculate the global average.</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="n">ds</span><span class="o">=</span><span class="n">ds</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">time</span><span class="o">=</span><span class="s1">&#39;YE&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="c1"># Resample to annual mean</span>
+    <span class="n">ds</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">drop_vars</span><span class="p">([</span><span class="s1">&#39;lat_bnds&#39;</span><span class="p">,</span><span class="s1">&#39;lon_bnds&#39;</span><span class="p">],</span> <span class="n">errors</span><span class="o">=</span><span class="s1">&#39;ignore&#39;</span><span class="p">)</span> <span class="c1"># create conflict when calculating global average</span>
+    <span class="n">weights</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">deg2rad</span><span class="p">(</span><span class="n">ds</span><span class="o">.</span><span class="n">lat</span><span class="p">))</span> <span class="c1"># Make weighted global average</span>
+    <span class="n">ds_weighted</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">weighted</span><span class="p">(</span><span class="n">weights</span><span class="p">)</span>
+    <span class="n">weighted_mean</span> <span class="o">=</span> <span class="n">ds_weighted</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;lon&#39;</span><span class="p">,</span><span class="s1">&#39;lat&#39;</span><span class="p">])</span>
+    
+    <span class="k">return</span> <span class="n">weighted_mean</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="dropdown admonition">
+<p class="admonition-title">Using dask</p>
+<p>The processing can be done in parallel using dask, which can speed things up a bit.<br />
+The dask cluster below is constrained within the resource each user have available.
+The corresponding dask cluster panel can be viewed by clicking on the dask icon <img src="https://upload.wikimedia.org/wikipedia/commons/1/12/Dask_Logo.svg" alt="" width="30" height="30"> on the left-side panel.</p>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">dask.distributed</span> <span class="kn">import</span> <span class="n">Client</span><span class="p">,</span> <span class="n">LocalCluster</span>
+<span class="n">client</span> <span class="o">=</span> <span class="n">Client</span><span class="p">(</span><span class="n">LocalCluster</span><span class="p">(</span><span class="n">n_workers</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">threads_per_worker</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">memory_limit</span><span class="o">=</span><span class="s1">&#39;16GB&#39;</span><span class="p">))</span>
+</pre></div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># dataset_dict = col.to_dataset_dict()</span>
+<span class="n">dataset_dict</span> <span class="o">=</span> <span class="n">col</span><span class="o">.</span><span class="n">to_dataset_dict</span><span class="p">(</span><span class="n">xarray_open_kwargs</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;use_cftime&#39;</span><span class="p">:</span><span class="kc">True</span><span class="p">,</span> <span class="s1">&#39;chunks&#39;</span><span class="p">:{</span><span class="s1">&#39;time&#39;</span><span class="p">:</span><span class="mi">48</span><span class="p">}},</span> 
+                           <span class="n">aggregate</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+                           <span class="n">preprocess</span><span class="o">=</span><span class="n">resample_calculate_and_global_avg</span><span class="p">,</span>
+                           <span class="n">skip_on_error</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+                           <span class="n">xarray_combine_by_coords</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;combine_attrs&#39;</span><span class="p">:</span> <span class="s1">&#39;override&#39;</span><span class="p">}</span> 
+                          <span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--&gt; The keys in the returned dictionary of datasets are constructed as follows:
+	&#39;activity_id.institution_id&#39;
+</pre></div>
+</div>
+<div class="output text_html">
+<style>
+    /* Turns off some styling */
+    progress {
+        /* gets rid of default border in Firefox and Opera. */
+        border: none;
+        /* Needs to be in here for Safari polyfill so background images work as expected. */
+        background-size: auto;
+    }
+    progress:not([value]), progress:not([value])::-webkit-progress-bar {
+        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);
+    }
+    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {
+        background: #F44336;
+    }
+</style>
+</div><div class="output text_html">
+    <div>
+      <progress value='9' class='' max='9' style='width:300px; height:20px; vertical-align: middle;'></progress>
+      100.00% [9/9 00:13&lt;00:00]
+    </div>
+    </div><div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/opt/conda/envs/pangeo-notebook/lib/python3.11/site-packages/xarray/conventions.py:286: SerializationWarning: variable &#39;od550aer&#39; has multiple fill values {1e+20, 1e+20} defined, decoding all values to NaN.
+  var = coder.decode(var, name=name)
+</pre></div>
+</div>
+</div>
+</div>
+<p>Without the providing a <code class="docutils literal notranslate"><span class="pre">preprocess</span></code> function the time aggregated output as dictionary with grouped by the following keys  <code class="docutils literal notranslate"><span class="pre">&quot;activity_id&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">&quot;institution_id&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">&quot;source_id&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">&quot;experiment_id&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">&quot;table_id&quot;</span></code>, <code class="docutils literal notranslate"><span class="pre">&quot;grid_label&quot;</span></code>.</p>
+<div class="cell tag_hide-output docutils container">
+<div class="cell_input above-output-prompt docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">col</span><span class="o">.</span><span class="n">to_dataset_dict</span><span class="p">(</span><span class="n">xarray_open_kwargs</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;use_cftime&#39;</span><span class="p">:</span><span class="kc">True</span><span class="p">,</span> <span class="s1">&#39;chunks&#39;</span><span class="p">:{</span><span class="s1">&#39;time&#39;</span><span class="p">:</span><span class="mi">48</span><span class="p">}},</span> 
+                           <span class="n">aggregate</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+                           <span class="n">skip_on_error</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+                           <span class="n">xarray_combine_by_coords</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;combine_attrs&#39;</span><span class="p">:</span> <span class="s1">&#39;override&#39;</span><span class="p">}</span> 
+                          <span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<details class="hide below-input">
+<summary aria-label="Toggle hidden content">
+<span class="collapsed">Show code cell output</span>
+<span class="expanded">Hide code cell output</span>
+</summary>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--&gt; The keys in the returned dictionary of datasets are constructed as follows:
+	&#39;activity_id.institution_id&#39;
+</pre></div>
+</div>
+<div class="output text_html">
+<style>
+    /* Turns off some styling */
+    progress {
+        /* gets rid of default border in Firefox and Opera. */
+        border: none;
+        /* Needs to be in here for Safari polyfill so background images work as expected. */
+        background-size: auto;
+    }
+    progress:not([value]), progress:not([value])::-webkit-progress-bar {
+        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);
+    }
+    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {
+        background: #F44336;
+    }
+</style>
+</div><div class="output text_html">
+    <div>
+      <progress value='9' class='' max='9' style='width:300px; height:20px; vertical-align: middle;'></progress>
+      100.00% [9/9 00:06&lt;00:00]
+    </div>
+    </div><div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/opt/conda/envs/pangeo-notebook/lib/python3.11/site-packages/xarray/conventions.py:286: SerializationWarning: variable &#39;od550aer&#39; has multiple fill values {1e+20, 1e+20} defined, decoding all values to NaN.
+  var = coder.decode(var, name=name)
+</pre></div>
+</div>
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>{&#39;AerChemMIP.CNRM-CERFACS&#39;: &lt;xarray.Dataset&gt; Size: 260MB
+ Dimensions:      (lat: 128, lon: 256, time: 1980, axis_nbounds: 2, member_id: 1)
+ Coordinates:
+   * lat          (lat) float64 1kB -88.93 -87.54 -86.14 ... 86.14 87.54 88.93
+   * lon          (lon) float64 2kB 0.0 1.406 2.812 4.219 ... 355.8 357.2 358.6
+   * time         (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00
+   * member_id    (member_id) object 8B &#39;r1i1p1f2&#39;
+ Dimensions without coordinates: axis_nbounds
+ Data variables:
+     time_bounds  (time, axis_nbounds) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;
+     od550aer     (member_id, time, lat, lon) float32 260MB dask.array&lt;chunksize=(1, 48, 128, 256), meta=np.ndarray&gt;
+ Attributes: (12/65)
+     Conventions:                      CF-1.7 CMIP-6.2
+     creation_date:                    2018-08-08T14:22:32Z
+     description:                      Historical transient with SSTs prescrib...
+     title:                            CNRM-ESM2-1 model output prepared for C...
+     activity_id:                      AerChemMIP
+     contact:                          contact.cmip@meteo.fr
+     ...                               ...
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  CNRM-CERFACS
+     intake_esm_attrs:version:         v20190621
+     intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.CNRM-CERFACS,
+ &#39;AerChemMIP.NOAA-GFDL&#39;: &lt;xarray.Dataset&gt; Size: 411MB
+ Dimensions:    (bnds: 2, lat: 180, lon: 288, member_id: 1, time: 1980)
+ Coordinates:
+   * bnds       (bnds) float64 16B 1.0 2.0
+   * lat        (lat) float64 1kB -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5
+     lat_bnds   (lat, bnds) float64 3kB dask.array&lt;chunksize=(180, 2), meta=np.ndarray&gt;
+   * lon        (lon) float64 2kB 0.625 1.875 3.125 4.375 ... 356.9 358.1 359.4
+     lon_bnds   (lon, bnds) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+   * time       (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00
+     time_bnds  (time, bnds) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;
+   * member_id  (member_id) object 8B &#39;r1i1p1f1&#39;
+ Data variables:
+     od550aer   (member_id, time, lat, lon) float32 411MB dask.array&lt;chunksize=(1, 48, 180, 288), meta=np.ndarray&gt;
+ Attributes: (12/56)
+     external_variables:               areacella
+     history:                          File was processed by fremetar (GFDL an...
+     table_id:                         AERmon
+     activity_id:                      AerChemMIP
+     branch_method:                    atmospheric and land state taken from p...
+     branch_time_in_child:             0.0
+     ...                               ...
+     intake_esm_attrs:grid_label:      gr1
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  NOAA-GFDL
+     intake_esm_attrs:version:         v20180701
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.NOAA-GFDL,
+ &#39;AerChemMIP.NCAR&#39;: &lt;xarray.Dataset&gt; Size: 438MB
+ Dimensions:    (member_id: 1, time: 1980, lat: 192, lon: 288, nbnd: 2)
+ Coordinates:
+   * lat        (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0
+   * lon        (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8
+   * time       (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00
+     time_bnds  (time, nbnd) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;
+     lat_bnds   (lat, nbnd) float32 2kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;
+     lon_bnds   (lon, nbnd) float32 2kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+   * member_id  (member_id) object 8B &#39;r1i2p1f1&#39;
+ Dimensions without coordinates: nbnd
+ Data variables:
+     od550aer   (member_id, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 48, 192, 288), meta=np.ndarray&gt;
+ Attributes: (12/56)
+     Conventions:                      CF-1.7 CMIP-6.2
+     activity_id:                      AerChemMIP
+     branch_method:                    no parent
+     branch_time_in_child:             674885.0
+     branch_time_in_parent:            0.0
+     case_id:                          47
+     ...                               ...
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  NCAR
+     intake_esm_attrs:version:         v20190531
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.NCAR,
+ &#39;AerChemMIP.NASA-GISS&#39;: &lt;xarray.Dataset&gt; Size: 103MB
+ Dimensions:    (time: 1980, bnds: 2, lat: 90, lon: 144, member_id: 1)
+ Coordinates:
+   * time       (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00
+     time_bnds  (time, bnds) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;
+   * lat        (lat) float64 720B -89.0 -87.0 -85.0 -83.0 ... 85.0 87.0 89.0
+     lat_bnds   (lat, bnds) float64 1kB dask.array&lt;chunksize=(90, 2), meta=np.ndarray&gt;
+   * lon        (lon) float64 1kB 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8
+     lon_bnds   (lon, bnds) float64 2kB dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;
+   * member_id  (member_id) object 8B &#39;r1i1p3f1&#39;
+ Dimensions without coordinates: bnds
+ Data variables:
+     od550aer   (member_id, time, lat, lon) float32 103MB dask.array&lt;chunksize=(1, 48, 90, 144), meta=np.ndarray&gt;
+ Attributes: (12/56)
+     Conventions:                      CF-1.7 CMIP-6.2
+     activity_id:                      AerChemMIP
+     branch_method:                    standard
+     branch_time_in_child:             0.0
+     branch_time_in_parent:            0.0
+     contact:                          Kenneth Lo (cdkkl@giss.nasa.gov)
+     ...                               ...
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  NASA-GISS
+     intake_esm_attrs:version:         v20191120
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.NASA-GISS,
+ &#39;AerChemMIP.MIROC&#39;: &lt;xarray.Dataset&gt; Size: 260MB
+ Dimensions:     (time: 1980, bnds: 2, lat: 128, lon: 256, member_id: 1)
+ Coordinates:
+   * time        (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00
+     time_bnds   (time, bnds) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;
+   * lat         (lat) float64 1kB -88.93 -87.54 -86.14 ... 86.14 87.54 88.93
+     lat_bnds    (lat, bnds) float64 2kB dask.array&lt;chunksize=(128, 2), meta=np.ndarray&gt;
+   * lon         (lon) float64 2kB 0.0 1.406 2.812 4.219 ... 355.8 357.2 358.6
+     lon_bnds    (lon, bnds) float64 4kB dask.array&lt;chunksize=(256, 2), meta=np.ndarray&gt;
+     wavelength  float64 8B 550.0
+   * member_id   (member_id) object 8B &#39;r1i1p1f1&#39;
+ Dimensions without coordinates: bnds
+ Data variables:
+     od550aer    (member_id, time, lat, lon) float32 260MB dask.array&lt;chunksize=(1, 48, 128, 256), meta=np.ndarray&gt;
+ Attributes: (12/53)
+     Conventions:                      CF-1.7 CMIP-6.2
+     activity_id:                      AerChemMIP
+     branch_method:                    standard
+     branch_time_in_child:             0.0
+     branch_time_in_parent:            0.0
+     data_specs_version:               01.00.31
+     ...                               ...
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  MIROC
+     intake_esm_attrs:version:         v20190828
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.MIROC,
+ &#39;AerChemMIP.MOHC&#39;: &lt;xarray.Dataset&gt; Size: 219MB
+ Dimensions:     (time: 1980, bnds: 2, lat: 144, lon: 192, member_id: 1)
+ Coordinates:
+   * time        (time) object 16kB 1850-01-16 00:00:00 ... 2014-12-16 00:00:00
+     time_bnds   (time, bnds) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;
+   * lat         (lat) float64 1kB -89.38 -88.12 -86.88 ... 86.88 88.12 89.38
+     lat_bnds    (lat, bnds) float64 2kB dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;
+   * lon         (lon) float64 2kB 0.9375 2.812 4.688 6.562 ... 355.3 357.2 359.1
+     lon_bnds    (lon, bnds) float64 3kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;
+     wavelength  float64 8B 550.0
+   * member_id   (member_id) object 8B &#39;r1i1p1f2&#39;
+ Dimensions without coordinates: bnds
+ Data variables:
+     od550aer    (member_id, time, lat, lon) float32 219MB dask.array&lt;chunksize=(1, 48, 144, 192), meta=np.ndarray&gt;
+ Attributes: (12/56)
+     Conventions:                      CF-1.7 CMIP-6.2
+     activity_id:                      AerChemMIP
+     branch_time_in_child:             0.0
+     data_specs_version:               01.00.29
+     experiment:                       historical prescribed SSTs and historic...
+     experiment_id:                    histSST
+     ...                               ...
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  MOHC
+     intake_esm_attrs:version:         v20190902
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.MOHC,
+ &#39;AerChemMIP.MRI&#39;: &lt;xarray.Dataset&gt; Size: 406MB
+ Dimensions:     (time: 1980, bnds: 2, lat: 160, lon: 320, member_id: 1)
+ Coordinates:
+   * time        (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00
+   * lat         (lat) float64 1kB -89.14 -88.03 -86.91 ... 86.91 88.03 89.14
+   * lon         (lon) float64 3kB 0.0 1.125 2.25 3.375 ... 356.6 357.8 358.9
+     wavelength  float64 8B ...
+   * member_id   (member_id) object 8B &#39;r1i1p1f1&#39;
+ Dimensions without coordinates: bnds
+ Data variables:
+     time_bnds   (time, bnds) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;
+     lat_bnds    (lat, bnds) float64 3kB dask.array&lt;chunksize=(160, 2), meta=np.ndarray&gt;
+     lon_bnds    (lon, bnds) float64 5kB dask.array&lt;chunksize=(320, 2), meta=np.ndarray&gt;
+     od550aer    (member_id, time, lat, lon) float32 406MB dask.array&lt;chunksize=(1, 48, 160, 320), meta=np.ndarray&gt;
+ Attributes: (12/59)
+     Conventions:                      CF-1.7 CMIP-6.2
+     activity_id:                      AerChemMIP
+     branch_method:                    standard (the actual parent run: RFMIP ...
+     branch_time_in_child:             0.0
+     branch_time_in_parent:            0.0
+     comment:                          This od550aer includes AOD from stratos...
+     ...                               ...
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  MRI
+     intake_esm_attrs:version:         v20200207
+     intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.MRI,
+ &#39;AerChemMIP.HAMMOZ-Consortium&#39;: &lt;xarray.Dataset&gt; Size: 146MB
+ Dimensions:     (time: 1980, bnds: 2, lat: 96, lon: 192, member_id: 1)
+ Coordinates:
+   * time        (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00
+     time_bnds   (time, bnds) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;
+   * lat         (lat) float64 768B -88.57 -86.72 -84.86 ... 84.86 86.72 88.57
+     lat_bnds    (lat, bnds) float64 2kB dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;
+   * lon         (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1
+     lon_bnds    (lon, bnds) float64 3kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;
+     wavelength  float64 8B 550.0
+   * member_id   (member_id) object 8B &#39;r1i1p1f1&#39;
+ Dimensions without coordinates: bnds
+ Data variables:
+     od550aer    (member_id, time, lat, lon) float32 146MB dask.array&lt;chunksize=(1, 48, 96, 192), meta=np.ndarray&gt;
+ Attributes: (12/57)
+     CDO:                              Climate Data Operators version 1.9.9rc8...
+     Conventions:                      CF-1.7 CMIP-6.2
+     activity_id:                      AerChemMIP
+     branch_method:                    standard
+     branch_time_in_child:             0.0
+     branch_time_in_parent:            0.0
+     ...                               ...
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  HAMMOZ-Consortium
+     intake_esm_attrs:version:         v20190628
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.HAMMOZ-Consortium,
+ &#39;CMIP.EC-Earth-Consortium&#39;: &lt;xarray.Dataset&gt; Size: 86MB
+ Dimensions:     (time: 1980, bnds: 2, lat: 90, lon: 120, member_id: 1)
+ Coordinates:
+   * time        (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00
+     time_bnds   (time, bnds) object 32kB dask.array&lt;chunksize=(12, 2), meta=np.ndarray&gt;
+   * lat         (lat) float64 720B -89.0 -87.0 -85.0 -83.0 ... 85.0 87.0 89.0
+     lat_bnds    (lat, bnds) float64 1kB dask.array&lt;chunksize=(90, 2), meta=np.ndarray&gt;
+   * lon         (lon) float64 960B 1.5 4.5 7.5 10.5 ... 349.5 352.5 355.5 358.5
+     lon_bnds    (lon, bnds) float64 2kB dask.array&lt;chunksize=(120, 2), meta=np.ndarray&gt;
+     wavelength  float64 8B 550.0
+   * member_id   (member_id) object 8B &#39;r1i1p1f1&#39;
+ Dimensions without coordinates: bnds
+ Data variables:
+     od550aer    (member_id, time, lat, lon) float32 86MB dask.array&lt;chunksize=(1, 12, 90, 120), meta=np.ndarray&gt;
+ Attributes: (12/57)
+     Conventions:                        CF-1.7 CMIP-6.2
+     activity_id:                        AerChemMIP
+     branch_method:                      standard
+     branch_time_in_child:               0.0
+     branch_time_in_parent:              0.0
+     contact:                            cmip6-data@ec-earth.org
+     ...                                 ...
+     intake_esm_attrs:grid_label:        gn
+     intake_esm_attrs:activity_id:       CMIP
+     intake_esm_attrs:institution_id:    EC-Earth-Consortium
+     intake_esm_attrs:version:           v20210309
+     intake_esm_attrs:_data_format_:     netcdf
+     intake_esm_dataset_key:             CMIP.EC-Earth-Consortium}
+</pre></div>
+</div>
+</div>
+</details>
+</div>
+<p>Preprocess dictionary only contain the time series, which is easy to loop over and plot for each model.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dataset_dict</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>{&#39;AerChemMIP.NASA-GISS&#39;: &lt;xarray.Dataset&gt; Size: 3kB
+ Dimensions:    (time: 165, member_id: 1)
+ Coordinates:
+   * time       (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00
+   * member_id  (member_id) object 8B &#39;r1i1p3f1&#39;
+ Data variables:
+     od550aer   (member_id, time) float64 1kB dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;
+ Attributes:
+     intake_esm_vars:                  [&#39;od550aer&#39;]
+     intake_esm_attrs:variable_id:     od550aer
+     intake_esm_attrs:table_id:        AERmon
+     intake_esm_attrs:source_id:       GISS-E2-1-G
+     intake_esm_attrs:experiment_id:   histSST
+     intake_esm_attrs:member_id:       r1i1p3f1
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  NASA-GISS
+     intake_esm_attrs:version:         v20191120
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.NASA-GISS,
+ &#39;AerChemMIP.CNRM-CERFACS&#39;: &lt;xarray.Dataset&gt; Size: 3kB
+ Dimensions:    (time: 165, member_id: 1)
+ Coordinates:
+   * time       (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00
+   * member_id  (member_id) object 8B &#39;r1i1p1f2&#39;
+ Data variables:
+     od550aer   (member_id, time) float64 1kB dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;
+ Attributes: (12/14)
+     intake_esm_vars:                  [&#39;od550aer&#39;]
+     intake_esm_attrs:variable_id:     od550aer
+     intake_esm_attrs:table_id:        AERmon
+     intake_esm_attrs:source_id:       CNRM-ESM2-1
+     intake_esm_attrs:experiment_id:   histSST
+     intake_esm_attrs:member_id:       r1i1p1f2
+     ...                               ...
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  CNRM-CERFACS
+     intake_esm_attrs:version:         v20190621
+     intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.CNRM-CERFACS,
+ &#39;AerChemMIP.NCAR&#39;: &lt;xarray.Dataset&gt; Size: 3kB
+ Dimensions:    (time: 165, member_id: 1)
+ Coordinates:
+   * time       (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00
+   * member_id  (member_id) object 8B &#39;r1i2p1f1&#39;
+ Data variables:
+     od550aer   (member_id, time) float64 1kB dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;
+ Attributes:
+     intake_esm_vars:                  [&#39;od550aer&#39;]
+     intake_esm_attrs:variable_id:     od550aer
+     intake_esm_attrs:table_id:        AERmon
+     intake_esm_attrs:source_id:       CESM2-WACCM
+     intake_esm_attrs:experiment_id:   histSST
+     intake_esm_attrs:member_id:       r1i2p1f1
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  NCAR
+     intake_esm_attrs:version:         v20190531
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.NCAR,
+ &#39;AerChemMIP.NOAA-GFDL&#39;: &lt;xarray.Dataset&gt; Size: 3kB
+ Dimensions:    (time: 165, member_id: 1)
+ Coordinates:
+   * time       (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00
+   * member_id  (member_id) object 8B &#39;r1i1p1f1&#39;
+ Data variables:
+     od550aer   (member_id, time) float64 1kB dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;
+ Attributes:
+     intake_esm_vars:                  [&#39;od550aer&#39;]
+     intake_esm_attrs:variable_id:     od550aer
+     intake_esm_attrs:table_id:        AERmon
+     intake_esm_attrs:source_id:       GFDL-ESM4
+     intake_esm_attrs:experiment_id:   histSST
+     intake_esm_attrs:member_id:       r1i1p1f1
+     intake_esm_attrs:grid_label:      gr1
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  NOAA-GFDL
+     intake_esm_attrs:version:         v20180701
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.NOAA-GFDL,
+ &#39;AerChemMIP.MIROC&#39;: &lt;xarray.Dataset&gt; Size: 3kB
+ Dimensions:     (time: 165, member_id: 1)
+ Coordinates:
+     wavelength  float64 8B 550.0
+   * time        (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00
+   * member_id   (member_id) object 8B &#39;r1i1p1f1&#39;
+ Data variables:
+     od550aer    (member_id, time) float64 1kB dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;
+ Attributes:
+     intake_esm_vars:                  [&#39;od550aer&#39;]
+     intake_esm_attrs:variable_id:     od550aer
+     intake_esm_attrs:table_id:        AERmon
+     intake_esm_attrs:source_id:       MIROC6
+     intake_esm_attrs:experiment_id:   histSST
+     intake_esm_attrs:member_id:       r1i1p1f1
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  MIROC
+     intake_esm_attrs:version:         v20190828
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.MIROC,
+ &#39;AerChemMIP.MOHC&#39;: &lt;xarray.Dataset&gt; Size: 3kB
+ Dimensions:     (time: 165, member_id: 1)
+ Coordinates:
+     wavelength  float64 8B 550.0
+   * time        (time) object 1kB 1850-12-30 00:00:00 ... 2014-12-30 00:00:00
+   * member_id   (member_id) object 8B &#39;r1i1p1f2&#39;
+ Data variables:
+     od550aer    (member_id, time) float64 1kB dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;
+ Attributes:
+     intake_esm_vars:                  [&#39;od550aer&#39;]
+     intake_esm_attrs:variable_id:     od550aer
+     intake_esm_attrs:table_id:        AERmon
+     intake_esm_attrs:source_id:       UKESM1-0-LL
+     intake_esm_attrs:experiment_id:   histSST
+     intake_esm_attrs:member_id:       r1i1p1f2
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  MOHC
+     intake_esm_attrs:version:         v20190902
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.MOHC,
+ &#39;AerChemMIP.HAMMOZ-Consortium&#39;: &lt;xarray.Dataset&gt; Size: 3kB
+ Dimensions:     (time: 165, member_id: 1)
+ Coordinates:
+     wavelength  float64 8B 550.0
+   * time        (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00
+   * member_id   (member_id) object 8B &#39;r1i1p1f1&#39;
+ Data variables:
+     od550aer    (member_id, time) float64 1kB dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;
+ Attributes:
+     intake_esm_vars:                  [&#39;od550aer&#39;]
+     intake_esm_attrs:variable_id:     od550aer
+     intake_esm_attrs:table_id:        AERmon
+     intake_esm_attrs:source_id:       MPI-ESM-1-2-HAM
+     intake_esm_attrs:experiment_id:   histSST
+     intake_esm_attrs:member_id:       r1i1p1f1
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  HAMMOZ-Consortium
+     intake_esm_attrs:version:         v20190628
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.HAMMOZ-Consortium,
+ &#39;AerChemMIP.MRI&#39;: &lt;xarray.Dataset&gt; Size: 3kB
+ Dimensions:     (time: 165, member_id: 1)
+ Coordinates:
+     wavelength  float64 8B 550.0
+   * time        (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00
+   * member_id   (member_id) object 8B &#39;r1i1p1f1&#39;
+ Data variables:
+     od550aer    (member_id, time) float64 1kB dask.array&lt;chunksize=(1, 4), meta=np.ndarray&gt;
+ Attributes: (12/14)
+     intake_esm_vars:                  [&#39;od550aer&#39;]
+     intake_esm_attrs:variable_id:     od550aer
+     intake_esm_attrs:table_id:        AERmon
+     intake_esm_attrs:source_id:       MRI-ESM2-0
+     intake_esm_attrs:experiment_id:   histSST
+     intake_esm_attrs:member_id:       r1i1p1f1
+     ...                               ...
+     intake_esm_attrs:activity_id:     AerChemMIP
+     intake_esm_attrs:institution_id:  MRI
+     intake_esm_attrs:version:         v20200207
+     intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           AerChemMIP.MRI,
+ &#39;CMIP.EC-Earth-Consortium&#39;: &lt;xarray.Dataset&gt; Size: 3kB
+ Dimensions:     (time: 165, member_id: 1)
+ Coordinates:
+     wavelength  float64 8B 550.0
+   * time        (time) object 1kB 1850-12-31 00:00:00 ... 2014-12-31 00:00:00
+   * member_id   (member_id) object 8B &#39;r1i1p1f1&#39;
+ Data variables:
+     od550aer    (member_id, time) float64 1kB dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;
+ Attributes:
+     intake_esm_vars:                  [&#39;od550aer&#39;]
+     intake_esm_attrs:variable_id:     od550aer
+     intake_esm_attrs:table_id:        AERmon
+     intake_esm_attrs:source_id:       EC-Earth3-AerChem
+     intake_esm_attrs:experiment_id:   histSST
+     intake_esm_attrs:member_id:       r1i1p1f1
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:activity_id:     CMIP
+     intake_esm_attrs:institution_id:  EC-Earth-Consortium
+     intake_esm_attrs:version:         v20210309
+     intake_esm_attrs:_data_format_:   netcdf
+     intake_esm_dataset_key:           CMIP.EC-Earth-Consortium}
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">fig</span><span class="p">,</span><span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
+<span class="k">for</span> <span class="n">datakey</span><span class="p">,</span> <span class="n">data</span> <span class="ow">in</span> <span class="n">dataset_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span> <span class="c1"># Looping over ever varable in the dictionary</span>
+    <span class="n">source_id</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">attrs</span><span class="p">[</span><span class="s1">&#39;intake_esm_attrs:source_id&#39;</span><span class="p">]</span>
+    <span class="n">member_id</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">attrs</span><span class="p">[</span><span class="s1">&#39;intake_esm_attrs:member_id&#39;</span><span class="p">]</span>
+    <span class="n">data</span><span class="p">[</span><span class="s1">&#39;od550aer&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">member_id</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="n">source_id</span><span class="si">}</span><span class="s1"> </span><span class="si">{</span><span class="n">member_id</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">)</span>
+
+<span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+    
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7fa1fc40f110&gt;
+</pre></div>
+</div>
+<img alt="../../_images/1ce8477193212fee86cf48b45f0742f9510c9b130e3820534a8d57922614db8e.png" src="../../_images/1ce8477193212fee86cf48b45f0742f9510c9b130e3820534a8d57922614db8e.png" />
+</div>
+</div>
+<section id="exporting-a-subset-of-the-catalog">
+<h3>Exporting a subset of the catalog<a class="headerlink" href="#exporting-a-subset-of-the-catalog" title="Link to this heading">#</a></h3>
+<p>Most likely you will only be analyzing a small subset of experiments the model experiment and it could be beneficial to work with a reduced catalog.
+Below we will make a subset that only contain the information related to <code class="docutils literal notranslate"><span class="pre">histSST</span></code> and <code class="docutils literal notranslate"><span class="pre">histSST-piaer</span></code>, and only the absorption optical depth (<code class="docutils literal notranslate"><span class="pre">od550abs</span></code>) and total optical depth (<code class="docutils literal notranslate"><span class="pre">od550aer</span></code>).</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">col</span> <span class="o">=</span> <span class="n">intake</span><span class="o">.</span><span class="n">open_esm_datastore</span><span class="p">(</span><span class="s1">&#39;/mnt/craas1-ns9989k-geo4992/data/cmip6.json&#39;</span><span class="p">)</span> <span class="c1"># Local data stored on NIRD</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">col</span> <span class="o">=</span> <span class="n">col</span><span class="o">.</span><span class="n">search</span><span class="p">(</span>    
+    <span class="n">experiment_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;histSST&#39;</span><span class="p">,</span> <span class="s1">&#39;histSST-piaer&#39;</span><span class="p">],</span>
+    <span class="n">variable_id</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;od550abs&#39;</span><span class="p">,</span> <span class="s1">&#39;od550aer&#39;</span><span class="p">]</span>
+<span class="p">)</span>
+<span class="n">col</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><p><strong>cmip6 catalog with 9 dataset(s) from 190 asset(s)</strong>:</p> <div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>unique</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>variable_id</th>
+      <td>1</td>
+    </tr>
+    <tr>
+      <th>table_id</th>
+      <td>1</td>
+    </tr>
+    <tr>
+      <th>source_id</th>
+      <td>9</td>
+    </tr>
+    <tr>
+      <th>experiment_id</th>
+      <td>1</td>
+    </tr>
+    <tr>
+      <th>member_id</th>
+      <td>4</td>
+    </tr>
+    <tr>
+      <th>grid_label</th>
+      <td>3</td>
+    </tr>
+    <tr>
+      <th>time_range</th>
+      <td>185</td>
+    </tr>
+    <tr>
+      <th>activity_id</th>
+      <td>2</td>
+    </tr>
+    <tr>
+      <th>institution_id</th>
+      <td>9</td>
+    </tr>
+    <tr>
+      <th>version</th>
+      <td>9</td>
+    </tr>
+    <tr>
+      <th>path</th>
+      <td>190</td>
+    </tr>
+    <tr>
+      <th>dcpp_init_year</th>
+      <td>0</td>
+    </tr>
+    <tr>
+      <th>derived_variable_id</th>
+      <td>0</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+<p>Then when we are happy with the selection the catalog can be exported as follows:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">col</span><span class="o">.</span><span class="n">serialize</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">&#39;histSST-AerChemMIP&#39;</span><span class="p">,</span><span class="n">catalog_type</span><span class="o">=</span><span class="s1">&#39;file&#39;</span><span class="p">,</span><span class="n">directory</span><span class="o">=</span><span class="s1">&#39;~/&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Successfully wrote ESM catalog json file to: file:///home/fc-3auid-3a9fdc0c87-2d7836-2d4bdc-2db802-2d9a250c322e3b//histSST-AerChemMIP.json
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">col</span> <span class="o">=</span> <span class="n">intake</span><span class="o">.</span><span class="n">open_esm_datastore</span><span class="p">(</span><span class="s1">&#39;~/histSST-AerChemMIP.json&#39;</span><span class="p">)</span>
+<span class="n">col</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><p><strong>histSST-AerChemMIP catalog with 9 dataset(s) from 190 asset(s)</strong>:</p> <div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>unique</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>variable_id</th>
+      <td>1</td>
+    </tr>
+    <tr>
+      <th>table_id</th>
+      <td>1</td>
+    </tr>
+    <tr>
+      <th>source_id</th>
+      <td>9</td>
+    </tr>
+    <tr>
+      <th>experiment_id</th>
+      <td>1</td>
+    </tr>
+    <tr>
+      <th>member_id</th>
+      <td>4</td>
+    </tr>
+    <tr>
+      <th>grid_label</th>
+      <td>3</td>
+    </tr>
+    <tr>
+      <th>time_range</th>
+      <td>185</td>
+    </tr>
+    <tr>
+      <th>activity_id</th>
+      <td>2</td>
+    </tr>
+    <tr>
+      <th>institution_id</th>
+      <td>9</td>
+    </tr>
+    <tr>
+      <th>version</th>
+      <td>9</td>
+    </tr>
+    <tr>
+      <th>path</th>
+      <td>190</td>
+    </tr>
+    <tr>
+      <th>dcpp_init_year</th>
+      <td>0</td>
+    </tr>
+    <tr>
+      <th>derived_variable_id</th>
+      <td>0</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+</section>
+</section>
+</section>
+
+
+                </article>
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+        <p class="prev-next-subtitle">previous</p>
+        <p class="prev-next-title">Data</p>
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+    <i class="fa-solid fa-list"></i> Contents
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+    <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#reading-and-browsing-the-catalog">Reading and browsing the catalog</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#browsing-the-catalog-comparing-the-change-in-aod-over-the-historical-period-across-cmip6-models">Browsing the catalog: Comparing the change in AOD over the historical period across CMIP6 models</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#loading-the-data-and-plotting">Loading the data and plotting</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#exporting-a-subset-of-the-catalog">Exporting a subset of the catalog</a></li>
+</ul>
+</li>
+</ul>
+  </nav></div>
+
+</div></div>
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+<h1>Local shared data<a class="headerlink" href="#local-shared-data" title="Link to this heading">#</a></h1>
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+<h2>Direct local data access<a class="headerlink" href="#direct-local-data-access" title="Link to this heading">#</a></h2>
+<p>Mounted data directories:
+- <code class="docutils literal notranslate"><span class="pre">~/shared-craas1-nn9989k-geo4992/data/</span></code> - data shared during this course.
+- <code class="docutils literal notranslate"><span class="pre">~/shared-craas1-nn9989k-cmip6/</span></code> subset of CMIP6 data from ESGF.
+- <code class="docutils literal notranslate"><span class="pre">~/shared-craas1-nn9989k-ns9560k/CAM6_CESM_PPE</span></code> CAM6 output for Perturbed Parameter Experiment
+- <code class="docutils literal notranslate"><span class="pre">~/shared-craas1-nn9989k-ns9560k/</span></code></p>
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+<li class="toctree-l1 current active"><a class="current reference internal" href="#">Jupyterhub access</a></li>
+<li class="toctree-l1 has-children"><a class="reference internal" href="../course_workflow/">Workflow for eScience2024 course</a><input checked class="toctree-checkbox" id="toctree-checkbox-1" name="toctree-checkbox-1" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-1"><i class="fa-solid fa-chevron-down"></i></label><ul>
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+<li class="toctree-l2"><a class="reference internal" href="../course_workflow/data/">Sharing data</a></li>
+</ul>
+</li>
+<li class="toctree-l1 has-children"><a class="reference internal" href="../basics/">Jupyterhub basic usage</a><input checked class="toctree-checkbox" id="toctree-checkbox-2" name="toctree-checkbox-2" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-2"><i class="fa-solid fa-chevron-down"></i></label><ul>
+<li class="toctree-l2"><a class="reference internal" href="../basics/start_stop/">Starting and stopping your server</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../basics/lab/">The JupyterLab Interface</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../basics/kernels/">Using different kernels in notebooks</a></li>
+</ul>
+</li>
+<li class="toctree-l1 has-children"><a class="reference internal" href="../data/">Data</a><input checked class="toctree-checkbox" id="toctree-checkbox-3" name="toctree-checkbox-3" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-3"><i class="fa-solid fa-chevron-down"></i></label><ul>
+<li class="toctree-l2"><a class="reference internal" href="../data/Intake-data-acess/">Acessing model data using intake-esm</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../data/local-data/">Local shared data</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../data/ACTRIS-data/">ACTRIS data</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/from_ebas_using_xarray/">Using xarray to read EBAS data</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/masked_and_weighted_average/">Using masks and computing weighted average</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/projections/">Using cartopy and projections for plotting</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/some-xarray-pandas-presentation_Sara/">Some tips with xarray and pandas</a></li>
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+    <h1>Jupyterhub access</h1>
+    <!-- Table of contents -->
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+        <div id="jb-print-toc">
+            
+            <div>
+                <h2> Contents </h2>
+            </div>
+            <nav aria-label="Page">
+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#creating-feide-openidp-account">Creating Feide OpenIdP account:</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#joining-escience2024-feide-group">Joining eScience2024 Feide group:</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#accessing-jupyterhub">Accessing Jupyterhub:</a></li>
+</ul>
+            </nav>
+        </div>
+    </div>
+</div>
+
+              
+                
+<div id="searchbox"></div>
+                <article class="bd-article">
+                  
+  <section id="jupyterhub-access">
+<h1>Jupyterhub access<a class="headerlink" href="#jupyterhub-access" title="Link to this heading">#</a></h1>
+<section id="creating-feide-openidp-account">
+<h2>Creating Feide OpenIdP account:<a class="headerlink" href="#creating-feide-openidp-account" title="Link to this heading">#</a></h2>
+<p>If you do not have a Feide account follow these instructions:</p>
+<blockquote>
+<div><ul class="simple">
+<li><p>Go to <a class="reference external" href="https://openidp.feide.no/">Feide OpenIdP</a>.</p></li>
+<li><p>Click on <a class="reference external" href="https://openidp.feide.no/simplesaml/module.php/selfregister/newUser.php">Register a new account</a>. Preferably provide the email you specified for the course.</p></li>
+<li><p>You will receive an email from Feide OpenIdP &lt;<a class="reference external" href="mailto:noreply&#37;&#52;&#48;sikt&#46;no">noreply<span>&#64;</span>sikt<span>&#46;</span>no</a>&gt;</p></li>
+</ul>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>You might need to check your spam/junk folder</p>
+</div>
+<ul class="simple">
+<li><p>Click on the link in the email and proceed with further registration.</p></li>
+<li><p>Now you have FEIDE <strong>guest</strong> account.</p></li>
+</ul>
+</div></blockquote>
+</section>
+<section id="joining-escience2024-feide-group">
+<h2>Joining eScience2024 Feide group:<a class="headerlink" href="#joining-escience2024-feide-group" title="Link to this heading">#</a></h2>
+<p>Once you created a FEIDE account (or if you already have one):</p>
+<blockquote>
+<div><ul class="simple">
+<li><p>You might have already received the invitation to a FEIDE group eScience2024 by email. If not, send email to Matvey Debolskiy &lt;<a class="reference external" href="mailto:matveyd&#37;&#52;&#48;uio&#46;no">matveyd<span>&#64;</span>uio<span>&#46;</span>no</a>&gt;.</p></li>
+<li><p>Click on the link in the email. You will be suggested to login in into dataporten.</p></li>
+<li><p>Login using your FEIDE account</p></li>
+</ul>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<dl class="simple">
+<dt>For those with FEIDE guest accounts:</dt><dd><ul class="simple">
+<li><p>Click <code class="docutils literal notranslate"><span class="pre">Can't</span> <span class="pre">find</span> <span class="pre">your</span> <span class="pre">user</span> <span class="pre">account?</span></code></p></li>
+<li><p>Choose <code class="docutils literal notranslate"><span class="pre">Feide</span> <span class="pre">guest</span> <span class="pre">users</span></code>, you would be promted to the OpenIdP login page.</p></li>
+</ul>
+</dd>
+</dl>
+</div>
+<ul class="simple">
+<li><p>Accept policies and become member of <strong>eScience2024</strong> Feide group</p></li>
+</ul>
+</div></blockquote>
+</section>
+<section id="accessing-jupyterhub">
+<h2>Accessing Jupyterhub:<a class="headerlink" href="#accessing-jupyterhub" title="Link to this heading">#</a></h2>
+<p>Once you’ve become a memeber of <strong>escience2024</strong> Feide group you can use Jupyterhub for eScience2024 cource at <a class="reference external" href="https://escience2024.craas1.sigma2.no">https://escience2024.craas1.sigma2.no</a>.</p>
+<blockquote>
+<div><ul class="simple">
+<li><p>Press <code class="docutils literal notranslate"><span class="pre">Sing</span> <span class="pre">in</span> <span class="pre">with</span> <span class="pre">NIRD</span> <span class="pre">Apps</span> <span class="pre">Auth</span></code>.</p></li>
+<li><p>Login with your Feide or Feide guest account.</p></li>
+</ul>
+<details class="summary-feide-guests">
+<summary>Feide Guests</summary><dl class="simple">
+<dt>For those with FEIDE guest accounts:</dt><dd><ul class="simple">
+<li><p>Click <code class="docutils literal notranslate"><span class="pre">Can't</span> <span class="pre">find</span> <span class="pre">your</span> <span class="pre">user</span> <span class="pre">account?</span></code></p></li>
+<li><p>Choose <code class="docutils literal notranslate"><span class="pre">Feide</span> <span class="pre">guest</span> <span class="pre">users</span></code>, you would be promted to the OpenIdP login page.</p></li>
+</ul>
+</dd>
+</dl>
+</details></div></blockquote>
+<div class="admonition warning">
+<p class="admonition-title">Warning</p>
+<p><strong>Test server access</strong></p>
+<p>Though <a class="reference external" href="https://escience2024-test.craas1.sigma2.no">test sever</a> is still reachable but will be shutdown soon.
+So if you have anything there, move it to escience2024 server. If you  need help ask <strong>&#64;mvdeoblskiy</strong>.</p>
+</div>
+</section>
+</section>
+
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+    <h1>Starting with git on the jupyterhub</h1>
+    <!-- Table of contents -->
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+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#adding-your-git-username-and-email">Adding your git username and email</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#using-git-gui-extension">Using git GUI extension:</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#using-git-cli">Using git CLI</a></li>
+</ul>
+            </nav>
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+              
+                
+<div id="searchbox"></div>
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+                  
+  <section id="starting-with-git-on-the-jupyterhub">
+<h1>Starting with git on the jupyterhub<a class="headerlink" href="#starting-with-git-on-the-jupyterhub" title="Link to this heading">#</a></h1>
+<section id="adding-your-git-username-and-email">
+<h2>Adding your git username and email<a class="headerlink" href="#adding-your-git-username-and-email" title="Link to this heading">#</a></h2>
+<p>First thing that you would want to do is to add your github username and email to the <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">config</span></code>.
+To do that, open a terminal (f.e. through launcher) and do:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>config<span class="w"> </span>--global<span class="w"> </span>user.name<span class="w"> </span><span class="s2">&quot;&lt;your_username&gt;&quot;</span>
+git<span class="w"> </span>config<span class="w"> </span>--global<span class="w"> </span>user.email<span class="w"> </span><span class="s2">&quot;&lt;your_email&gt;&quot;</span>
+</pre></div>
+</div>
+<p>You can check if the config is added by doing <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">config</span> <span class="pre">--get</span> <span class="pre">user.name</span></code>.</p>
+</section>
+<section id="using-git-gui-extension">
+<h2>Using git GUI extension:<a class="headerlink" href="#using-git-gui-extension" title="Link to this heading">#</a></h2>
+<p>Jupyterlab includes a GUI to make it easier to use git.
+You can see a git icon <img alt="gitico" src="../../_images/git_ico.png" /> on the left panel. To clone a repository, click on the icon and then on <strong>Clone Reopsitory</strong>.
+You should see the following prompt:</p>
+<a class="reference internal image-reference" href="../../_images/clone-repo.png"><img alt="Cloning repo GUI" src="../../_images/clone-repo.png" style="width: 800px;" /></a>
+<p>Check both boxes and press <strong>Clone</strong>. You will get the following prompt:</p>
+<a class="reference internal image-reference" href="../../_images/gui-credentials.png"><img alt="Credentials prompt GUI" src="../../_images/gui-credentials.png" style="width: 300px;" /></a>
+<p>If you do not know what a personal access token is follow <a class="reference external" href="https://docs.github.com/en/enterprise-server&#64;3.9/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens">official github instructions</a> to create one. Usually, the tokens start with <code class="docutils literal notranslate"><span class="pre">ghp_***</span></code>. Treat this token as a password.
+Once you’ve logged in you will see in the file browser that a folder was created with the same name as the repo you have cloned.
+Go into that folder in the file browser and then click on the git tab <img alt="gitico" src="../../_images/git_ico.png" /> in the left panel. You will see the following:</p>
+<a class="reference internal image-reference" href="../../_images/repo-tab.png"><img alt="Repo tab GUI" src="../../_images/repo-tab.png" style="width: 200px;" /></a>
+<p>You can hover over different tabs and buttons too see what they do.
+If you click on <strong>History</strong> tab, you will see the beautiful graph of the commit-history of the branch you are currently on.
+You can clone multiple repositories and if you are in some repo folder within your file browser you can always click on the git icon to use version control for that specific repository.</p>
+<p>Pulling and pushing and fetching are done using the cloud buttons <img alt="ppbuttons" src="../../_images/push-pull-gui.png" /> at the top right of the panel.</p>
+</section>
+<section id="using-git-cli">
+<h2>Using git CLI<a class="headerlink" href="#using-git-cli" title="Link to this heading">#</a></h2>
+<p>You can also use git within the command line.
+To do that, Open a terminal through the <strong>Launcher</strong>. That will open the terminal at your current directory.
+To see the absolute path of where are you at use <code class="docutils literal notranslate"><span class="pre">pwd</span></code>. Now, we will clone a repository that we use for the course (assuming you made a fork of it).</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>clone<span class="w"> </span>&lt;repository<span class="w"> </span>url&gt;<span class="w"> </span>&lt;folder&gt;
+
+<span class="nb">cd</span><span class="w"> </span>&lt;folder&gt;
+</pre></div>
+</div>
+<p>If the <code class="docutils literal notranslate"><span class="pre">folder</span></code> is not provided, the repository will be cloned into a folder with the same name as a repository.
+Since we are using private repositories, you will get promoted to authenticate. Use your github username and <a class="reference external" href="https://docs.github.com/en/enterprise-server&#64;3.9/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens">token</a>.</p>
+<p>Once you are in the repo folder. You can create a new branch for a feature/piece of work you will be working on, so you can make a pull request to the upstream repo later.
+To see what branch are you on right now and any changes you have made use <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">status</span></code>.</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>switch<span class="w"> </span>-c<span class="w"> </span>my-new-branch
+
+git<span class="w"> </span>status
+</pre></div>
+</div>
+<p>You will see that you just created a new branch and that you are up-to-date with it. Note, this branch is local and does not exist yet on github repo.</p>
+<p>Now, suppose you made some changes to a file <code class="docutils literal notranslate"><span class="pre">file.txt</span></code>. You want to commit the changes and than push it to the remote (your repo on git hub). To commit your changes, you can add a single file, multiple files or all the changes.</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1">#this will stage a single file</span>
+git<span class="w"> </span>add<span class="w"> </span>file.txt
+<span class="c1">#this will stage multiple files</span>
+git<span class="w"> </span>add<span class="w"> </span>file1.txt<span class="w"> </span>file2.txt<span class="w"> </span>...
+</pre></div>
+</div>
+<p>To commit the files you have staged:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>commit<span class="w"> </span>-m<span class="w"> </span><span class="s2">&quot;commit-message, changed file.txt&quot;</span>
+</pre></div>
+</div>
+<p>You can commit all the changes at once:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>commit<span class="w"> </span>-a<span class="w"> </span>-m<span class="w"> </span><span class="s2">&quot;changed bunch of stuff&quot;</span>
+</pre></div>
+</div>
+<p>Once you’ve made commits, you want to push them to the remote repository:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1">#--set-upstream origin my-new-branch is only needed once</span>
+<span class="c1"># for every newly created branch to push it along with commits.</span>
+git<span class="w"> </span>push<span class="w"> </span>--set-upstream<span class="w"> </span>origin<span class="w"> </span>my-new-branch
+<span class="c1"># after that you can just simply do:</span>
+git<span class="w"> </span>push
+</pre></div>
+</div>
+<p>To pull changes from the remote to your local repo use <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">pull</span></code>. To get updated history (branches, tags etc) from the remote use <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">fetch</span> <span class="pre">-a</span></code>.</p>
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+Give your PR a meaningful title and description and check <code class="docutils literal notranslate"><span class="pre">Allow</span> <span class="pre">edits</span> <span class="pre">by</span> <span class="pre">maintainers</span></code> if you want people responsible for the repo your are pulling into to have access to your branch associated with the PR.
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+    <h1>Setting up remotes</h1>
+    <!-- Table of contents -->
+    <div id="print-main-content">
+        <div id="jb-print-toc">
+            
+            <div>
+                <h2> Contents </h2>
+            </div>
+            <nav aria-label="Page">
+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#adding-remotes">Adding remotes</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#checking-out-remote-branches">Checking out remote branches</a></li>
+</ul>
+            </nav>
+        </div>
+    </div>
+</div>
+
+              
+                
+<div id="searchbox"></div>
+                <article class="bd-article">
+                  
+  <section id="setting-up-remotes">
+<h1>Setting up remotes<a class="headerlink" href="#setting-up-remotes" title="Link to this heading">#</a></h1>
+<p>Since we are working with two repositories: your fork and the repository you forked from, you might want to set up your local repo to see them both.
+In order to do that you would have to use terminal even if you use GUI for committing/pushing.</p>
+<p>In git, remotes are repositories somewhere on the server (gitlab/github) that are not present locally on your machine.
+When you clone a repository and create a branch you generally want your branch to track some other branch on one of the remotes (usually with the same name).</p>
+<p>That’s why you need to do <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">push</span> <span class="pre">--set-origin</span> <span class="pre">&lt;remote-name&gt;</span> <span class="pre">&lt;branch-name&gt;</span></code> whe you first push a branch you have created locally with <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">switch</span> <span class="pre">-c</span> <span class="pre">&lt;branch-name&gt;</span></code>.</p>
+<section id="adding-remotes">
+<h2>Adding remotes<a class="headerlink" href="#adding-remotes" title="Link to this heading">#</a></h2>
+<p>Here we will add an <code class="docutils literal notranslate"><span class="pre">upstream</span></code> repository to the clone of your fork.
+Assuming you have cloned your fork and are currently in the folder that contains it. Open a terminal:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>remote<span class="w"> </span>add<span class="w"> </span>upstream<span class="w"> </span>&lt;url-of-the-repo-you-forked-from&gt;
+<span class="c1">#check if the remote is added</span>
+git<span class="w"> </span>remote<span class="w"> </span>-v
+<span class="c1">#get all the branches/tags from newly added remote:</span>
+git<span class="w"> </span>fetch<span class="w"> </span>upstream
+</pre></div>
+</div>
+<p>Now, you have successfully added the upstream remote to your clone.</p>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>If you are using GUI, in the git tab when you click on branches, you will see branches from all the remotes you’ve in your clone <code class="docutils literal notranslate"><span class="pre">remote-name/branch-name</span></code> your locacl branches will not have <code class="docutils literal notranslate"><span class="pre">remote-name/</span></code> prefix.</p>
+</div>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>To update your clone with any changes on the remotes (new branches, tags, commits) you might want to regularly run <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">fetch</span> <span class="pre">--all</span></code> or for a specific remote: <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">fetch</span> <span class="pre">&lt;remote-name&gt;</span></code>.</p>
+</div>
+</section>
+<section id="checking-out-remote-branches">
+<h2>Checking out remote branches<a class="headerlink" href="#checking-out-remote-branches" title="Link to this heading">#</a></h2>
+<p>When you have configured the remotes in your clone you can check out the heads of specific branches from those remotes or make local branches to track remote branches:</p>
+<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1"># this will show you all the remote branches:</span>
+git<span class="w"> </span>branch<span class="w"> </span>-r
+<span class="c1"># to see ALL the branches local/remote:</span>
+git<span class="w"> </span>branch<span class="w"> </span>-v<span class="w"> </span>-a
+<span class="c1"># check out the head of a remote branch</span>
+git<span class="w"> </span>checkout<span class="w"> </span>&lt;remote-name/branch-name&gt;
+<span class="c1"># create a new branch that will originate</span>
+git<span class="w"> </span>switch<span class="w"> </span>-c<span class="w"> </span>&lt;new-branch&gt;<span class="w"> </span><span class="c1"># note, when you push you will need to --set-origin</span>
+<span class="c1"># to create a new local branch that will TRACK already existing remote branch</span>
+git<span class="w"> </span>switch<span class="w"> </span>-c<span class="w"> </span>&lt;branch-name&gt;<span class="w"> </span>&lt;remote-name&gt;/&lt;branch-name&gt;
+
+<span class="c1"># to delete a local branch</span>
+git<span class="w"> </span>-d<span class="w"> </span>&lt;branch-name&gt;
+</pre></div>
+</div>
+<div class="admonition tip">
+<p class="admonition-title">Tip</p>
+<p>If you have local changes and you want to switch/make a new branch you can use <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">stash</span></code> to get to the latest commit of the branch you are on.
+The changes will stay in the stash and you can use it later. To permanently <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">reset</span> <span class="pre">--hard</span></code>.</p>
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+<li class="toctree-l2"><a class="reference internal" href="data/Intake-data-acess/">Acessing model data using intake-esm</a></li>
+<li class="toctree-l2"><a class="reference internal" href="data/local-data/">Local shared data</a></li>
+<li class="toctree-l2"><a class="reference internal" href="data/ACTRIS-data/">ACTRIS data</a></li>
+</ul>
+</li>
+<li class="toctree-l1 has-children"><a class="reference internal" href="learning/">Learning Corner</a><input checked class="toctree-checkbox" id="toctree-checkbox-4" name="toctree-checkbox-4" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-4"><i class="fa-solid fa-chevron-down"></i></label><ul>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/cool_stuff/">Building notebooks directly</a></li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/from_ebas_using_xarray/">Using xarray to read EBAS data</a></li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/masked_and_weighted_average/">Using masks and computing weighted average</a></li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/projections/">Using cartopy and projections for plotting</a></li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/">Some tips with xarray and pandas</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="git_integration/git_jlab/">Starting with git on the jupyterhub</a></li>
+<li class="toctree-l2"><a class="reference internal" href="git_integration/remotes/">Setting up remotes</a></li>
+<li class="toctree-l2"><a class="reference internal" href="git_integration/github-work/">Pull requests and Issues</a></li>
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+    <h1>eScience 2024 course</h1>
+    <!-- Table of contents -->
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+                  
+  <section id="escience-2024-course">
+<h1>eScience 2024 course<a class="headerlink" href="#escience-2024-course" title="Link to this heading">#</a></h1>
+<div class="toctree-wrapper compound">
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="feide/">Jupyterhub access</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="feide/#creating-feide-openidp-account">Creating Feide OpenIdP account:</a></li>
+<li class="toctree-l2"><a class="reference internal" href="feide/#joining-escience2024-feide-group">Joining eScience2024 Feide group:</a></li>
+<li class="toctree-l2"><a class="reference internal" href="feide/#accessing-jupyterhub">Accessing Jupyterhub:</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="course_workflow/">Workflow for eScience2024 course</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="course_workflow/workflow/">Basic setup</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="course_workflow/workflow/#fork-projects-repository">1. Fork projects repository</a></li>
+<li class="toctree-l3"><a class="reference internal" href="course_workflow/workflow/#get-gitgub-access-token">2. Get GitGub Access token</a></li>
+<li class="toctree-l3"><a class="reference internal" href="course_workflow/workflow/#setup-git-and-clone-on-jupyterhub">3. Setup git and clone on jupyterhub</a></li>
+<li class="toctree-l3"><a class="reference internal" href="course_workflow/workflow/#sharing-your-work-within-the-group">4. Sharing your work within the group</a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="course_workflow/rules/">Basic Rules for the course</a></li>
+<li class="toctree-l2"><a class="reference internal" href="course_workflow/data/">Sharing data</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="basics/">Jupyterhub basic usage</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="basics/start_stop/">Starting and stopping your server</a></li>
+<li class="toctree-l2"><a class="reference internal" href="basics/lab/">The JupyterLab Interface</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="basics/lab/#menu-bar">Menu Bar</a></li>
+<li class="toctree-l3"><a class="reference internal" href="basics/lab/#left-sidebar">Left Sidebar</a></li>
+<li class="toctree-l3"><a class="reference internal" href="basics/lab/#tips">Tips</a></li>
+<li class="toctree-l3"><a class="reference internal" href="basics/lab/#create-a-new-python-3-notebook">Create a new python 3 notebook</a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="basics/kernels/">Using different kernels in notebooks</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="basics/kernels/#available-kernels">Available kernels</a></li>
+<li class="toctree-l3"><a class="reference internal" href="basics/kernels/#using-the-conda-environments-outside-of-the-course">Using the conda environments outside of the course</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="data/">Data</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="data/Intake-data-acess/">Acessing model data using intake-esm</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="data/Intake-data-acess/#reading-and-browsing-the-catalog">Reading and browsing the catalog</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="data/Intake-data-acess/#browsing-the-catalog-comparing-the-change-in-aod-over-the-historical-period-across-cmip6-models">Browsing the catalog: Comparing the change in AOD over the historical period across CMIP6 models</a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="data/Intake-data-acess/#loading-the-data-and-plotting">Loading the data and plotting</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="data/Intake-data-acess/#exporting-a-subset-of-the-catalog">Exporting a subset of the catalog</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="data/local-data/">Local shared data</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="data/local-data/#direct-local-data-access">Direct local data access</a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="data/ACTRIS-data/">ACTRIS data</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="data/ACTRIS-data/#access-via-thredds-server-from-nilu">Access via thredds server from NILU</a></li>
+<li class="toctree-l3"><a class="reference internal" href="data/ACTRIS-data/#check-availability-via-actris-web-interface">Check availability via ACTRIS web interface</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="learning/">Learning Corner</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/cool_stuff/">Building notebooks directly</a></li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/from_ebas_using_xarray/">Using xarray to read EBAS data</a></li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/masked_and_weighted_average/">Using masks and computing weighted average</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/masked_and_weighted_average/#import-python-packages">Import python packages</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/masked_and_weighted_average/#search-data">Search data</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/masked_and_weighted_average/#create-dictionary-from-the-list-of-datasets-we-found">Create dictionary from the list of datasets we found</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/masked_and_weighted_average/#compute-weighted-mean">Compute weighted mean</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/masked_and_weighted_average/#compute-weighted-average-over-the-entire-globe">Compute weighted average over the entire globe</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/masked_and_weighted_average/#comparison-with-unweighted-mean">Comparison with unweighted mean</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/masked_and_weighted_average/#compute-weigted-arctic-average">Compute Weigted arctic average</a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/projections/">Using cartopy and projections for plotting</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/projections/#open-era5-dataset">Open ERA5 dataset</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/projections/#reading-and-browsing-the-catalog">Reading and browsing the catalog</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/projections/#browsing-the-catalog-compering-the-change-in-aod-over-the-historical-period-across-cmip6-models">Browsing the catalog: Compering the change in AOD over the historical period across CMIP6 models</a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/projections/#get-metadata">Get metadata</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/projections/#get-variable-metadata-air-temperature-at-2-metres">Get variable metadata (air_temperature_at_2_metres)</a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/projections/#select-time">Select time</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/projections/#visualize-data">Visualize data</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/projections/#simple-visualization-from-xarray-plotting-method">Simple visualization from xarray plotting method</a><ul>
+<li class="toctree-l5"><a class="reference internal" href="learning/notebooks/projections/#same-plot-but-with-local-file">Same plot but with local file</a></li>
+</ul>
+</li>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/projections/#customize-plot">Customize plot</a><ul>
+<li class="toctree-l5"><a class="reference internal" href="learning/notebooks/projections/#set-the-size-of-the-figure-and-add-coastlines">Set the size of the figure and add coastlines</a></li>
+<li class="toctree-l5"><a class="reference internal" href="learning/notebooks/projections/#change-plotting-projection">Change plotting projection</a></li>
+<li class="toctree-l5"><a class="reference internal" href="learning/notebooks/projections/#choose-extent-of-values">Choose extent of values</a></li>
+</ul>
+</li>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/projections/#combine-plots-with-different-projections">Combine plots with different projections</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/">Some tips with xarray and pandas</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#print-hey-world">print(‘Hey world’)</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#what-are-pandas-and-xarray">What are pandas and xarray?</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#pandas">Pandas</a></li>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#xarray">Xarray</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#read-in-cmip6-data-we-will-skip-this-next-part-but-you-can-check-it-later-to-read-data">1. Read in CMIP6 data: We will skip this next part, but you can check it later to read data:</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#import-python-packages">Import python packages</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#open-cmip6-online-catalog">Open CMIP6 online catalog</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#search-corresponding-data">Search corresponding data</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#create-dictionary-from-the-list-of-datasets-we-found">Create dictionary from the list of datasets we found</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#open-dataset">Open dataset</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#reading-in-the-data-from-file">1.1 Reading in the data from file:</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#opening-multiple-files">Opening multiple files:</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#check-how-your-dataset-looks">2. Check how your dataset looks</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#different-types-of-information-data">Different types of information/data:</a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#sometimes-we-want-to-do-some-nice-tweaks-before-we-start">3. Sometimes we want to do some nice tweaks before we start:</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#selecting-data-and-super-quick-plotting">Selecting data and super quick plotting:</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#see-here-for-nice-overview">See here for nice overview</a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#slice-in-time-the-sel-method">Slice in time: the sel method</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#isel-sel-index-selecting">isel, sel: index selecting</a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#calculates-variables-and-assign-attributes">3.2 Calculates variables and assign attributes!</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#convert-longitude">3.3 Convert longitude:</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#the-easiest-interpolation-select-with-nearest-neighboor">4. The easiest interpolation: select with ‘nearest’ neighboor</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#super-quick-averaging-etc">Super quick averaging etc</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#mask-data-and-groupby-pick-out-seasons">Mask data and groupby: pick out seasons</a></li>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#controle-the-plot-visuals">Controle the plot visuals:</a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#plotting-with-cartopy">5. Plotting with cartopy</a></li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#global-average-weighted-means">6. Global average: weighted means!</a></li>
+<li class="toctree-l2"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#convert-to-pandas-do-some-random-fun-stuff">7. Convert to pandas &amp; do some random fun stuff:</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#pick-out-station">Pick out station:</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#resample">Resample:</a></li>
+<li class="toctree-l4"><a class="reference internal" href="learning/notebooks/some-xarray-pandas-presentation_Sara/#lets-do-something-unnecesarily-complicated-d">lets do something unnecesarily complicated :D</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="notebooks/masked_and_weighted_average/">Using masks and computing weighted average</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/projections/">Using cartopy and projections for plotting</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/some-xarray-pandas-presentation_Sara/">Some tips with xarray and pandas</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/some-xarray-pandas-presentation_Sara/#read-in-cmip6-data-we-will-skip-this-next-part-but-you-can-check-it-later-to-read-data">1. Read in CMIP6 data: We will skip this next part, but you can check it later to read data:</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/some-xarray-pandas-presentation_Sara/#check-how-your-dataset-looks">2. Check how your dataset looks</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/some-xarray-pandas-presentation_Sara/#sometimes-we-want-to-do-some-nice-tweaks-before-we-start">3. Sometimes we want to do some nice tweaks before we start:</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/some-xarray-pandas-presentation_Sara/#the-easiest-interpolation-select-with-nearest-neighboor">4. The easiest interpolation: select with ‘nearest’ neighboor</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/some-xarray-pandas-presentation_Sara/#plotting-with-cartopy">5. Plotting with cartopy</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/some-xarray-pandas-presentation_Sara/#global-average-weighted-means">6. Global average: weighted means!</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks/some-xarray-pandas-presentation_Sara/#convert-to-pandas-do-some-random-fun-stuff">7. Convert to pandas &amp; do some random fun stuff:</a></li>
+<li class="toctree-l1"><a class="reference internal" href="us-links/">Useful links</a></li>
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+    <h1>Using xarray to read EBAS data</h1>
+    <!-- Table of contents -->
+    <div id="print-main-content">
+        <div id="jb-print-toc">
+            
+        </div>
+    </div>
+</div>
+
+              
+                
+<div id="searchbox"></div>
+                <article class="bd-article">
+                  
+  <section id="using-xarray-to-read-ebas-data">
+<h1>Using xarray to read EBAS data<a class="headerlink" href="#using-xarray-to-read-ebas-data" title="Link to this heading">#</a></h1>
+<p>See more at http://ebas.nilu.no/
+and https://ebas.nilu.no/thredds/</p>
+<p>requirements
+pip install threddsclient</p>
+<p>The EBAS database collects observational data on atmospheric chemical composition and physical properties from a variety of national and international research projects and monitoring programs, such as ACTRIS, AMAP, EMEP, GAW and HELCOM, as well as for the Norwegian monitoring programs funded by the Norwegian Environment Agency, the Ministry of Climate and Environment and NILU – Norwegian Institute for Air Research.</p>
+<p>See all files available:
+https://thredds.nilu.no/thredds/catalog/ebas/catalog.html</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># You need to first install threddsclient:</span>
+<span class="c1"># remember to do in terminal pip install threddsclient</span>
+<span class="kn">import</span> <span class="nn">threddsclient</span>
+<span class="kn">import</span> <span class="nn">xarray</span> <span class="k">as</span> <span class="nn">xr</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Find url addresses for files on EBAS</span>
+
+<span class="n">all_opendap_urls</span> <span class="o">=</span> <span class="n">threddsclient</span><span class="o">.</span><span class="n">opendap_urls</span><span class="p">(</span>
+<span class="s1">&#39;https://thredds.nilu.no/thredds/catalog/ebas/catalog.xml&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#Example 1 nephelometer scattering coefficient data</span>
+<span class="c1"># get all data urls for one station, e.g., Zeppelin NO0042G</span>
+<span class="n">opendap_urls</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">all_opendap_urls</span> <span class="k">if</span> <span class="s1">&#39;NO0042G&#39;</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]</span>
+<span class="c1"># get all scattering data urls</span>
+<span class="n">opendap_urls</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">opendap_urls</span> <span class="k">if</span> <span class="s1">&#39;nephelometer&#39;</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]</span>
+
+<span class="n">opendap_urls</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20100101000000.20150216111241.nephelometer..pm10.4y.1h.SE02L_TSI_3563_ZEP_dry.SE02L_scat_coef.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20080708135939.20181213000000.nephelometer..aerosol_humidified.3mo.6h.CH02L_TSI_3563_ZEP_ref+TSI_3563_ZEP_wet.CH02L_hygro_tandem_neph_CorrData.lev2.nc&#39;]
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># read multiple files</span>
+<span class="c1"># the problem with this example is, </span>
+<span class="c1">#    that the files are from different instruments</span>
+<span class="c1">#    thus, they need to be treated and digested one by one.</span>
+
+<span class="n">dsmf</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">open_mfdataset</span><span class="p">(</span><span class="n">opendap_urls</span><span class="p">)</span>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 66MB
+Dimensions:                                                         (
+                                                                     time: 35451,
+                                                                     metadata_time: 5,
+                                                                     Wavelength: 3,
+                                                                     RH_base: 1,
+                                                                     RH_humidified: 1,
+                                                                     ...
+                                                                     aerosol_light_scattering_coefficient_prec1587_qc_flags: 2,
+                                                                     aerosol_light_scattering_coefficient_perc8413_qc_flags: 2,
+                                                                     pressure_qc_flags: 2,
+                                                                     aerosol_light_backscattering_coefficient_prec1587_qc_flags: 2,
+                                                                     aerosol_light_backscattering_coefficient_amean_qc_flags: 2,
+                                                                     aerosol_light_backscattering_coefficient_perc8413_qc_flags: 2)
+Coordinates:
+  * time                                                            (time) datetime64[ns] 284kB ...
+  * metadata_time                                                   (metadata_time) datetime64[ns] 40B ...
+  * Wavelength                                                      (Wavelength) float64 24B ...
+  * RH_base                                                         (RH_base) float64 8B ...
+  * RH_humidified                                                   (RH_humidified) float64 8B ...
+  * RH_base_max                                                     (RH_base_max) float64 8B ...
+  * RH                                                              (RH) float64 104B ...
+  * Location                                                        (Location) |S64 64B ...
+Dimensions without coordinates: tbnds,
+                                aerosol_light_scattering_enhancement_factor_qc_flags,
+                                aerosol_light_backscattering_coefficient_qc_flags,
+                                aerosol_light_backscattering_enhancement_factor_qc_flags,
+                                aerosol_light_scattering_coefficient_qc_flags,
+                                temperature_qc_flags,
+                                ...
+                                aerosol_light_scattering_coefficient_prec1587_qc_flags,
+                                aerosol_light_scattering_coefficient_perc8413_qc_flags,
+                                pressure_qc_flags,
+                                aerosol_light_backscattering_coefficient_prec1587_qc_flags,
+                                aerosol_light_backscattering_coefficient_amean_qc_flags,
+                                aerosol_light_backscattering_coefficient_perc8413_qc_flags
+Data variables: (12/41)
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+    aerosol_light_backscattering_enhancement_factor_ebasmetadata    (Wavelength, RH_base_max, RH_humidified, metadata_time) object 120B dask.array&lt;chunksize=(3, 1, 1, 5), meta=np.ndarray&gt;
+    aerosol_light_scattering_enhancement_factor_ebasmetadata        (Wavelength, RH_base, RH_humidified, metadata_time) object 120B dask.array&lt;chunksize=(3, 1, 1, 5), meta=np.ndarray&gt;
+    aerosol_light_backscattering_coefficient_qc                     (Wavelength, RH, aerosol_light_backscattering_coefficient_qc_flags, time) float64 11MB dask.array&lt;chunksize=(3, 13, 1, 35451), meta=np.ndarray&gt;
+    ...                                                              ...
+    aerosol_light_scattering_coefficient_prec1587                   (Wavelength, time) float64 851kB dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;
+    pressure                                                        (Location, time) float64 284kB dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;
+    aerosol_light_backscattering_coefficient_amean                  (Wavelength, time) float64 851kB dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;
+    aerosol_light_scattering_coefficient_perc8413                   (Wavelength, time) float64 851kB dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;
+    relative_humidity                                               (Location, time) float64 284kB dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;
+    aerosol_light_backscattering_coefficient_prec1587               (Wavelength, time) float64 851kB dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;
+Attributes: (12/47)
+    Conventions:                   CF-1.7, ACDD-1.3
+    featureType:                   timeSeries
+    title:                         Ground based in situ observations of nephe...
+    keywords:                      NO0042G, Zeppelin mountain (Ny-Ålesund), a...
+    id:                            NO0042G.20080708135939.20181213000000.neph...
+    naming_authority:              EBAS
+    ...                            ...
+    geospatial_lat_units:          degrees_north
+    geospatial_lon_units:          degrees_east
+    comment:                       {\n    &quot;Data definition&quot;: &quot;EBAS_1.1&quot;, \n  ...
+    standard_name_vocabulary:      CF-1.7, ACDD-1.3
+    history:                       None
+    creator_url:                   ebas.nilu.no</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c02cbbce-4e9a-4108-a726-50340ee56de0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c02cbbce-4e9a-4108-a726-50340ee56de0' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 35451</li><li><span class='xr-has-index'>metadata_time</span>: 5</li><li><span class='xr-has-index'>Wavelength</span>: 3</li><li><span class='xr-has-index'>RH_base</span>: 1</li><li><span class='xr-has-index'>RH_humidified</span>: 1</li><li><span class='xr-has-index'>RH_base_max</span>: 1</li><li><span class='xr-has-index'>RH</span>: 13</li><li><span>tbnds</span>: 2</li><li><span>aerosol_light_scattering_enhancement_factor_qc_flags</span>: 1</li><li><span>aerosol_light_backscattering_coefficient_qc_flags</span>: 1</li><li><span>aerosol_light_backscattering_enhancement_factor_qc_flags</span>: 1</li><li><span>aerosol_light_scattering_coefficient_qc_flags</span>: 1</li><li><span class='xr-has-index'>Location</span>: 1</li><li><span>temperature_qc_flags</span>: 2</li><li><span>relative_humidity_qc_flags</span>: 2</li><li><span>aerosol_light_scattering_coefficient_amean_qc_flags</span>: 2</li><li><span>aerosol_light_scattering_coefficient_prec1587_qc_flags</span>: 2</li><li><span>aerosol_light_scattering_coefficient_perc8413_qc_flags</span>: 2</li><li><span>pressure_qc_flags</span>: 2</li><li><span>aerosol_light_backscattering_coefficient_prec1587_qc_flags</span>: 2</li><li><span>aerosol_light_backscattering_coefficient_amean_qc_flags</span>: 2</li><li><span>aerosol_light_backscattering_coefficient_perc8413_qc_flags</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8c49fe42-f5e8-4e92-bbd8-43b971accd7c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8c49fe42-f5e8-4e92-bbd8-43b971accd7c' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2008-07-08T16:59:38.999999488 .....</div><input id='attrs-283ad786-e890-487b-a235-6ed7647466d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-283ad786-e890-487b-a235-6ed7647466d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f46b4a2d-8edf-4681-97bc-6128766d4002' class='xr-var-data-in' type='checkbox'><label for='data-f46b4a2d-8edf-4681-97bc-6128766d4002' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time of measurement</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>cell_methods :</span></dt><dd>mean</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2008-07-08T16:59:38.999999488&#x27;, &#x27;2008-07-08T22:59:38.999999488&#x27;,
+       &#x27;2008-07-09T04:59:38.999999488&#x27;, ..., &#x27;2013-12-31T21:30:00.000000000&#x27;,
+       &#x27;2013-12-31T22:29:59.000000000&#x27;, &#x27;2013-12-31T23:29:59.000000000&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>metadata_time</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2008-08-25T22:59:38.999999488 .....</div><input id='attrs-e2e7c8c8-bbf9-4852-9bb5-9b3048ccc837' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2e7c8c8-bbf9-4852-9bb5-9b3048ccc837' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb4c4b6d-d640-46bd-85db-7ab53a7d1d6c' class='xr-var-data-in' type='checkbox'><label for='data-eb4c4b6d-d640-46bd-85db-7ab53a7d1d6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time of ebas metadata intervals</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>metadata_time_bnds</dd><dt><span>cell_methods :</span></dt><dd>mean</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2008-08-25T22:59:38.999999488&#x27;, &#x27;2010-07-02T12:00:00.000000000&#x27;,
+       &#x27;2011-07-02T12:00:00.000000000&#x27;, &#x27;2012-07-02T00:00:00.000000000&#x27;,
+       &#x27;2013-07-02T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Wavelength</span></div><div class='xr-var-dims'>(Wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>450.0 550.0 700.0</div><input id='attrs-c0f2f27b-ba68-47ea-b4e9-75caec7955b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0f2f27b-ba68-47ea-b4e9-75caec7955b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b63ef43-48fc-4ae1-b3c9-a7f2c47c33ba' class='xr-var-data-in' type='checkbox'><label for='data-1b63ef43-48fc-4ae1-b3c9-a7f2c47c33ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([450., 550., 700.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>RH_base</span></div><div class='xr-var-dims'>(RH_base)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0</div><input id='attrs-cf63a8ff-a245-4f7a-8153-4c43f3d29455' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf63a8ff-a245-4f7a-8153-4c43f3d29455' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c987b0b-3d06-467c-a868-621f28edb13e' class='xr-var-data-in' type='checkbox'><label for='data-4c987b0b-3d06-467c-a868-621f28edb13e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([40.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>RH_humidified</span></div><div class='xr-var-dims'>(RH_humidified)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>85.0</div><input id='attrs-056a30b6-eaf1-46ac-a1b6-a34f79ff2be4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-056a30b6-eaf1-46ac-a1b6-a34f79ff2be4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc8400de-ab8e-4075-8ab1-965eaea827ba' class='xr-var-data-in' type='checkbox'><label for='data-dc8400de-ab8e-4075-8ab1-965eaea827ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([85.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>RH_base_max</span></div><div class='xr-var-dims'>(RH_base_max)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0</div><input id='attrs-52e744d5-b350-4507-b7cc-dbdec1df08c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52e744d5-b350-4507-b7cc-dbdec1df08c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-318afd66-20c8-4c53-8e82-1629184c6770' class='xr-var-data-in' type='checkbox'><label for='data-318afd66-20c8-4c53-8e82-1629184c6770' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([40.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>RH</span></div><div class='xr-var-dims'>(RH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>30.0 35.0 40.0 ... 80.0 85.0 90.0</div><input id='attrs-7500a61c-7a72-4490-abe0-2c3693d33872' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7500a61c-7a72-4490-abe0-2c3693d33872' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93f67cd3-e536-4c5d-8d3a-79dad3c26c2c' class='xr-var-data-in' type='checkbox'><label for='data-93f67cd3-e536-4c5d-8d3a-79dad3c26c2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([30., 35., 40., 45., 50., 55., 60., 65., 70., 75., 80., 85., 90.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Location</span></div><div class='xr-var-dims'>(Location)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>b&#x27;instrument internal&#x27;</div><input id='attrs-3353dfe7-2f0d-4fbd-8af1-7b9c008f905e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3353dfe7-2f0d-4fbd-8af1-7b9c008f905e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdb6a5a9-e12e-4cf2-8cf1-bec7b7061928' class='xr-var-data-in' type='checkbox'><label for='data-fdb6a5a9-e12e-4cf2-8cf1-bec7b7061928' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([b&#x27;instrument internal&#x27;], dtype=&#x27;|S64&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e1cd6f9e-dca1-4ef3-8e84-661919955dd7' class='xr-section-summary-in' type='checkbox'  ><label for='section-e1cd6f9e-dca1-4ef3-8e84-661919955dd7' class='xr-section-summary' >Data variables: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, tbnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(35451, 2), meta=np.ndarray&gt;</div><input id='attrs-b48ab23b-e2ec-4319-b8ac-24f283fc43ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b48ab23b-e2ec-4319-b8ac-24f283fc43ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a03aabf-db15-4b99-9632-fbb19ed5233c' class='xr-var-data-in' type='checkbox'><label for='data-6a03aabf-db15-4b99-9632-fbb19ed5233c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time bounds for measurement</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 553.92 kiB </td>
+                        <td> 553.92 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (35451, 2) </td>
+                        <td> (35451, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> datetime64[ns] numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
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+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">35451</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>metadata_time_bnds</span></div><div class='xr-var-dims'>(metadata_time, tbnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(5, 2), meta=np.ndarray&gt;</div><input id='attrs-75019dac-2b7d-4e51-91d9-cc6b7e93b8b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75019dac-2b7d-4e51-91d9-cc6b7e93b8b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52b12302-e706-40ab-9759-5a0040691ceb' class='xr-var-data-in' type='checkbox'><label for='data-52b12302-e706-40ab-9759-5a0040691ceb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time bounds for ebas metadata intervals</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 80 B </td>
+                        <td> 80 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (5, 2) </td>
+                        <td> (5, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> datetime64[ns] numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="98" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="48" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="48" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="48" y1="0" x2="48" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 48.0,0.0 48.0,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="24.000000" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="68.000000" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,68.000000,60.000000)">5</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_enhancement_factor_qc</span></div><div class='xr-var-dims'>(Wavelength, RH_base, RH_humidified, aerosol_light_scattering_enhancement_factor_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 1, 1, 1, 35451), meta=np.ndarray&gt;</div><input id='attrs-29e01cfe-14d9-4cdd-a113-af2b2d17c435' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29e01cfe-14d9-4cdd-a113-af2b2d17c435' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ce00c2a-6e4b-4c9d-a8bc-cdf13b0b636e' class='xr-var-data-in' type='checkbox'><label for='data-4ce00c2a-6e4b-4c9d-a8bc-cdf13b0b636e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
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+                    <tr>
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+                        <td> 830.88 kiB </td>
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+                        <td> (3, 1, 1, 35451) </td>
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+    </tr>
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+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
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+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 120 B </td>
+                        <td> 120 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 5) </td>
+                        <td> (3, 5) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 11 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
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+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
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+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
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+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 553.92 kiB </td>
+                        <td> 553.92 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 2, 35451) </td>
+                        <td> (1, 2, 35451) </td>
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+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>relative_humidity_qc</span></div><div class='xr-var-dims'>(Location, relative_humidity_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-2be2c242-b162-4fa7-bbd1-64f8302c9174' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2be2c242-b162-4fa7-bbd1-64f8302c9174' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31c798ec-bfdb-45da-86fe-e748cac8784e' class='xr-var-data-in' type='checkbox'><label for='data-31c798ec-bfdb-45da-86fe-e748cac8784e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 553.92 kiB </td>
+                        <td> 553.92 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 2, 35451) </td>
+                        <td> (1, 2, 35451) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_prec1587_ebasmetadata</span></div><div class='xr-var-dims'>(Wavelength, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 5), meta=np.ndarray&gt;</div><input id='attrs-6d220f77-eb96-4b48-9dbe-1d0dbe1a4bee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d220f77-eb96-4b48-9dbe-1d0dbe1a4bee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3355aa8-7493-4d18-a3be-5e71bf88080b' class='xr-var-data-in' type='checkbox'><label for='data-e3355aa8-7493-4d18-a3be-5e71bf88080b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 120 B </td>
+                        <td> 120 B </td>
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+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 5) </td>
+                        <td> (3, 5) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 11 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_amean_qc</span></div><div class='xr-var-dims'>(Wavelength, aerosol_light_scattering_coefficient_amean_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-1f139e95-6758-4d13-bbe2-2241094f04d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f139e95-6758-4d13-bbe2-2241094f04d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45d964b2-8935-4450-8dfa-fbd9b9aa9719' class='xr-var-data-in' type='checkbox'><label for='data-45d964b2-8935-4450-8dfa-fbd9b9aa9719' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
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+                        <th> Chunk </th>
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+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 1.62 MiB </td>
+                        <td> 1.62 MiB </td>
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+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 2, 35451) </td>
+                        <td> (3, 2, 35451) </td>
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+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
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+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
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+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 120 B </td>
+                        <td> 120 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 5) </td>
+                        <td> (3, 5) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 11 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
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+    <tr>
+        <td>
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+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 120 B </td>
+                        <td> 120 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 5) </td>
+                        <td> (3, 5) </td>
+                    </tr>
+                    <tr>
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+                        <td colspan="2"> 1 chunks in 11 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
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+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 40 B </td>
+                        <td> 40 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 5) </td>
+                        <td> (1, 5) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 11 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
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+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
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+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 40 B </td>
+                        <td> 40 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 5) </td>
+                        <td> (1, 5) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 11 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
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+                </tbody>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_prec1587_qc</span></div><div class='xr-var-dims'>(Wavelength, aerosol_light_scattering_coefficient_prec1587_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-dc1b74b0-9a80-4620-ae12-1af6cc0a7558' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc1b74b0-9a80-4620-ae12-1af6cc0a7558' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f994696-51ae-4178-b6d0-32c3f2577c40' class='xr-var-data-in' type='checkbox'><label for='data-9f994696-51ae-4178-b6d0-32c3f2577c40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
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+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 1.62 MiB </td>
+                        <td> 1.62 MiB </td>
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+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 2, 35451) </td>
+                        <td> (3, 2, 35451) </td>
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+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
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+                        <th> Data type </th>
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+        </td>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_perc8413_qc</span></div><div class='xr-var-dims'>(Wavelength, aerosol_light_scattering_coefficient_perc8413_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-e9e68502-c5eb-4b3d-8b47-d6e53a277645' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9e68502-c5eb-4b3d-8b47-d6e53a277645' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b63ad800-90cf-445f-9103-749a3d7fa3e0' class='xr-var-data-in' type='checkbox'><label for='data-b63ad800-90cf-445f-9103-749a3d7fa3e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>
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+            <table style="border-collapse: collapse;">
+                <thead>
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+                <tbody>
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+                    <tr>
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+                        <td> 1.62 MiB </td>
+                        <td> 1.62 MiB </td>
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+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 2, 35451) </td>
+                        <td> (3, 2, 35451) </td>
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+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
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+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_qc</span></div><div class='xr-var-dims'>(Location, pressure_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2, 35451), meta=np.ndarray&gt;</div><input id='attrs-81bcdb3d-54d6-411e-8342-bccdb9e7b67c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81bcdb3d-54d6-411e-8342-bccdb9e7b67c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fafc84a-0864-4e6d-bd9f-c047b72228e4' class='xr-var-data-in' type='checkbox'><label for='data-0fafc84a-0864-4e6d-bd9f-c047b72228e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
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+                        <th> Chunk </th>
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+                <tbody>
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+                    <tr>
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+                        <td> 120 B </td>
+                        <td> 120 B </td>
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+                    
+                    <tr>
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+                        <td> (3, 5) </td>
+                        <td> (3, 5) </td>
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+                        <td> 1.62 MiB </td>
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+                    <tr>
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+                        <td> 1.62 MiB </td>
+                        <td> 1.62 MiB </td>
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+                        <td> (3, 2, 35451) </td>
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+                        <td> 120 B </td>
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+                        <td> (3, 5) </td>
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+                        <td> 1.62 MiB </td>
+                        <td> 1.62 MiB </td>
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+                        <td> (3, 2, 35451) </td>
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+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>relative_humidity_ebasmetadata</span></div><div class='xr-var-dims'>(Location, metadata_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;</div><input id='attrs-761aa528-6b56-4da3-8751-b0413b8d6cf0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-761aa528-6b56-4da3-8751-b0413b8d6cf0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c37cf06-2f97-450d-89c2-739a699d16ba' class='xr-var-data-in' type='checkbox'><label for='data-7c37cf06-2f97-450d-89c2-739a699d16ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
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+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 40 B </td>
+                        <td> 40 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 5) </td>
+                        <td> (1, 5) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 11 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
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+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_perc8413</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-ca70ed6d-874b-4585-8581-ead4a681eb67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca70ed6d-874b-4585-8581-ead4a681eb67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3ac19f5-b6b2-4d6f-951f-95a576008170' class='xr-var-data-in' type='checkbox'><label for='data-e3ac19f5-b6b2-4d6f-951f-95a576008170' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_backscattering_coefficient_perc8413_qc aerosol_light_backscattering_coefficient_perc8413_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: percentile:84.13</dd></dl></div><div class='xr-var-data'><table>
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+                        <th> Chunk </th>
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+                    <tr>
+                        <th> Bytes </th>
+                        <td> 830.88 kiB </td>
+                        <td> 830.88 kiB </td>
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+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 35451) </td>
+                        <td> (3, 35451) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
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+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_amean</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-9372dba9-44ed-4669-b2c8-475b0b1b8aff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9372dba9-44ed-4669-b2c8-475b0b1b8aff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6e31db7-871b-4b91-a7cf-c41cee07f675' class='xr-var-data-in' type='checkbox'><label for='data-e6e31db7-871b-4b91-a7cf-c41cee07f675' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_scattering_coefficient_amean_qc aerosol_light_scattering_coefficient_amean_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 830.88 kiB </td>
+                        <td> 830.88 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 35451) </td>
+                        <td> (3, 35451) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
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+                </tbody>
+            </table>
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+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(Location, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;</div><input id='attrs-d9f780da-bd0b-4125-917f-d4ae2066c22a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9f780da-bd0b-4125-917f-d4ae2066c22a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e971cee-ac7a-4ae8-8b2d-c2f539fd4530' class='xr-var-data-in' type='checkbox'><label for='data-4e971cee-ac7a-4ae8-8b2d-c2f539fd4530' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>ancillary_variables :</span></dt><dd>temperature_qc temperature_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 276.96 kiB </td>
+                        <td> 276.96 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 35451) </td>
+                        <td> (1, 35451) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
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+                </tbody>
+            </table>
+        </td>
+        <td>
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+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_prec1587</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-dd4619a3-e54d-4639-98dd-7ddf53fc74eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd4619a3-e54d-4639-98dd-7ddf53fc74eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d286f9c1-105a-430f-a7bc-f1a3922aad45' class='xr-var-data-in' type='checkbox'><label for='data-d286f9c1-105a-430f-a7bc-f1a3922aad45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_scattering_coefficient_prec1587_qc aerosol_light_scattering_coefficient_prec1587_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: percentile:15.87</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
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+                        <th> Array </th>
+                        <th> Chunk </th>
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+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 830.88 kiB </td>
+                        <td> 830.88 kiB </td>
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+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 35451) </td>
+                        <td> (3, 35451) </td>
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+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
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+                </tbody>
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+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(Location, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;</div><input id='attrs-ba2eed54-f197-4c8e-91fd-8f017d4c131a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba2eed54-f197-4c8e-91fd-8f017d4c131a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-676ba34a-41b6-4e55-a33b-fe265a1329f4' class='xr-var-data-in' type='checkbox'><label for='data-676ba34a-41b6-4e55-a33b-fe265a1329f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd><dt><span>ancillary_variables :</span></dt><dd>pressure_qc pressure_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
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+                <tbody>
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+                    <tr>
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+                        <td> 276.96 kiB </td>
+                        <td> 276.96 kiB </td>
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+                        <td> (1, 35451) </td>
+                        <td> (1, 35451) </td>
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+                    <tr>
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+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_amean</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-e13c66c6-34c5-446c-82bf-0d97e796deb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e13c66c6-34c5-446c-82bf-0d97e796deb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b747a934-cdf1-404f-8108-f83d1f4762c7' class='xr-var-data-in' type='checkbox'><label for='data-b747a934-cdf1-404f-8108-f83d1f4762c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_backscattering_coefficient_amean_qc aerosol_light_backscattering_coefficient_amean_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 830.88 kiB </td>
+                        <td> 830.88 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 35451) </td>
+                        <td> (3, 35451) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="75" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="120" y2="25" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="25" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="25" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="45.412617" font-size="1.0rem" font-weight="100" text-anchor="middle" >35451</text>
+  <text x="140.000000" y="12.706308" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,12.706308)">3</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_scattering_coefficient_perc8413</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-75b31c65-7500-4126-93cd-f15fbc84ac0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75b31c65-7500-4126-93cd-f15fbc84ac0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dffccd5-1502-4246-abd8-9440099f96ba' class='xr-var-data-in' type='checkbox'><label for='data-0dffccd5-1502-4246-abd8-9440099f96ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_scattering_coefficient_perc8413_qc aerosol_light_scattering_coefficient_perc8413_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: percentile:84.13</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 830.88 kiB </td>
+                        <td> 830.88 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 35451) </td>
+                        <td> (3, 35451) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="75" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="120" y2="25" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="25" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="25" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="45.412617" font-size="1.0rem" font-weight="100" text-anchor="middle" >35451</text>
+  <text x="140.000000" y="12.706308" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,12.706308)">3</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>relative_humidity</span></div><div class='xr-var-dims'>(Location, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 35451), meta=np.ndarray&gt;</div><input id='attrs-15a1750d-08e7-43da-9274-a7550e277189' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15a1750d-08e7-43da-9274-a7550e277189' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ea3b871-b2a8-4ebb-9492-612a35e5d909' class='xr-var-data-in' type='checkbox'><label for='data-3ea3b871-b2a8-4ebb-9492-612a35e5d909' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>ancillary_variables :</span></dt><dd>relative_humidity_qc relative_humidity_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 276.96 kiB </td>
+                        <td> 276.96 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 35451) </td>
+                        <td> (1, 35451) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="75" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="120" y2="25" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="25" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="25" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="45.412617" font-size="1.0rem" font-weight="100" text-anchor="middle" >35451</text>
+  <text x="140.000000" y="12.706308" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,12.706308)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aerosol_light_backscattering_coefficient_prec1587</span></div><div class='xr-var-dims'>(Wavelength, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 35451), meta=np.ndarray&gt;</div><input id='attrs-7c7bb327-0609-4e12-87be-5a78a0e59c4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c7bb327-0609-4e12-87be-5a78a0e59c4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e856bc0-c65c-407d-b431-57ef5144a241' class='xr-var-data-in' type='checkbox'><label for='data-6e856bc0-c65c-407d-b431-57ef5144a241' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1/Mm</dd><dt><span>ancillary_variables :</span></dt><dd>aerosol_light_backscattering_coefficient_prec1587_qc aerosol_light_backscattering_coefficient_prec1587_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: percentile:15.87</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 830.88 kiB </td>
+                        <td> 830.88 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (3, 35451) </td>
+                        <td> (3, 35451) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="75" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="120" y2="25" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="25" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="25" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="45.412617" font-size="1.0rem" font-weight="100" text-anchor="middle" >35451</text>
+  <text x="140.000000" y="12.706308" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,12.706308)">3</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6caddc14-68e2-437e-bf22-f07defea4817' class='xr-section-summary-in' type='checkbox'  ><label for='section-6caddc14-68e2-437e-bf22-f07defea4817' class='xr-section-summary' >Indexes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d6b3c699-826a-42d4-8e3a-73b6a89d8714' class='xr-index-data-in' type='checkbox'/><label for='index-d6b3c699-826a-42d4-8e3a-73b6a89d8714' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2008-07-08 16:59:38.999999488&#x27;,
+               &#x27;2008-07-08 22:59:38.999999488&#x27;,
+               &#x27;2008-07-09 04:59:38.999999488&#x27;,
+               &#x27;2008-07-09 10:59:38.999999488&#x27;,
+               &#x27;2008-07-09 16:59:38.999999488&#x27;,
+               &#x27;2008-07-09 22:59:38.999999488&#x27;,
+               &#x27;2008-07-10 04:59:38.999999488&#x27;,
+               &#x27;2008-07-10 10:59:38.999999488&#x27;,
+               &#x27;2008-07-10 16:59:38.999999488&#x27;,
+               &#x27;2008-07-10 22:59:38.999999488&#x27;,
+               ...
+                         &#x27;2013-12-31 14:29:59&#x27;,
+                         &#x27;2013-12-31 15:30:00&#x27;,
+                         &#x27;2013-12-31 16:29:59&#x27;,
+                         &#x27;2013-12-31 17:29:59&#x27;,
+                         &#x27;2013-12-31 18:30:00&#x27;,
+                         &#x27;2013-12-31 19:29:59&#x27;,
+                         &#x27;2013-12-31 20:29:59&#x27;,
+                         &#x27;2013-12-31 21:30:00&#x27;,
+                         &#x27;2013-12-31 22:29:59&#x27;,
+                         &#x27;2013-12-31 23:29:59&#x27;],
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=35451, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>metadata_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-da030b04-28f0-4385-858f-c639acb357e2' class='xr-index-data-in' type='checkbox'/><label for='index-da030b04-28f0-4385-858f-c639acb357e2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2008-08-25 22:59:38.999999488&#x27;,
+                         &#x27;2010-07-02 12:00:00&#x27;,
+                         &#x27;2011-07-02 12:00:00&#x27;,
+                         &#x27;2012-07-02 00:00:00&#x27;,
+                         &#x27;2013-07-02 12:00:00&#x27;],
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;metadata_time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>Wavelength</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-58008ea5-7bf4-4357-b849-5fbcc866a308' class='xr-index-data-in' type='checkbox'/><label for='index-58008ea5-7bf4-4357-b849-5fbcc866a308' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([450.0, 550.0, 700.0], dtype=&#x27;float64&#x27;, name=&#x27;Wavelength&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>RH_base</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bca85a7c-9d4c-4792-97be-e139ac2a318c' class='xr-index-data-in' type='checkbox'/><label for='index-bca85a7c-9d4c-4792-97be-e139ac2a318c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([40.0], dtype=&#x27;float64&#x27;, name=&#x27;RH_base&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>RH_humidified</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3eafcd23-5bc0-4384-81c7-c9d7960f6cba' class='xr-index-data-in' type='checkbox'/><label for='index-3eafcd23-5bc0-4384-81c7-c9d7960f6cba' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([85.0], dtype=&#x27;float64&#x27;, name=&#x27;RH_humidified&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>RH_base_max</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0148ea02-fe96-4bc2-9fcb-8efcd6c7c194' class='xr-index-data-in' type='checkbox'/><label for='index-0148ea02-fe96-4bc2-9fcb-8efcd6c7c194' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([40.0], dtype=&#x27;float64&#x27;, name=&#x27;RH_base_max&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>RH</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f8cefb99-30a3-4b8b-b582-b64ce092e544' class='xr-index-data-in' type='checkbox'/><label for='index-f8cefb99-30a3-4b8b-b582-b64ce092e544' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0,
+       90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;RH&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>Location</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-821bd459-6a7a-4a64-9c4f-39428ee8323f' class='xr-index-data-in' type='checkbox'/><label for='index-821bd459-6a7a-4a64-9c4f-39428ee8323f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([b&#x27;instrument internal&#x27;], dtype=&#x27;object&#x27;, name=&#x27;Location&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f789336-5d98-4d64-960e-a6883fdfc3c3' class='xr-section-summary-in' type='checkbox'  ><label for='section-6f789336-5d98-4d64-960e-a6883fdfc3c3' class='xr-section-summary' >Attributes: <span>(47)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7, ACDD-1.3</dd><dt><span>featureType :</span></dt><dd>timeSeries</dd><dt><span>title :</span></dt><dd>Ground based in situ observations of nephelometer at Zeppelin mountain (Ny-Ålesund) (NO0042G)</dd><dt><span>keywords :</span></dt><dd>NO0042G, Zeppelin mountain (Ny-Ålesund), aerosol_light_scattering_enhancement_factor, aerosol_light_backscattering_enhancement_factor, aerosol_light_backscattering_coefficient, EMEP, aerosol_light_scattering_coefficient, GAW-WDCA, aerosol_humidified, ACTRIS, CREATE</dd><dt><span>id :</span></dt><dd>NO0042G.20080708135939.20181213000000.nephelometer..aerosol_humidified.3mo.6h.CH02L_TSI_3563_ZEP_ref+TSI_3563_ZEP_wet.CH02L_hygro_tandem_neph_CorrData.lev2.nc</dd><dt><span>naming_authority :</span></dt><dd>EBAS</dd><dt><span>project :</span></dt><dd>CREATE, ACTRIS, EMEP, GAW-WDCA</dd><dt><span>acknowledgement :</span></dt><dd>Request acknowledgement details from data originator</dd><dt><span>license :</span></dt><dd>CREATE: Fair use data policy (see also EMEP and WMO-GAW), ACTRIS: http://actris.nilu.no/Content/Documents/DataPolicy.pdf, EMEP: Public open access. We encourage contacting data originators if substatial use of individual time series is planned (fair use data policy)., GAW-WDCA: </dd><dt><span>summary :</span></dt><dd>Ground based in situ observations of nephelometer at Zeppelin mountain (Ny-Ålesund) (NO0042G). These measurements are gathered as a part of the following projects CREATE, ACTRIS, EMEP, GAW-WDCA and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: aerosol_light_backscattering_coefficient in aerosol_humidified, aerosol_light_backscattering_enhancement_factor in aerosol_humidified, aerosol_light_scattering_coefficient in aerosol_humidified, aerosol_light_scattering_enhancement_factor in aerosol_humidified</dd><dt><span>source :</span></dt><dd>surface observation</dd><dt><span>institution :</span></dt><dd>CH02L, Paul Scherrer Institut, PSI, Laboratory of Atmospheric Chemistry (LAC), OFLB, 5232, Villigen PSI, Switzerland</dd><dt><span>processing_level :</span></dt><dd>processing_level_test</dd><dt><span>date_created :</span></dt><dd>2018-12-13T00:00:00 UTC</dd><dt><span>date_metadata_modified :</span></dt><dd>2018-12-13T00:00:00 UTC</dd><dt><span>creator_name :</span></dt><dd>Paul Zieger, Maria A. Burgos</dd><dt><span>creator_type :</span></dt><dd>person</dd><dt><span>creator_email :</span></dt><dd>paul.zieger@aces.su.se, paul.zieger@aces.su.se</dd><dt><span>creator_institution :</span></dt><dd>&quot;Department of Environmental Science and Analytical Chemistry, ACES&quot;, &quot;Department of Environmental Science and Analytical Chemistry, ACES&quot;</dd><dt><span>contributor_name :</span></dt><dd>Maria A. Burgos</dd><dt><span>contributor_role :</span></dt><dd>data submitter</dd><dt><span>publisher_type :</span></dt><dd>institution</dd><dt><span>publisher_name :</span></dt><dd>NILU - Norwegian Institute for Air Research, ATMOS, EBAS</dd><dt><span>publisher_institution :</span></dt><dd>NILU - Norwegian Institute for Air Research, ATMOS, EBAS</dd><dt><span>publisher_email :</span></dt><dd>ebas@nilu.no</dd><dt><span>publisher_url :</span></dt><dd>https://www.nilu.no/</dd><dt><span>geospatial_bounds :</span></dt><dd>POINT Z (78.91 11.88 477.0)</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>EPSG:4979</dd><dt><span>geospatial_lat_min :</span></dt><dd>78.91</dd><dt><span>geospatial_lat_max :</span></dt><dd>78.91</dd><dt><span>geospatial_lon_min :</span></dt><dd>11.88</dd><dt><span>geospatial_lon_max :</span></dt><dd>11.88</dd><dt><span>geospatial_vertical_min :</span></dt><dd>477.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>477.0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>time_coverage_start :</span></dt><dd>2008-07-08T13:59:39 UTC</dd><dt><span>time_coverage_end :</span></dt><dd>2008-10-13T07:59:39 UTC</dd><dt><span>time_coverage_duration :</span></dt><dd>P0000-03-04T18:00:00</dd><dt><span>time_coverage_resolution :</span></dt><dd>P0000-00-00T06:00:00</dd><dt><span>timezone :</span></dt><dd>UTC</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>comment :</span></dt><dd>{
+    &quot;Data definition&quot;: &quot;EBAS_1.1&quot;, 
+    &quot;Set type code&quot;: &quot;TU&quot;, 
+    &quot;Timezone&quot;: &quot;UTC&quot;, 
+    &quot;File name&quot;: &quot;NO0042G.20080708135939.20181213000000.nephelometer..aerosol_humidified.3mo.6h.CH02L_TSI_3563_ZEP_ref+TSI_3563_ZEP_wet.CH02L_hygro_tandem_neph_CorrData.lev2.nc&quot;, 
+    &quot;File creation&quot;: &quot;20190627182802&quot;, 
+    &quot;Startdate&quot;: &quot;20080708135939&quot;, 
+    &quot;Revision date&quot;: &quot;20181213000000&quot;, 
+    &quot;Version&quot;: &quot;1&quot;, 
+    &quot;Version description&quot;: &quot;interpolated scattering coefficients, calculated scattering enhancement factors as described in Burgos et al., 2018&quot;, 
+    &quot;Statistics&quot;: &quot;arithmetic mean&quot;, 
+    &quot;Data level&quot;: &quot;2&quot;, 
+    &quot;Period code&quot;: &quot;3mo&quot;, 
+    &quot;Resolution code&quot;: &quot;6h&quot;, 
+    &quot;Sample duration&quot;: &quot;6h&quot;, 
+    &quot;Orig. time res.&quot;: &quot;6h&quot;, 
+    &quot;Station code&quot;: &quot;NO0042G&quot;, 
+    &quot;Platform code&quot;: &quot;NO0042S&quot;, 
+    &quot;Station name&quot;: &quot;Zeppelin mountain (Ny-Ålesund)&quot;, 
+    &quot;Station WDCA-ID&quot;: &quot;GAWANO__ZEP&quot;, 
+    &quot;Station GAW-ID&quot;: &quot;ZEP&quot;, 
+    &quot;Station GAW-Name&quot;: &quot;Zeppelin Mountain (Ny Ålesund)&quot;, 
+    &quot;Station land use&quot;: &quot;Gravel and stone&quot;, 
+    &quot;Station setting&quot;: &quot;Polar&quot;, 
+    &quot;Station GAW type&quot;: &quot;G&quot;, 
+    &quot;Station WMO region&quot;: &quot;6&quot;, 
+    &quot;Station latitude&quot;: &quot;78.90715&quot;, 
+    &quot;Station longitude&quot;: &quot;11.88668&quot;, 
+    &quot;Station altitude&quot;: &quot;474.0 m&quot;, 
+    &quot;Measurement latitude&quot;: &quot;78.91&quot;, 
+    &quot;Measurement longitude&quot;: &quot;11.88&quot;, 
+    &quot;Measurement altitude&quot;: &quot;477.0 m&quot;, 
+    &quot;Measurement height&quot;: &quot;2.0 m&quot;, 
+    &quot;Regime&quot;: &quot;IMG&quot;, 
+    &quot;Unit&quot;: &quot;1/Mm&quot;, 
+    &quot;Matrix&quot;: &quot;aerosol_humidified&quot;, 
+    &quot;Laboratory code&quot;: &quot;CH02L&quot;, 
+    &quot;Instrument type&quot;: &quot;nephelometer&quot;, 
+    &quot;Instrument name&quot;: &quot;TSI_3563_ZEP_ref+TSI_3563_ZEP_wet&quot;, 
+    &quot;Instrument manufacturer&quot;: &quot;TSI&quot;, 
+    &quot;Instrument model&quot;: &quot;3563&quot;, 
+    &quot;Instrument serial number&quot;: &quot;1043&quot;, 
+    &quot;Method ref&quot;: &quot;CH02L_hygro_tandem_neph_CorrData&quot;, 
+    &quot;Standard method&quot;: &quot;cal-gas=CO2+AIR_truncation-correction=Anderson1998&quot;, 
+    &quot;Inlet type&quot;: &quot;Stainless steel&quot;, 
+    &quot;Inlet description&quot;: &quot;no heater, no cut size&quot;, 
+    &quot;Humidity/temperature control&quot;: &quot;Humidification&quot;, 
+    &quot;Humidity/temperature control description&quot;: &quot;humidogram&quot;, 
+    &quot;Volume std. temperature&quot;: &quot;273.15 K&quot;, 
+    &quot;Volume std. pressure&quot;: &quot;1013.25 hPa&quot;, 
+    &quot;Detection limit&quot;: &quot;0.5 1/Mm&quot;, 
+    &quot;Detection limit expl.&quot;: &quot;Determined by instrument counting statistics, no detection limit flag used&quot;, 
+    &quot;Measurement uncertainty expl.&quot;: &quot;Uncertainty analysis described in Burgos et al., 2019&quot;, 
+    &quot;Zero/negative values code&quot;: &quot;Zero/negative possible&quot;, 
+    &quot;Zero/negative values&quot;: &quot;zero and neg. values may appear due to statistical variations at very low concentrations&quot;, 
+    &quot;Organization&quot;: &quot;CH02L, Paul Scherrer Institut, PSI, Laboratory of Atmospheric Chemistry (LAC), OFLB, , 5232, Villigen PSI, Switzerland&quot;, 
+    &quot;Frameworks&quot;: &quot;ACTRIS CREATE EMEP GAW-WDCA&quot;, 
+    &quot;Originator&quot;: &quot;Burgos, Maria A., paul.zieger@aces.su.se, Department of Environmental Science and Analytical Chemistry, ACES, , Frescativägen 54, , SE10691, Stockholm, Sweden&quot;, 
+    &quot;Submitter&quot;: &quot;Burgos, Maria A., paul.zieger@aces.su.se, Department of Environmental Science and Analytical Chemistry, ACES, , Frescativägen 54, , SE10691, Stockholm, Sweden&quot;, 
+    &quot;Acknowledgement&quot;: &quot;Request acknowledgement details from data originator&quot;
+}</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF-1.7, ACDD-1.3</dd><dt><span>history :</span></dt><dd>None</dd><dt><span>creator_url :</span></dt><dd>ebas.nilu.no</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Example 2 aerosol sulphate data </span>
+<span class="c1"># also here - </span>
+<span class="c1">#    the files are differently shaped for different periods</span>
+<span class="c1">#    best to read single files, analyse, and then concatenate for longer time series</span>
+<span class="c1">#    note that catalogue file names give no full description of what is in a file</span>
+
+<span class="c1"># get all data urls for one station, e.g., Zeppelin NO0042G</span>
+<span class="n">opendap_urls</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">all_opendap_urls</span> <span class="k">if</span> <span class="s1">&#39;NO0042G&#39;</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]</span>
+
+<span class="c1"># get all data urls which could contain sulphate data, exclude some</span>
+<span class="n">opendap_urls</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">opendap_urls</span> <span class="k">if</span> <span class="s1">&#39;filter_3pack&#39;</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]</span>
+<span class="n">opendap_urls</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">opendap_urls</span> <span class="k">if</span> <span class="ow">not</span> <span class="s1">&#39;sum_ammonia&#39;</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]</span>
+<span class="n">opendap_urls</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">opendap_urls</span> <span class="k">if</span> <span class="ow">not</span> <span class="s1">&#39;sulphur_dioxide&#39;</span> <span class="ow">in</span> <span class="n">x</span><span class="p">]</span>
+
+<span class="n">opendap_urls</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20200101070000.20230314140946.filter_3pack...1y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20160101070000.20230314140946.filter_3pack...3y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20230511100226.filter_3pack.sulphate_corrected.aerosol.9y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20230314140946.filter_3pack.sum_nitric_acid_and_nitrate.air+aerosol.9y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20230314140050.filter_3pack.potassium.aerosol.7y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20230314140050.filter_3pack.chloride.aerosol.7y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.sulphate_total.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.sodium.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.nitric_acid.air.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.nitrate.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.magnesium.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.calcium.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.ammonium.aerosol.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20140101070000.20210420142507.filter_3pack.ammonia.air.2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20010101070000.20230511100226.filter_3pack...19y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.19930101070000.20210421112338.filter_3pack...8y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.19920101070000.20210420142507.filter_3pack...1y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;,
+ &#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.19891101070000.20210420142507.filter_3pack...26mo.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;]
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">file_to_read</span> <span class="o">=</span> <span class="n">opendap_urls</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+<span class="n">file_to_read</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&#39;https://thredds.nilu.no/thredds/dodsC/ebas/NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&#39;
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds_single_file</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">open_dataset</span><span class="p">(</span><span class="n">file_to_read</span><span class="p">)</span>
+<span class="n">ds_single_file</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 183kB
+Dimensions:                                  (time: 730, tbnds: 2,
+                                              metadata_time: 2,
+                                              ammonia_qc_flags: 1,
+                                              ammonium_ug_N_per_m3_qc_flags: 1,
+                                              ammonium_ug_per_m3_qc_flags: 1,
+                                              calcium_qc_flags: 1,
+                                              ...
+                                              nitric_acid_qc_flags: 1,
+                                              potassium_qc_flags: 1,
+                                              sodium_qc_flags: 1,
+                                              sulphate_total_ug_S_per_m3_qc_flags: 1,
+                                              sulphate_total_ug_per_m3_qc_flags: 1,
+                                              sulphur_dioxide_qc_flags: 1)
+Coordinates:
+  * time                                     (time) datetime64[ns] 6kB 2021-0...
+  * metadata_time                            (metadata_time) datetime64[ns] 16B ...
+Dimensions without coordinates: tbnds, ammonia_qc_flags,
+                                ammonium_ug_N_per_m3_qc_flags,
+                                ammonium_ug_per_m3_qc_flags, calcium_qc_flags,
+                                chloride_qc_flags, magnesium_qc_flags,
+                                nitrate_ug_N_per_m3_qc_flags,
+                                nitrate_ug_per_m3_qc_flags,
+                                nitric_acid_qc_flags, potassium_qc_flags,
+                                sodium_qc_flags,
+                                sulphate_total_ug_S_per_m3_qc_flags,
+                                sulphate_total_ug_per_m3_qc_flags,
+                                sulphur_dioxide_qc_flags
+Data variables: (12/44)
+    time_bnds                                (time, tbnds) datetime64[ns] 12kB ...
+    metadata_time_bnds                       (metadata_time, tbnds) datetime64[ns] 32B ...
+    ammonia                                  (time) float64 6kB ...
+    ammonia_qc                               (ammonia_qc_flags, time) float64 6kB ...
+    ammonia_ebasmetadata                     (metadata_time) |S64 128B ...
+    ammonium_ug_N_per_m3                     (time) float64 6kB ...
+    ...                                       ...
+    sulphate_total_ug_per_m3                 (time) float64 6kB ...
+    sulphate_total_ug_per_m3_qc              (sulphate_total_ug_per_m3_qc_flags, time) float64 6kB ...
+    sulphate_total_ug_per_m3_ebasmetadata    (metadata_time) |S64 128B ...
+    sulphur_dioxide                          (time) float64 6kB ...
+    sulphur_dioxide_qc                       (sulphur_dioxide_qc_flags, time) float64 6kB ...
+    sulphur_dioxide_ebasmetadata             (metadata_time) |S64 128B ...
+Attributes: (12/106)
+    Conventions:                                   CF-1.8, ACDD-1.3
+    featureType:                                   timeSeries
+    title:                                         Ground based in situ obser...
+    keywords:                                      mass_concentration_of_nitr...
+    id:                                            NO0042G.20210101070000.202...
+    naming_authority:                              EBAS
+    ...                                            ...
+    geospatial_lat_units:                          degrees_north
+    geospatial_lon_units:                          degrees_east
+    comment:                                       {\n    &quot;Data definition&quot;: ...
+    standard_name_vocabulary:                      CF-1.7, ACDD-1.3
+    history:                                       None
+    creator_url:                                   ebas.nilu.no</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6a36b03a-3f96-48a2-b37f-c7b81600fec5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6a36b03a-3f96-48a2-b37f-c7b81600fec5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 730</li><li><span>tbnds</span>: 2</li><li><span class='xr-has-index'>metadata_time</span>: 2</li><li><span>ammonia_qc_flags</span>: 1</li><li><span>ammonium_ug_N_per_m3_qc_flags</span>: 1</li><li><span>ammonium_ug_per_m3_qc_flags</span>: 1</li><li><span>calcium_qc_flags</span>: 1</li><li><span>chloride_qc_flags</span>: 1</li><li><span>magnesium_qc_flags</span>: 1</li><li><span>nitrate_ug_N_per_m3_qc_flags</span>: 1</li><li><span>nitrate_ug_per_m3_qc_flags</span>: 1</li><li><span>nitric_acid_qc_flags</span>: 1</li><li><span>potassium_qc_flags</span>: 1</li><li><span>sodium_qc_flags</span>: 1</li><li><span>sulphate_total_ug_S_per_m3_qc_flags</span>: 1</li><li><span>sulphate_total_ug_per_m3_qc_flags</span>: 1</li><li><span>sulphur_dioxide_qc_flags</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-63eea7d2-907f-40d0-8881-db111ada73eb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-63eea7d2-907f-40d0-8881-db111ada73eb' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01T19:00:00 ... 2022-12-...</div><input id='attrs-bb922fc0-9cfc-4763-8fbb-b28017012122' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb922fc0-9cfc-4763-8fbb-b28017012122' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7aa82031-4025-4ef0-8fcb-4f64df694b68' class='xr-var-data-in' type='checkbox'><label for='data-7aa82031-4025-4ef0-8fcb-4f64df694b68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time of measurement</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T19:00:00.000000000&#x27;, &#x27;2021-01-02T19:00:00.000000000&#x27;,
+       &#x27;2021-01-03T19:00:00.000000000&#x27;, ..., &#x27;2022-12-29T19:00:00.000000000&#x27;,
+       &#x27;2022-12-30T19:00:00.000000000&#x27;, &#x27;2022-12-31T19:00:00.000000000&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>metadata_time</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-07-02T19:00:00 2022-07-02T1...</div><input id='attrs-abeee7de-2745-4250-8da0-3b9fe3629886' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abeee7de-2745-4250-8da0-3b9fe3629886' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4ef8efa-b44d-4c5d-89eb-955a1a12ca71' class='xr-var-data-in' type='checkbox'><label for='data-b4ef8efa-b44d-4c5d-89eb-955a1a12ca71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time of ebas metadata intervals</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>metadata_time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-07-02T19:00:00.000000000&#x27;, &#x27;2022-07-02T19:00:00.000000000&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6654873f-4c28-414d-9fc3-019ef303e43e' class='xr-section-summary-in' type='checkbox'  ><label for='section-6654873f-4c28-414d-9fc3-019ef303e43e' class='xr-section-summary' >Data variables: <span>(44)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, tbnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c1ab47e2-1c1b-4e7c-ad34-6decc1e33ca7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1ab47e2-1c1b-4e7c-ad34-6decc1e33ca7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f071e50-0eb4-4da8-8322-917ce45d1d9d' class='xr-var-data-in' type='checkbox'><label for='data-3f071e50-0eb4-4da8-8322-917ce45d1d9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time bounds for measurement</dd></dl></div><div class='xr-var-data'><pre>[1460 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>metadata_time_bnds</span></div><div class='xr-var-dims'>(metadata_time, tbnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9031fa9b-8704-4dda-92fd-1d706de241d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9031fa9b-8704-4dda-92fd-1d706de241d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35b241b7-149e-411c-877c-31a2600deee4' class='xr-var-data-in' type='checkbox'><label for='data-35b241b7-149e-411c-877c-31a2600deee4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time bounds for ebas metadata intervals</dd></dl></div><div class='xr-var-data'><pre>[4 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonia</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3005ba4d-e2b2-4880-b7d4-0b303bc935f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3005ba4d-e2b2-4880-b7d4-0b303bc935f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cce05361-07e2-43f8-adff-6639922b21c6' class='xr-var-data-in' type='checkbox'><label for='data-cce05361-07e2-43f8-adff-6639922b21c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_ammonia_expressed_as_nitrogen_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>ammonia_qc ammonia_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>ammonia</dd><dt><span>ebas_unit :</span></dt><dd>ug N/m3</dd><dt><span>ebas_matrix :</span></dt><dd>air</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Cellulose</dd><dt><span>ebas_coating_solution :</span></dt><dd>Oxalic acid</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.04 ug N/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonia_qc</span></div><div class='xr-var-dims'>(ammonia_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d4c949a4-580c-4acc-9679-edcf50f8daa5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4c949a4-580c-4acc-9679-edcf50f8daa5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd1d325a-4d23-4f31-b1ab-a1879dda1652' class='xr-var-data-in' type='checkbox'><label for='data-fd1d325a-4d23-4f31-b1ab-a1879dda1652' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonia_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c00c8d98-106e-4b68-964c-709c7415b20f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c00c8d98-106e-4b68-964c-709c7415b20f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b93e9340-14ea-45bd-965e-947b2976691f' class='xr-var-data-in' type='checkbox'><label for='data-b93e9340-14ea-45bd-965e-947b2976691f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_N_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f09cc450-fb1e-4256-94ef-aae6ac227f4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f09cc450-fb1e-4256-94ef-aae6ac227f4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8260f0d-b2c0-4a37-9e9a-081cc266deb7' class='xr-var-data-in' type='checkbox'><label for='data-e8260f0d-b2c0-4a37-9e9a-081cc266deb7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_ammonium_expressed_as_nitrogen_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>ammonium_ug N_per_m3_qc ammonium_ug N_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>ammonium</dd><dt><span>ebas_unit :</span></dt><dd>ug N/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0103 ug N/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_N_per_m3_qc</span></div><div class='xr-var-dims'>(ammonium_ug_N_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cfe9106c-2621-447e-a780-cbdf14ece2ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfe9106c-2621-447e-a780-cbdf14ece2ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06392c9e-6faa-4a8a-9e54-3bdf6b3c2d25' class='xr-var-data-in' type='checkbox'><label for='data-06392c9e-6faa-4a8a-9e54-3bdf6b3c2d25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_N_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-76fcf987-9b97-4827-8bc7-9f3cc746a7bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76fcf987-9b97-4827-8bc7-9f3cc746a7bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a51a72a4-d827-4c01-ab47-4d0361ee5f6e' class='xr-var-data-in' type='checkbox'><label for='data-a51a72a4-d827-4c01-ab47-4d0361ee5f6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-caac7b0f-6bc4-433e-9010-719cd6ca43af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-caac7b0f-6bc4-433e-9010-719cd6ca43af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37f552c3-1a64-47a1-8676-2712d2f8f74d' class='xr-var-data-in' type='checkbox'><label for='data-37f552c3-1a64-47a1-8676-2712d2f8f74d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_ammonium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>ammonium_ug_per_m3_qc ammonium_ug_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>ammonium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.013 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_comment :</span></dt><dd>Data converted on export from EBAS from &#x27;ug N/m3&#x27; to &#x27;ug/m3&#x27;, conversion factor 1.28786. Detection limit converted from &#x27;0.0103 ug N/m3&#x27; to &#x27;0.013 ug/m3&#x27;, conversion factor 1.28786.</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_per_m3_qc</span></div><div class='xr-var-dims'>(ammonium_ug_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-efe6d814-bac9-412a-a2f2-9b0f69698f08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efe6d814-bac9-412a-a2f2-9b0f69698f08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6209b05-6824-4f19-b8c7-802b72d9dd08' class='xr-var-data-in' type='checkbox'><label for='data-f6209b05-6824-4f19-b8c7-802b72d9dd08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ammonium_ug_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-34d9b517-4795-4bf3-a750-1e6a9fdda047' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34d9b517-4795-4bf3-a750-1e6a9fdda047' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1201d86b-7a37-489b-a4f6-14a3e6dc57e6' class='xr-var-data-in' type='checkbox'><label for='data-1201d86b-7a37-489b-a4f6-14a3e6dc57e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calcium</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e5634032-5e92-41ca-888f-291e6c0c5acc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5634032-5e92-41ca-888f-291e6c0c5acc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e737fa46-f4bd-43a1-a517-1f13b8ff9844' class='xr-var-data-in' type='checkbox'><label for='data-e737fa46-f4bd-43a1-a517-1f13b8ff9844' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_calcium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>calcium_qc calcium_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>calcium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0177 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calcium_qc</span></div><div class='xr-var-dims'>(calcium_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-73d90db7-6d10-4641-a99a-f5747f6c6d92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73d90db7-6d10-4641-a99a-f5747f6c6d92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab1f49d9-f58c-405e-b58a-9bd5f6f6d4d3' class='xr-var-data-in' type='checkbox'><label for='data-ab1f49d9-f58c-405e-b58a-9bd5f6f6d4d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calcium_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e5819d06-71bc-4df1-a706-417819551aaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5819d06-71bc-4df1-a706-417819551aaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16ba0b82-4891-4d65-a9fe-c23f0b73d3e0' class='xr-var-data-in' type='checkbox'><label for='data-16ba0b82-4891-4d65-a9fe-c23f0b73d3e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>chloride</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7b78ebca-8668-4219-b062-569baa8b3fd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b78ebca-8668-4219-b062-569baa8b3fd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6dac1a1-13d3-422c-bb25-f503e6961210' class='xr-var-data-in' type='checkbox'><label for='data-f6dac1a1-13d3-422c-bb25-f503e6961210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_chloride_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>chloride_qc chloride_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>chloride</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>chloride_qc</span></div><div class='xr-var-dims'>(chloride_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8d3d57f1-735b-4a93-aa07-6cd0aee0372b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d3d57f1-735b-4a93-aa07-6cd0aee0372b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cea7f1be-b080-4e3b-9c74-6655c4e963e2' class='xr-var-data-in' type='checkbox'><label for='data-cea7f1be-b080-4e3b-9c74-6655c4e963e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>chloride_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd230975-f973-4498-b32e-8dbf196b48cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd230975-f973-4498-b32e-8dbf196b48cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b68bb57d-98b6-4de1-8a8f-8fd25fdbd8b9' class='xr-var-data-in' type='checkbox'><label for='data-b68bb57d-98b6-4de1-8a8f-8fd25fdbd8b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>magnesium</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f6e22587-5085-4fa4-8845-b14b4d684395' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6e22587-5085-4fa4-8845-b14b4d684395' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa083b69-6f95-4b5a-aab2-3c1acd47e0ea' class='xr-var-data-in' type='checkbox'><label for='data-fa083b69-6f95-4b5a-aab2-3c1acd47e0ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_magnesium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>magnesium_qc magnesium_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>magnesium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0148 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>magnesium_qc</span></div><div class='xr-var-dims'>(magnesium_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-491a5d63-4d61-4776-8acd-9ec5253f8837' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-491a5d63-4d61-4776-8acd-9ec5253f8837' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53adcb69-1b5e-4955-857e-1f5e82d6f5a7' class='xr-var-data-in' type='checkbox'><label for='data-53adcb69-1b5e-4955-857e-1f5e82d6f5a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>magnesium_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-59bdc409-1663-4977-833e-c0a872798511' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59bdc409-1663-4977-833e-c0a872798511' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a95056d-f043-4286-a0fc-e004c7f2c1e6' class='xr-var-data-in' type='checkbox'><label for='data-8a95056d-f043-4286-a0fc-e004c7f2c1e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_N_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6953e430-7542-4d65-a215-0304764647b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6953e430-7542-4d65-a215-0304764647b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69c6a8a6-5c16-4b24-b970-f32beaa2bd5d' class='xr-var-data-in' type='checkbox'><label for='data-69c6a8a6-5c16-4b24-b970-f32beaa2bd5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_nitrate_expressed_as_nitrogen_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>nitrate_ug N_per_m3_qc nitrate_ug N_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>nitrate</dd><dt><span>ebas_unit :</span></dt><dd>ug N/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug N/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_N_per_m3_qc</span></div><div class='xr-var-dims'>(nitrate_ug_N_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4c30655c-d1c6-48eb-bb4e-b11f407aa5ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c30655c-d1c6-48eb-bb4e-b11f407aa5ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-164e005a-1ff0-4bee-985c-7337b07a7e6e' class='xr-var-data-in' type='checkbox'><label for='data-164e005a-1ff0-4bee-985c-7337b07a7e6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_N_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd4e338c-0612-42fb-ab9a-55378342c68f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd4e338c-0612-42fb-ab9a-55378342c68f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45a62f25-b53e-4e61-8493-142c89e753f3' class='xr-var-data-in' type='checkbox'><label for='data-45a62f25-b53e-4e61-8493-142c89e753f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-89ec7033-ff4c-4c9b-82af-b122ee7c706a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89ec7033-ff4c-4c9b-82af-b122ee7c706a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e312112a-e166-40b6-9301-d0f32db560fe' class='xr-var-data-in' type='checkbox'><label for='data-e312112a-e166-40b6-9301-d0f32db560fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_nitrate_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>nitrate_ug_per_m3_qc nitrate_ug_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>nitrate</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.09 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_comment :</span></dt><dd>Data converted on export from EBAS from &#x27;ug N/m3&#x27; to &#x27;ug/m3&#x27;, conversion factor 4.4267. Detection limit converted from &#x27;0.02 ug N/m3&#x27; to &#x27;0.09 ug/m3&#x27;, conversion factor 4.4267.</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_per_m3_qc</span></div><div class='xr-var-dims'>(nitrate_ug_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ce6674c9-ece4-4c29-860a-2122df0034e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce6674c9-ece4-4c29-860a-2122df0034e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6de7b1ce-f4b4-4163-8c4a-306e1f83fc03' class='xr-var-data-in' type='checkbox'><label for='data-6de7b1ce-f4b4-4163-8c4a-306e1f83fc03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitrate_ug_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-427c6265-4d26-4328-b232-e8fcb76673e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-427c6265-4d26-4328-b232-e8fcb76673e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24f8e645-2eec-489d-90b0-d03d815b2534' class='xr-var-data-in' type='checkbox'><label for='data-24f8e645-2eec-489d-90b0-d03d815b2534' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitric_acid</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-70d0197f-386f-44c7-87d5-6304ddfd07f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70d0197f-386f-44c7-87d5-6304ddfd07f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5b0d2d0-fa99-441f-a4e6-e42a7560b3d1' class='xr-var-data-in' type='checkbox'><label for='data-a5b0d2d0-fa99-441f-a4e6-e42a7560b3d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_nitric_acid_expressed_as_nitrogen_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>nitric_acid_qc nitric_acid_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>nitric_acid</dd><dt><span>ebas_unit :</span></dt><dd>ug N/m3</dd><dt><span>ebas_matrix :</span></dt><dd>air</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Cellulose</dd><dt><span>ebas_coating_solution :</span></dt><dd>KOH</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug N/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitric_acid_qc</span></div><div class='xr-var-dims'>(nitric_acid_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-325c6e23-e7b6-4ddb-8b07-c26956968c37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-325c6e23-e7b6-4ddb-8b07-c26956968c37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff7e37b3-c448-4ffa-a1ec-3d9969dfb579' class='xr-var-data-in' type='checkbox'><label for='data-ff7e37b3-c448-4ffa-a1ec-3d9969dfb579' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nitric_acid_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ce8b5956-6eee-4cb1-bbcc-ad58e248721d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce8b5956-6eee-4cb1-bbcc-ad58e248721d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2e4487e-cc46-41f8-a42e-3bc9ddadae09' class='xr-var-data-in' type='checkbox'><label for='data-c2e4487e-cc46-41f8-a42e-3bc9ddadae09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>potassium</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ff574fc4-2ee7-438b-8014-176036ba2a08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff574fc4-2ee7-438b-8014-176036ba2a08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd0f895b-ef9d-4078-a452-1c73ed3ab3d4' class='xr-var-data-in' type='checkbox'><label for='data-dd0f895b-ef9d-4078-a452-1c73ed3ab3d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_potassium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>potassium_qc potassium_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>potassium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0155 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>potassium_qc</span></div><div class='xr-var-dims'>(potassium_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-362a040d-56d8-468d-b50b-8f829be7bd0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-362a040d-56d8-468d-b50b-8f829be7bd0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-671fe420-98b5-4564-8b43-23b123a4a1b8' class='xr-var-data-in' type='checkbox'><label for='data-671fe420-98b5-4564-8b43-23b123a4a1b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>potassium_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4a3588d5-89e7-4c96-ac7f-975e9a68df2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a3588d5-89e7-4c96-ac7f-975e9a68df2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41397e56-5a95-4231-b1ef-92007f24f87d' class='xr-var-data-in' type='checkbox'><label for='data-41397e56-5a95-4231-b1ef-92007f24f87d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sodium</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ee81b262-14a5-4359-b34e-08781c944267' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee81b262-14a5-4359-b34e-08781c944267' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ffb533f-fed7-4e2b-8815-9e16489768ba' class='xr-var-data-in' type='checkbox'><label for='data-3ffb533f-fed7-4e2b-8815-9e16489768ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_sodium_in_dry_aerosol_particles_in _air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>sodium_qc sodium_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>sodium</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.0188 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sodium_qc</span></div><div class='xr-var-dims'>(sodium_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-424378a8-a08b-41db-bb51-a0eaced174f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-424378a8-a08b-41db-bb51-a0eaced174f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4adb628c-5990-4d44-88d7-91500f68f9e1' class='xr-var-data-in' type='checkbox'><label for='data-4adb628c-5990-4d44-88d7-91500f68f9e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sodium_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-73978c65-e14b-4147-b9e4-b529a85e0684' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73978c65-e14b-4147-b9e4-b529a85e0684' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66fdb1e4-078e-4c74-b4d9-f826e1553925' class='xr-var-data-in' type='checkbox'><label for='data-66fdb1e4-078e-4c74-b4d9-f826e1553925' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_S_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cad1f31a-d597-4b2a-98b3-d1ea20ad1c42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cad1f31a-d597-4b2a-98b3-d1ea20ad1c42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dec00460-cac1-4ae8-b77e-45d53e5dab1f' class='xr-var-data-in' type='checkbox'><label for='data-dec00460-cac1-4ae8-b77e-45d53e5dab1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>sulphate_total_ug S_per_m3_qc sulphate_total_ug S_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>sulphate_total</dd><dt><span>ebas_unit :</span></dt><dd>ug S/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug S/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_S_per_m3_qc</span></div><div class='xr-var-dims'>(sulphate_total_ug_S_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c13832e3-341e-4485-a79e-ce73fdd8e034' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c13832e3-341e-4485-a79e-ce73fdd8e034' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45b29f86-153a-41a9-8b09-c6b300b03575' class='xr-var-data-in' type='checkbox'><label for='data-45b29f86-153a-41a9-8b09-c6b300b03575' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_S_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c992d25a-fe19-4d80-b3d0-4f2e91ecc0f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c992d25a-fe19-4d80-b3d0-4f2e91ecc0f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b9c4adc-5b14-4f75-8f38-7ba83a71a5a2' class='xr-var-data-in' type='checkbox'><label for='data-2b9c4adc-5b14-4f75-8f38-7ba83a71a5a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_per_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd103b30-ff9d-4d82-b1b7-c95b35af3840' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd103b30-ff9d-4d82-b1b7-c95b35af3840' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2d5804b-0218-4411-b5fd-f595c3a9f318' class='xr-var-data-in' type='checkbox'><label for='data-a2d5804b-0218-4411-b5fd-f595c3a9f318' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>sulphate_total_ug_per_m3_qc sulphate_total_ug_per_m3_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>sulphate_total</dd><dt><span>ebas_unit :</span></dt><dd>ug/m3</dd><dt><span>ebas_matrix :</span></dt><dd>aerosol</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Teflon</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.06 ug/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_comment :</span></dt><dd>Data converted on export from EBAS from &#x27;ug S/m3&#x27; to &#x27;ug/m3&#x27;, conversion factor 2.9962. Detection limit converted from &#x27;0.02 ug S/m3&#x27; to &#x27;0.06 ug/m3&#x27;, conversion factor 2.9962.</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_per_m3_qc</span></div><div class='xr-var-dims'>(sulphate_total_ug_per_m3_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-29d7a19c-769e-45e2-b077-01cdf996b01a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29d7a19c-769e-45e2-b077-01cdf996b01a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e5f0b4f-c444-4182-9ba1-765ece6c999a' class='xr-var-data-in' type='checkbox'><label for='data-3e5f0b4f-c444-4182-9ba1-765ece6c999a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphate_total_ug_per_m3_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f285e969-ff85-4385-ba23-5184eb156277' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f285e969-ff85-4385-ba23-5184eb156277' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81925295-b5b5-4d8d-88e5-6e3b8b5c8d46' class='xr-var-data-in' type='checkbox'><label for='data-81925295-b5b5-4d8d-88e5-6e3b8b5c8d46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphur_dioxide</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-96567704-89cd-4277-ac6f-f6d39874b29d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96567704-89cd-4277-ac6f-f6d39874b29d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9c96b30-80ba-45b9-b5d1-1c4276026394' class='xr-var-data-in' type='checkbox'><label for='data-e9c96b30-80ba-45b9-b5d1-1c4276026394' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>mass_concentration_of_sulphur_dioxide_expressed_as_sulphur_in_air</dd><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>ancillary_variables :</span></dt><dd>sulphur_dioxide_qc sulphur_dioxide_ebasmetadata</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_component :</span></dt><dd>sulphur_dioxide</dd><dt><span>ebas_unit :</span></dt><dd>ug S/m3</dd><dt><span>ebas_matrix :</span></dt><dd>air</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_medium :</span></dt><dd>Cellulose</dd><dt><span>ebas_coating_solution :</span></dt><dd>KOH</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit :</span></dt><dd>0.02 ug S/m3</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphur_dioxide_qc</span></div><div class='xr-var-dims'>(sulphur_dioxide_qc_flags, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3801f11e-8afa-4029-afef-fda5833b4be1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3801f11e-8afa-4029-afef-fda5833b4be1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4fbf7a9-b07e-414f-ad4f-575f8ab10c38' class='xr-var-data-in' type='checkbox'><label for='data-b4fbf7a9-b07e-414f-ad4f-575f8ab10c38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>status_flag</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[730 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sulphur_dioxide_ebasmetadata</span></div><div class='xr-var-dims'>(metadata_time)</div><div class='xr-var-dtype'>|S64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7cbb44d2-fc66-410a-b99c-258d6f1eecf7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7cbb44d2-fc66-410a-b99c-258d6f1eecf7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3081937f-f0dc-4ce5-b679-a363c43a75cc' class='xr-var-data-in' type='checkbox'><label for='data-3081937f-f0dc-4ce5-b679-a363c43a75cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ebas metadata for different time intervals; json encoded</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=|S64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-091f477a-042a-4001-a94d-2de996c9691d' class='xr-section-summary-in' type='checkbox'  ><label for='section-091f477a-042a-4001-a94d-2de996c9691d' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e53c6e94-1d02-4b5b-912f-4b7ce0282f0f' class='xr-index-data-in' type='checkbox'/><label for='index-e53c6e94-1d02-4b5b-912f-4b7ce0282f0f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-01-01 19:00:00&#x27;, &#x27;2021-01-02 19:00:00&#x27;,
+               &#x27;2021-01-03 19:00:00&#x27;, &#x27;2021-01-04 19:00:00&#x27;,
+               &#x27;2021-01-05 19:00:00&#x27;, &#x27;2021-01-06 19:00:00&#x27;,
+               &#x27;2021-01-07 19:00:00&#x27;, &#x27;2021-01-08 19:00:00&#x27;,
+               &#x27;2021-01-09 19:00:00&#x27;, &#x27;2021-01-10 19:00:00&#x27;,
+               ...
+               &#x27;2022-12-22 19:00:00&#x27;, &#x27;2022-12-23 19:00:00&#x27;,
+               &#x27;2022-12-24 19:00:00&#x27;, &#x27;2022-12-25 19:00:00&#x27;,
+               &#x27;2022-12-26 19:00:00&#x27;, &#x27;2022-12-27 19:00:00&#x27;,
+               &#x27;2022-12-28 19:00:00&#x27;, &#x27;2022-12-29 19:00:00&#x27;,
+               &#x27;2022-12-30 19:00:00&#x27;, &#x27;2022-12-31 19:00:00&#x27;],
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=730, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>metadata_time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4b2dfbeb-dde8-42d0-82c7-9848edcb4dbc' class='xr-index-data-in' type='checkbox'/><label for='index-4b2dfbeb-dde8-42d0-82c7-9848edcb4dbc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-07-02 19:00:00&#x27;, &#x27;2022-07-02 19:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;metadata_time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-006f714a-0af6-404b-83e9-8ef7b9184806' class='xr-section-summary-in' type='checkbox'  ><label for='section-006f714a-0af6-404b-83e9-8ef7b9184806' class='xr-section-summary' >Attributes: <span>(106)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8, ACDD-1.3</dd><dt><span>featureType :</span></dt><dd>timeSeries</dd><dt><span>title :</span></dt><dd>Ground based in situ observations of filter_3pack at Zeppelin mountain (Ny-Ålesund) (NO0042G)</dd><dt><span>keywords :</span></dt><dd>mass_concentration_of_nitrate_in_dry_aerosol_particles_in _air, potassium, mass_concentration_of_sodium_in_dry_aerosol_particles_in _air, chloride, air, nitrate, sodium, NILU, nitric_acid, aerosol, ammonia, ammonium, mass_concentration_of_calcium_in_dry_aerosol_particles_in _air, EMEP, mass_concentration_of_potassium_in_dry_aerosol_particles_in _air, mass_concentration_of_nitric_acid_expressed_as_nitrogen_in_air, sulphur_dioxide, AMAP, mass_concentration_of_ammonium_expressed_as_nitrogen_in_dry_aerosol_particles_in _air, CAMP, calcium, magnesium, mass_concentration_of_sulphur_dioxide_expressed_as_sulphur_in_air, NO0042G, mass_concentration_of_ammonium_in_dry_aerosol_particles_in _air, mass_concentration_of_nitrate_expressed_as_nitrogen_in_dry_aerosol_particles_in _air, mass_concentration_of_magnesium_in_dry_aerosol_particles_in _air, mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air, mass_concentration_of_chloride_in_dry_aerosol_particles_in _air, Zeppelin mountain (Ny-Ålesund), sulphate_total, mass_concentration_of_ammonia_expressed_as_nitrogen_in_air</dd><dt><span>id :</span></dt><dd>NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc</dd><dt><span>naming_authority :</span></dt><dd>EBAS</dd><dt><span>project :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>summary :</span></dt><dd>Ground based in situ observations of filter_3pack at Zeppelin mountain (Ny-Ålesund) (NO0042G). These measurements are gathered as a part of the following projects AMAP, CAMP, EMEP, NILU and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: ammonia in air (mass_concentration_of_ammonia_expressed_as_nitrogen_in_air), ammonium in aerosol (mass_concentration_of_ammonium_expressed_as_nitrogen_in_dry_aerosol_particles_in _air), ammonium in aerosol (mass_concentration_of_ammonium_in_dry_aerosol_particles_in _air), calcium in aerosol (mass_concentration_of_calcium_in_dry_aerosol_particles_in _air), chloride in aerosol (mass_concentration_of_chloride_in_dry_aerosol_particles_in _air), magnesium in aerosol (mass_concentration_of_magnesium_in_dry_aerosol_particles_in _air), nitrate in aerosol (mass_concentration_of_nitrate_expressed_as_nitrogen_in_dry_aerosol_particles_in _air), nitrate in aerosol (mass_concentration_of_nitrate_in_dry_aerosol_particles_in _air), nitric_acid in air (mass_concentration_of_nitric_acid_expressed_as_nitrogen_in_air), potassium in aerosol (mass_concentration_of_potassium_in_dry_aerosol_particles_in _air), sodium in aerosol (mass_concentration_of_sodium_in_dry_aerosol_particles_in _air), sulphate_total in aerosol (mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air), sulphate_total in aerosol (mass_concentration_of_total_sulphateexpressed_as_sulphur_in_dry_aerosol_particles_in_air), sulphur_dioxide in air (mass_concentration_of_sulphur_dioxide_expressed_as_sulphur_in_air)</dd><dt><span>source :</span></dt><dd>surface observation</dd><dt><span>institution :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway</dd><dt><span>processing_level :</span></dt><dd>processing_level_test</dd><dt><span>date_created :</span></dt><dd>2023-03-14T14:00:50 UTC</dd><dt><span>date_metadata_modified :</span></dt><dd>2023-03-14T14:00:50 UTC</dd><dt><span>creator_name :</span></dt><dd>Wenche Aas</dd><dt><span>creator_type :</span></dt><dd>person</dd><dt><span>creator_email :</span></dt><dd>waa@nilu.no</dd><dt><span>creator_institution :</span></dt><dd>&quot;Norwegian Institute for Air Research, Atmosphere and Climate Department, NILU&quot;</dd><dt><span>contributor_name :</span></dt><dd>Anne Hjellbrekke</dd><dt><span>contributor_role :</span></dt><dd>data submitter</dd><dt><span>publisher_type :</span></dt><dd>institution</dd><dt><span>publisher_name :</span></dt><dd>NILU - Norwegian Institute for Air Research, ATMOS, EBAS</dd><dt><span>publisher_institution :</span></dt><dd>NILU - Norwegian Institute for Air Research, ATMOS, EBAS</dd><dt><span>publisher_email :</span></dt><dd>ebas@nilu.no</dd><dt><span>publisher_url :</span></dt><dd>https://www.nilu.no/</dd><dt><span>geospatial_bounds :</span></dt><dd>POINT Z (78.90715 11.88668 474.0)</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>EPSG:4979</dd><dt><span>geospatial_lat_min :</span></dt><dd>78.90715</dd><dt><span>geospatial_lat_max :</span></dt><dd>78.90715</dd><dt><span>geospatial_lon_min :</span></dt><dd>11.88668</dd><dt><span>geospatial_lon_max :</span></dt><dd>11.88668</dd><dt><span>geospatial_vertical_min :</span></dt><dd>474.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>474.0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>time_coverage_start :</span></dt><dd>2021-01-01T07:00:00 UTC</dd><dt><span>time_coverage_end :</span></dt><dd>2023-01-01T07:00:00 UTC</dd><dt><span>time_coverage_duration :</span></dt><dd>P0002-00-00T00:00:00</dd><dt><span>time_coverage_resolution :</span></dt><dd>P0000-00-01T00:00:00</dd><dt><span>timezone :</span></dt><dd>UTC</dd><dt><span>ebas_data_definition :</span></dt><dd>EBAS_1.1</dd><dt><span>ebas_data_license :</span></dt><dd>https://creativecommons.org/licenses/by/4.0/</dd><dt><span>ebas_set_type_code :</span></dt><dd>TI</dd><dt><span>ebas_timezone :</span></dt><dd>UTC</dd><dt><span>ebas_file_name :</span></dt><dd>NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc</dd><dt><span>ebas_file_creation :</span></dt><dd>2023-05-11T11:26:58.786202 UTC</dd><dt><span>ebas_export_state :</span></dt><dd>2023-05-11T10:25:03.246277 UTC</dd><dt><span>ebas_export_filter :</span></dt><dd>exclude-900,exclude-invalid</dd><dt><span>ebas_startdate :</span></dt><dd>20210101070000</dd><dt><span>ebas_revision_date :</span></dt><dd>20230314140050</dd><dt><span>ebas_statistics :</span></dt><dd>arithmetic mean</dd><dt><span>ebas_data_level :</span></dt><dd>2</dd><dt><span>ebas_period_code :</span></dt><dd>2y</dd><dt><span>ebas_resolution_code :</span></dt><dd>1d</dd><dt><span>ebas_station_code :</span></dt><dd>NO0042G</dd><dt><span>ebas_platform_code :</span></dt><dd>NO0042S</dd><dt><span>ebas_station_name :</span></dt><dd>Zeppelin mountain (Ny-Ålesund)</dd><dt><span>ebas_station_wdca_id :</span></dt><dd>GAWANO__ZEP</dd><dt><span>ebas_station_gaw_id :</span></dt><dd>ZEP</dd><dt><span>ebas_station_gaw_name :</span></dt><dd>Zeppelin Mountain (Ny Ålesund)</dd><dt><span>ebas_station_land_use :</span></dt><dd>Gravel and stone</dd><dt><span>ebas_station_setting :</span></dt><dd>Polar</dd><dt><span>ebas_station_gaw_type :</span></dt><dd>G</dd><dt><span>ebas_station_wmo_region :</span></dt><dd>6</dd><dt><span>ebas_station_latitude :</span></dt><dd>78.90715</dd><dt><span>ebas_station_longitude :</span></dt><dd>11.88668</dd><dt><span>ebas_station_altitude :</span></dt><dd>474.0 m</dd><dt><span>ebas_regime :</span></dt><dd>IMG</dd><dt><span>ebas_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_instrument_type :</span></dt><dd>filter_3pack</dd><dt><span>ebas_instrument_name :</span></dt><dd>f3p_d_0042</dd><dt><span>ebas_instrument_manufacturer :</span></dt><dd>NILU</dd><dt><span>ebas_instrument_model :</span></dt><dd>Three stage open face</dd><dt><span>ebas_analytical_laboratory_code :</span></dt><dd>NO01L</dd><dt><span>ebas_analytical_measurement_technique :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_name :</span></dt><dd>IC</dd><dt><span>ebas_analytical_instrument_manufacturer :</span></dt><dd>Dionex</dd><dt><span>ebas_analytical_instrument_model :</span></dt><dd>ICS-2100</dd><dt><span>ebas_method_ref :</span></dt><dd>NO01L_IC</dd><dt><span>ebas_standard_method :</span></dt><dd>SOP=EMEP_manual_v2014</dd><dt><span>ebas_inlet_type :</span></dt><dd>Hat or hood</dd><dt><span>ebas_inlet_description :</span></dt><dd>Downward facing</dd><dt><span>ebas_flow_rate :</span></dt><dd>17.4 l/min</dd><dt><span>ebas_sample_preparation :</span></dt><dd>Water extraction after ultrasonic treatment</dd><dt><span>ebas_blank_correction :</span></dt><dd>Blank corrected</dd><dt><span>ebas_humidity_temperaure_control :</span></dt><dd>None</dd><dt><span>ebas_humidity_temperaure_control_description :</span></dt><dd>Filter kept at ambient conditions together with sampling head</dd><dt><span>ebas_volume_std_temperature :</span></dt><dd>ambient</dd><dt><span>ebas_volume_std_pressure :</span></dt><dd>ambient</dd><dt><span>ebas_detection_limit_expl :</span></dt><dd>Detection limit is determined by taking three times standard deviation of ensemble of field blanks</dd><dt><span>ebas_zero_negative_values_code :</span></dt><dd>Zero/negative impossible</dd><dt><span>ebas_zero_negative_values :</span></dt><dd>Values below detection limit are reported as DL value, flagged with 781.</dd><dt><span>ebas_organization :</span></dt><dd>NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>ebas_framework_acronym :</span></dt><dd>AMAP, CAMP, EMEP, NILU</dd><dt><span>ebas_framework_name :</span></dt><dd>, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research</dd><dt><span>ebas_framework_description :</span></dt><dd>, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.</dd><dt><span>ebas_framework_contact_name :</span></dt><dd>Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth</dd><dt><span>ebas_framework_contact_email :</span></dt><dd>waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no</dd><dt><span>ebas_originator :</span></dt><dd>Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970</dd><dt><span>ebas_submitter :</span></dt><dd>Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>comment :</span></dt><dd>{
+    &quot;Data definition&quot;: &quot;EBAS_1.1&quot;,
+    &quot;Data license&quot;: &quot;https://creativecommons.org/licenses/by/4.0/&quot;,
+    &quot;Set type code&quot;: &quot;TI&quot;,
+    &quot;Timezone&quot;: &quot;UTC&quot;,
+    &quot;File name&quot;: &quot;NO0042G.20210101070000.20230314140050.filter_3pack...2y.1d.NO01L_f3p_d_0042.NO01L_IC.lev2.nc&quot;,
+    &quot;File creation&quot;: &quot;2023-05-11T11:26:58.786202 UTC&quot;,
+    &quot;Export state&quot;: &quot;2023-05-11T10:25:03.246277 UTC&quot;,
+    &quot;Export filter&quot;: &quot;exclude-900,exclude-invalid&quot;,
+    &quot;Startdate&quot;: &quot;20210101070000&quot;,
+    &quot;Revision date&quot;: &quot;20230314140050&quot;,
+    &quot;Statistics&quot;: &quot;arithmetic mean&quot;,
+    &quot;Data level&quot;: &quot;2&quot;,
+    &quot;Period code&quot;: &quot;2y&quot;,
+    &quot;Resolution code&quot;: &quot;1d&quot;,
+    &quot;Station code&quot;: &quot;NO0042G&quot;,
+    &quot;Platform code&quot;: &quot;NO0042S&quot;,
+    &quot;Station name&quot;: &quot;Zeppelin mountain (Ny-Ålesund)&quot;,
+    &quot;Station WDCA-ID&quot;: &quot;GAWANO__ZEP&quot;,
+    &quot;Station GAW-ID&quot;: &quot;ZEP&quot;,
+    &quot;Station GAW-Name&quot;: &quot;Zeppelin Mountain (Ny Ålesund)&quot;,
+    &quot;Station land use&quot;: &quot;Gravel and stone&quot;,
+    &quot;Station setting&quot;: &quot;Polar&quot;,
+    &quot;Station GAW type&quot;: &quot;G&quot;,
+    &quot;Station WMO region&quot;: &quot;6&quot;,
+    &quot;Station latitude&quot;: &quot;78.90715&quot;,
+    &quot;Station longitude&quot;: &quot;11.88668&quot;,
+    &quot;Station altitude&quot;: &quot;474.0 m&quot;,
+    &quot;Regime&quot;: &quot;IMG&quot;,
+    &quot;Laboratory code&quot;: &quot;NO01L&quot;,
+    &quot;Instrument type&quot;: &quot;filter_3pack&quot;,
+    &quot;Instrument name&quot;: &quot;f3p_d_0042&quot;,
+    &quot;Instrument manufacturer&quot;: &quot;NILU&quot;,
+    &quot;Instrument model&quot;: &quot;Three stage open face&quot;,
+    &quot;Analytical laboratory code&quot;: &quot;NO01L&quot;,
+    &quot;Analytical measurement technique&quot;: &quot;IC&quot;,
+    &quot;Analytical instrument name&quot;: &quot;IC&quot;,
+    &quot;Analytical instrument manufacturer&quot;: &quot;Dionex&quot;,
+    &quot;Analytical instrument model&quot;: &quot;ICS-2100&quot;,
+    &quot;Method ref&quot;: &quot;NO01L_IC&quot;,
+    &quot;Standard method&quot;: &quot;SOP=EMEP_manual_v2014&quot;,
+    &quot;Inlet type&quot;: &quot;Hat or hood&quot;,
+    &quot;Inlet description&quot;: &quot;Downward facing&quot;,
+    &quot;Flow rate&quot;: &quot;17.4 l/min&quot;,
+    &quot;Sample preparation&quot;: &quot;Water extraction after ultrasonic treatment&quot;,
+    &quot;Blank correction&quot;: &quot;Blank corrected&quot;,
+    &quot;Humidity/temperature control&quot;: &quot;None&quot;,
+    &quot;Humidity/temperature control description&quot;: &quot;Filter kept at ambient conditions together with sampling head&quot;,
+    &quot;Volume std. temperature&quot;: &quot;ambient&quot;,
+    &quot;Volume std. pressure&quot;: &quot;ambient&quot;,
+    &quot;Detection limit expl.&quot;: &quot;Detection limit is determined by taking three times standard deviation of ensemble of field blanks&quot;,
+    &quot;Zero/negative values code&quot;: &quot;Zero/negative impossible&quot;,
+    &quot;Zero/negative values&quot;: &quot;Values below detection limit are reported as DL value, flagged with 781.&quot;,
+    &quot;Organization&quot;: &quot;NO01L, Norwegian Institute for Air Research, NILU, , Instituttveien 18, , 2007, Kjeller, Norway&quot;,
+    &quot;Framework acronym&quot;: &quot;AMAP, CAMP, EMEP, NILU&quot;,
+    &quot;Framework name&quot;: &quot;, OSPARCOM - Comprehensive Atmospheric Monitoring Programme, European Monitoring and Evaluation Programme, Norwegian Institute for Air Research&quot;,
+    &quot;Framework description&quot;: &quot;, The OSPARCOM Comprehensive Atmospheric Monitoring Programme goal is the assessment of the atmospheric input of selected contaminants to the OSPAR maritime area and regions., The European Monitoring and Evaluation Programme (EMEP) is a scientifically based and policy driven programme under the Convention on Long-range Transboundary Air Pollution (CLRTAP) for int&#x27;l co-operation to solve transboundary air pollution problems., Atmospheric measuremnts produced at NILU.&quot;,
+    &quot;Framework contact name&quot;: &quot;Wenche Aas, Wenche Aas, Kjetil Tørseth, Kjetil Tørseth&quot;,
+    &quot;Framework contact email&quot;: &quot;waa@nilu.no, waa@nilu.no, kt@nilu.no, kt@nilu.no&quot;,
+    &quot;Originator&quot;: &quot;Aas, Wenche, waa@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway, ORCID=0000-0002-2908-1970&quot;,
+    &quot;Submitter&quot;: &quot;Hjellbrekke, Anne, agh@nilu.no, Norwegian Institute for Air Research, NILU, Atmosphere and Climate Department, Instituttveien 18, , 2007, Kjeller, Norway&quot;
+}</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF-1.7, ACDD-1.3</dd><dt><span>history :</span></dt><dd>None</dd><dt><span>creator_url :</span></dt><dd>ebas.nilu.no</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds_single_file</span><span class="p">[</span><span class="s1">&#39;sulphate_total_ug_S_per_m3&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span>
+</pre></div>
+</div>
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+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7f4257b00950&gt;]
+</pre></div>
+</div>
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+    <span class="theme-switch nav-link" data-mode="auto"><i class="fa-solid fa-circle-half-stroke fa-lg"></i></span>
+  </button>
+`);
+</script>
+
+
+<script>
+document.write(`
+  <button class="btn btn-sm navbar-btn search-button search-button__button" title="Search" aria-label="Search" data-bs-placement="bottom" data-bs-toggle="tooltip">
+    <i class="fa-solid fa-magnifying-glass fa-lg"></i>
+  </button>
+`);
+</script>
+<label class="sidebar-toggle secondary-toggle btn btn-sm" for="__secondary"title="Toggle secondary sidebar" data-bs-placement="bottom" data-bs-toggle="tooltip">
+    <span class="fa-solid fa-list"></span>
+</label>
+</div></div>
+      
+    </div>
+  
+</div>
+</div>
+              
+              
+
+<div id="jb-print-docs-body" class="onlyprint">
+    <h1>Using masks and computing weighted average</h1>
+    <!-- Table of contents -->
+    <div id="print-main-content">
+        <div id="jb-print-toc">
+            
+            <div>
+                <h2> Contents </h2>
+            </div>
+            <nav aria-label="Page">
+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#import-python-packages">Import python packages</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#search-data">Search data</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#create-dictionary-from-the-list-of-datasets-we-found">Create dictionary from the list of datasets we found</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#compute-weighted-mean">Compute weighted mean</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#compute-weighted-average-over-the-entire-globe">Compute weighted average over the entire globe</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#comparison-with-unweighted-mean">Comparison with unweighted mean</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#compute-weigted-arctic-average">Compute Weigted arctic average</a></li>
+</ul>
+            </nav>
+        </div>
+    </div>
+</div>
+
+              
+                
+<div id="searchbox"></div>
+                <article class="bd-article">
+                  
+  <section id="using-masks-and-computing-weighted-average">
+<h1>Using masks and computing weighted average<a class="headerlink" href="#using-masks-and-computing-weighted-average" title="Link to this heading">#</a></h1>
+<p>This example is based from xarray example http://xarray.pydata.org/en/stable/examples/area_weighted_temperature.html</p>
+<section id="import-python-packages">
+<h2>Import python packages<a class="headerlink" href="#import-python-packages" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">xarray</span> <span class="k">as</span> <span class="nn">xr</span>
+<span class="n">xr</span><span class="o">.</span><span class="n">set_options</span><span class="p">(</span><span class="n">display_style</span><span class="o">=</span><span class="s1">&#39;html&#39;</span><span class="p">)</span>
+<span class="kn">import</span> <span class="nn">intake</span>
+<span class="kn">import</span> <span class="nn">cftime</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+<span class="kn">import</span> <span class="nn">cartopy.crs</span> <span class="k">as</span> <span class="nn">ccrs</span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="o">%</span><span class="k">matplotlib</span> inline
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">cat_url</span> <span class="o">=</span> <span class="s2">&quot;https://storage.googleapis.com/cmip6/pangeo-cmip6.json&quot;</span>
+<span class="n">col</span> <span class="o">=</span> <span class="n">intake</span><span class="o">.</span><span class="n">open_esm_datastore</span><span class="p">(</span><span class="n">cat_url</span><span class="p">)</span>
+<span class="n">col</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><p><strong>pangeo-cmip6 catalog with 7674 dataset(s) from 514818 asset(s)</strong>:</p> <div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>unique</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>activity_id</th>
+      <td>18</td>
+    </tr>
+    <tr>
+      <th>institution_id</th>
+      <td>36</td>
+    </tr>
+    <tr>
+      <th>source_id</th>
+      <td>88</td>
+    </tr>
+    <tr>
+      <th>experiment_id</th>
+      <td>170</td>
+    </tr>
+    <tr>
+      <th>member_id</th>
+      <td>657</td>
+    </tr>
+    <tr>
+      <th>table_id</th>
+      <td>37</td>
+    </tr>
+    <tr>
+      <th>variable_id</th>
+      <td>700</td>
+    </tr>
+    <tr>
+      <th>grid_label</th>
+      <td>10</td>
+    </tr>
+    <tr>
+      <th>zstore</th>
+      <td>514818</td>
+    </tr>
+    <tr>
+      <th>dcpp_init_year</th>
+      <td>60</td>
+    </tr>
+    <tr>
+      <th>version</th>
+      <td>736</td>
+    </tr>
+    <tr>
+      <th>derived_variable_id</th>
+      <td>0</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+</section>
+<section id="search-data">
+<h2>Search data<a class="headerlink" href="#search-data" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">cat</span> <span class="o">=</span> <span class="n">col</span><span class="o">.</span><span class="n">search</span><span class="p">(</span><span class="n">source_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;NorESM2-LM&#39;</span><span class="p">],</span> <span class="n">experiment_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;historical&#39;</span><span class="p">],</span> <span class="n">table_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Amon&#39;</span><span class="p">],</span> <span class="n">variable_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">],</span> <span class="n">member_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;r1i1p1f1&#39;</span><span class="p">])</span>
+<span class="n">cat</span><span class="o">.</span><span class="n">df</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>activity_id</th>
+      <th>institution_id</th>
+      <th>source_id</th>
+      <th>experiment_id</th>
+      <th>member_id</th>
+      <th>table_id</th>
+      <th>variable_id</th>
+      <th>grid_label</th>
+      <th>zstore</th>
+      <th>dcpp_init_year</th>
+      <th>version</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>0</th>
+      <td>CMIP</td>
+      <td>NCC</td>
+      <td>NorESM2-LM</td>
+      <td>historical</td>
+      <td>r1i1p1f1</td>
+      <td>Amon</td>
+      <td>tas</td>
+      <td>gn</td>
+      <td>gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historica...</td>
+      <td>NaN</td>
+      <td>20190815</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+</section>
+<section id="create-dictionary-from-the-list-of-datasets-we-found">
+<h2>Create dictionary from the list of datasets we found<a class="headerlink" href="#create-dictionary-from-the-list-of-datasets-we-found" title="Link to this heading">#</a></h2>
+<ul class="simple">
+<li><p>This step may take several minutes so be patient!</p></li>
+</ul>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dset_dict</span> <span class="o">=</span> <span class="n">cat</span><span class="o">.</span><span class="n">to_dataset_dict</span><span class="p">(</span><span class="n">zarr_kwargs</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;use_cftime&#39;</span><span class="p">:</span><span class="kc">True</span><span class="p">})</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--&gt; The keys in the returned dictionary of datasets are constructed as follows:
+	&#39;activity_id.institution_id.source_id.experiment_id.table_id.grid_label&#39;
+</pre></div>
+</div>
+<div class="output text_html">
+<style>
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+    <div>
+      <progress value='1' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>
+      100.00% [1/1 00:12&lt;00:00]
+    </div>
+    </div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="nb">list</span><span class="p">(</span><span class="n">dset_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&#39;CMIP.NCC.NorESM2-LM.historical.Amon.gn&#39;]
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dset</span> <span class="o">=</span> <span class="n">dset_dict</span><span class="p">[</span><span class="nb">list</span><span class="p">(</span><span class="n">dset_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">())[</span><span class="mi">0</span><span class="p">]]</span>
+<span class="n">dset</span>
+</pre></div>
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+
+.xr-var-attrs,
+.xr-var-data,
+.xr-index-data {
+  display: none;
+  background-color: var(--xr-background-color) !important;
+  padding-bottom: 5px !important;
+}
+
+.xr-var-attrs-in:checked ~ .xr-var-attrs,
+.xr-var-data-in:checked ~ .xr-var-data,
+.xr-index-data-in:checked ~ .xr-index-data {
+  display: block;
+}
+
+.xr-var-data > table {
+  float: right;
+}
+
+.xr-var-name span,
+.xr-var-data,
+.xr-index-name div,
+.xr-index-data,
+.xr-attrs {
+  padding-left: 25px !important;
+}
+
+.xr-attrs,
+.xr-var-attrs,
+.xr-var-data,
+.xr-index-data {
+  grid-column: 1 / -1;
+}
+
+dl.xr-attrs {
+  padding: 0;
+  margin: 0;
+  display: grid;
+  grid-template-columns: 125px auto;
+}
+
+.xr-attrs dt,
+.xr-attrs dd {
+  padding: 0;
+  margin: 0;
+  float: left;
+  padding-right: 10px;
+  width: auto;
+}
+
+.xr-attrs dt {
+  font-weight: normal;
+  grid-column: 1;
+}
+
+.xr-attrs dt:hover span {
+  display: inline-block;
+  background: var(--xr-background-color);
+  padding-right: 10px;
+}
+
+.xr-attrs dd {
+  grid-column: 2;
+  white-space: pre-wrap;
+  word-break: break-all;
+}
+
+.xr-icon-database,
+.xr-icon-file-text2,
+.xr-no-icon {
+  display: inline-block;
+  vertical-align: middle;
+  width: 1em;
+  height: 1.5em !important;
+  stroke-width: 0;
+  stroke: currentColor;
+  fill: currentColor;
+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 110MB
+Dimensions:         (lat: 96, bnds: 2, lon: 144, member_id: 1,
+                     dcpp_init_year: 1, time: 1980)
+Coordinates:
+    height          float64 8B ...
+  * lat             (lat) float64 768B -90.0 -88.11 -86.21 ... 86.21 88.11 90.0
+    lat_bnds        (lat, bnds) float64 2kB dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;
+  * lon             (lon) float64 1kB 0.0 2.5 5.0 7.5 ... 352.5 355.0 357.5
+    lon_bnds        (lon, bnds) float64 2kB dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;
+  * time            (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:...
+    time_bnds       (time, bnds) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+Dimensions without coordinates: bnds
+Data variables:
+    tas             (member_id, dcpp_init_year, time, lat, lon) float32 109MB dask.array&lt;chunksize=(1, 1, 990, 96, 144), meta=np.ndarray&gt;
+Attributes: (12/65)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    Hybrid-restart from year 1600-01-01 of ...
+    branch_time:                      0.0
+    branch_time_in_child:             0.0
+    branch_time_in_parent:            430335.0
+    ...                               ...
+    intake_esm_attrs:variable_id:     tas
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/hi...
+    intake_esm_attrs:version:         20190815
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCC.NorESM2-LM.historical.Amon.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2f5bb113-4108-45a8-8b6e-a23f5ff0cadb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2f5bb113-4108-45a8-8b6e-a23f5ff0cadb' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 96</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 144</li><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-24910492-b4b3-49c9-b1db-625b27633c26' class='xr-section-summary-in' type='checkbox'  checked><label for='section-24910492-b4b3-49c9-b1db-625b27633c26' class='xr-section-summary' >Coordinates: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-25bffdd6-7a32-489d-a7d3-a8741cf0e77d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25bffdd6-7a32-489d-a7d3-a8741cf0e77d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-136117b1-8d4a-4c51-9f4e-2b9f7507180e' class='xr-var-data-in' type='checkbox'><label for='data-136117b1-8d4a-4c51-9f4e-2b9f7507180e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.11 -86.21 ... 88.11 90.0</div><input id='attrs-add5a11d-33a7-4d01-92fe-04dafb7aefd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-add5a11d-33a7-4d01-92fe-04dafb7aefd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67431778-c956-4f2f-b711-81c139a3dd4e' class='xr-var-data-in' type='checkbox'><label for='data-67431778-c956-4f2f-b711-81c139a3dd4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -88.105263, -86.210526, -84.315789, -82.421053, -80.526316,
+       -78.631579, -76.736842, -74.842105, -72.947368, -71.052632, -69.157895,
+       -67.263158, -65.368421, -63.473684, -61.578947, -59.684211, -57.789474,
+       -55.894737, -54.      , -52.105263, -50.210526, -48.315789, -46.421053,
+       -44.526316, -42.631579, -40.736842, -38.842105, -36.947368, -35.052632,
+       -33.157895, -31.263158, -29.368421, -27.473684, -25.578947, -23.684211,
+       -21.789474, -19.894737, -18.      , -16.105263, -14.210526, -12.315789,
+       -10.421053,  -8.526316,  -6.631579,  -4.736842,  -2.842105,  -0.947368,
+         0.947368,   2.842105,   4.736842,   6.631579,   8.526316,  10.421053,
+        12.315789,  14.210526,  16.105263,  18.      ,  19.894737,  21.789474,
+        23.684211,  25.578947,  27.473684,  29.368421,  31.263158,  33.157895,
+        35.052632,  36.947368,  38.842105,  40.736842,  42.631579,  44.526316,
+        46.421053,  48.315789,  50.210526,  52.105263,  54.      ,  55.894737,
+        57.789474,  59.684211,  61.578947,  63.473684,  65.368421,  67.263158,
+        69.157895,  71.052632,  72.947368,  74.842105,  76.736842,  78.631579,
+        80.526316,  82.421053,  84.315789,  86.210526,  88.105263,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;</div><input id='attrs-2ad0f556-14c8-4960-ab9d-3dfc3e1859ea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2ad0f556-14c8-4960-ab9d-3dfc3e1859ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9cac7e1-55c0-4472-b83b-db6b1d64de40' class='xr-var-data-in' type='checkbox'><label for='data-b9cac7e1-55c0-4472-b83b-db6b1d64de40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 1.50 kiB </td>
+                        <td> 1.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (96, 2) </td>
+                        <td> (96, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="79" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="29" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="29" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="29" y1="0" x2="29" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 29.2612335534925,0.0 29.2612335534925,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="14.630617" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="49.261234" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,49.261234,60.000000)">96</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5 5.0 ... 352.5 355.0 357.5</div><input id='attrs-8b12e301-791e-42c8-82f9-1bf903daab62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b12e301-791e-42c8-82f9-1bf903daab62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6440b1e2-4d43-40ba-bd3c-a1bc6c628f69' class='xr-var-data-in' type='checkbox'><label for='data-6440b1e2-4d43-40ba-bd3c-a1bc6c628f69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0. ,   2.5,   5. ,   7.5,  10. ,  12.5,  15. ,  17.5,  20. ,  22.5,
+        25. ,  27.5,  30. ,  32.5,  35. ,  37.5,  40. ,  42.5,  45. ,  47.5,
+        50. ,  52.5,  55. ,  57.5,  60. ,  62.5,  65. ,  67.5,  70. ,  72.5,
+        75. ,  77.5,  80. ,  82.5,  85. ,  87.5,  90. ,  92.5,  95. ,  97.5,
+       100. , 102.5, 105. , 107.5, 110. , 112.5, 115. , 117.5, 120. , 122.5,
+       125. , 127.5, 130. , 132.5, 135. , 137.5, 140. , 142.5, 145. , 147.5,
+       150. , 152.5, 155. , 157.5, 160. , 162.5, 165. , 167.5, 170. , 172.5,
+       175. , 177.5, 180. , 182.5, 185. , 187.5, 190. , 192.5, 195. , 197.5,
+       200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,
+       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,
+       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,
+       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,
+       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,
+       325. , 327.5, 330. , 332.5, 335. , 337.5, 340. , 342.5, 345. , 347.5,
+       350. , 352.5, 355. , 357.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;</div><input id='attrs-e7442090-4a19-4647-a8b4-ab92a8f44588' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7442090-4a19-4647-a8b4-ab92a8f44588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4eeb2154-4bc1-4828-8492-45f6c158b28f' class='xr-var-data-in' type='checkbox'><label for='data-4eeb2154-4bc1-4828-8492-45f6c158b28f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 2.25 kiB </td>
+                        <td> 2.25 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (144, 2) </td>
+                        <td> (144, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="77" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="27" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="27" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="27" y1="0" x2="27" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 27.054035963169408,0.0 27.054035963169408,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="13.527018" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="47.054036" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,47.054036,60.000000)">144</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2014-12-...</div><input id='attrs-73258975-2fb9-449a-9ec7-a8d2bf6ea155' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73258975-2fb9-449a-9ec7-a8d2bf6ea155' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e06054b-f481-4a88-9c00-8b6014f55e0f' class='xr-var-data-in' type='checkbox'><label for='data-9e06054b-f481-4a88-9c00-8b6014f55e0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2014, 10, 16, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 11, 16, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 12, 16, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-4d0ce4ef-db65-4ec5-a879-36a4815dbf39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d0ce4ef-db65-4ec5-a879-36a4815dbf39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6f5a4a6-b35c-4a01-89d6-10dfda46bbcb' class='xr-var-data-in' type='checkbox'><label for='data-d6f5a4a6-b35c-4a01-89d6-10dfda46bbcb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 30.94 kiB </td>
+                        <td> 30.94 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1980, 2) </td>
+                        <td> (1980, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-acc42975-e02e-4dad-84c6-2554daea5204' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-acc42975-e02e-4dad-84c6-2554daea5204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3620eb4-d6df-48ae-a736-2f6c76aea28b' class='xr-var-data-in' type='checkbox'><label for='data-c3620eb4-d6df-48ae-a736-2f6c76aea28b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-98ffee70-2221-4c81-a431-93fab9c1fb1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98ffee70-2221-4c81-a431-93fab9c1fb1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da08f6d4-9cda-4819-a825-8fa730341863' class='xr-var-data-in' type='checkbox'><label for='data-da08f6d4-9cda-4819-a825-8fa730341863' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0d0e4745-1664-4bc3-824c-73a1a6be2723' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0d0e4745-1664-4bc3-824c-73a1a6be2723' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 990, 96, 144), meta=np.ndarray&gt;</div><input id='attrs-a0ffedab-455b-46fe-8cbf-32c5ac361863' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0ffedab-455b-46fe-8cbf-32c5ac361863' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6943860-f327-41e6-a286-f0db563209ac' class='xr-var-data-in' type='checkbox'><label for='data-f6943860-f327-41e6-a286-f0db563209ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>history :</span></dt><dd>2019-08-15T12:42:20Z altered by CMOR: Treated scalar dimension: &#x27;height&#x27;. 2019-08-15T12:42:21Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>original_name :</span></dt><dd>TREFHT</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 104.41 MiB </td>
+                        <td> 52.21 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 96, 144) </td>
+                        <td> (1, 1, 990, 96, 144) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="347" height="154" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="25" y2="25" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="25" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="25" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,25.412616514582485 0.0,25.412616514582485" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="45.412617" font-size="1.0rem" font-weight="100" text-anchor="middle" >1</text>
+  <text x="45.412617" y="12.706308" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,45.412617,12.706308)">1</text>
+
+
+  <!-- Horizontal lines -->
+  <line x1="95" y1="0" x2="165" y2="70" style="stroke-width:2" />
+  <line x1="95" y1="34" x2="165" y2="104" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="95" y1="0" x2="95" y2="34" style="stroke-width:2" />
+  <line x1="130" y1="35" x2="130" y2="69" />
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+
+  <!-- Colored Rectangle -->
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+
+  <!-- Horizontal lines -->
+  <line x1="95" y1="0" x2="131" y2="0" style="stroke-width:2" />
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+
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+  <line x1="95" y1="0" x2="165" y2="70" style="stroke-width:2" />
+  <line x1="131" y1="0" x2="202" y2="70" style="stroke-width:2" />
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+  <!-- Colored Rectangle -->
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+
+  <!-- Horizontal lines -->
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+
+  <!-- Vertical lines -->
+  <line x1="165" y1="70" x2="165" y2="104" style="stroke-width:2" />
+  <line x1="202" y1="70" x2="202" y2="104" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="165.58823529411765,70.58823529411765 202.35463992729706,70.58823529411765 202.35463992729706,104.9007638365262 165.58823529411765,104.9007638365262" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="183.971438" y="124.900764" font-size="1.0rem" font-weight="100" text-anchor="middle" >144</text>
+  <text x="222.354640" y="87.744500" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,222.354640,87.744500)">96</text>
+  <text x="120.294118" y="89.606646" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(45,120.294118,89.606646)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-d7393555-5f4b-4bd3-8ed0-164f44ff1283' class='xr-section-summary-in' type='checkbox'  ><label for='section-d7393555-5f4b-4bd3-8ed0-164f44ff1283' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-938ffefc-eb5a-42c1-a92a-38e5e6733c8f' class='xr-index-data-in' type='checkbox'/><label for='index-938ffefc-eb5a-42c1-a92a-38e5e6733c8f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([              -90.0,  -88.10526315789474,  -86.21052631578948,
+         -84.3157894736842,  -82.42105263157895,  -80.52631578947368,
+        -78.63157894736842,  -76.73684210526316,  -74.84210526315789,
+        -72.94736842105263,  -71.05263157894737,  -69.15789473684211,
+        -67.26315789473685,  -65.36842105263158, -63.473684210526315,
+       -61.578947368421055, -59.684210526315795,  -57.78947368421053,
+        -55.89473684210527,               -54.0,  -52.10526315789474,
+        -50.21052631578947,  -48.31578947368421,  -46.42105263157895,
+       -44.526315789473685, -42.631578947368425,  -40.73684210526316,
+         -38.8421052631579,  -36.94736842105264,  -35.05263157894737,
+        -33.15789473684211, -31.263157894736842, -29.368421052631582,
+       -27.473684210526322, -25.578947368421055, -23.684210526315795,
+       -21.789473684210535,  -19.89473684210526,               -18.0,
+        -16.10526315789474,  -14.21052631578948,  -12.31578947368422,
+       -10.421052631578945,  -8.526315789473685,  -6.631578947368425,
+        -4.736842105263165, -2.8421052631579045, -0.9473684210526301,
+        0.9473684210526301,  2.8421052631578902,    4.73684210526315,
+         6.631578947368411,   8.526315789473685,  10.421052631578945,
+        12.315789473684205,  14.210526315789465,  16.105263157894726,
+                      18.0,   19.89473684210526,   21.78947368421052,
+         23.68421052631578,   25.57894736842104,  27.473684210526315,
+        29.368421052631575,  31.263157894736835,  33.157894736842096,
+        35.052631578947356,   36.94736842105263,   38.84210526315789,
+         40.73684210526315,   42.63157894736841,   44.52631578947367,
+         46.42105263157893,   48.31578947368419,   50.21052631578948,
+         52.10526315789474,                54.0,   55.89473684210526,
+         57.78947368421052,   59.68421052631578,   61.57894736842104,
+          63.4736842105263,   65.36842105263156,   67.26315789473682,
+         69.15789473684211,   71.05263157894737,   72.94736842105263,
+         74.84210526315789,   76.73684210526315,   78.63157894736841,
+         80.52631578947367,   82.42105263157893,   84.31578947368419,
+         86.21052631578945,   88.10526315789474,                90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d2d8b648-b942-4086-877f-64848dba7677' class='xr-index-data-in' type='checkbox'/><label for='index-d2d8b648-b942-4086-877f-64848dba7677' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.0,   2.5,   5.0,   7.5,  10.0,  12.5,  15.0,  17.5,  20.0,  22.5,
+       ...
+       335.0, 337.5, 340.0, 342.5, 345.0, 347.5, 350.0, 352.5, 355.0, 357.5],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=144))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-42ec8893-285d-4063-899d-498012cca2e3' class='xr-index-data-in' type='checkbox'/><label for='index-42ec8893-285d-4063-899d-498012cca2e3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,
+             1850-04-16 00:00:00, 1850-05-16 12:00:00, 1850-06-16 00:00:00,
+             1850-07-16 12:00:00, 1850-08-16 12:00:00, 1850-09-16 00:00:00,
+             1850-10-16 12:00:00,
+             ...
+             2014-03-16 12:00:00, 2014-04-16 00:00:00, 2014-05-16 12:00:00,
+             2014-06-16 00:00:00, 2014-07-16 12:00:00, 2014-08-16 12:00:00,
+             2014-09-16 00:00:00, 2014-10-16 12:00:00, 2014-11-16 00:00:00,
+             2014-12-16 12:00:00],
+            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2a11e953-0839-4697-9436-51600baf9acf' class='xr-index-data-in' type='checkbox'/><label for='index-2a11e953-0839-4697-9436-51600baf9acf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4f928d45-6df3-4efe-841f-45ea08d37338' class='xr-index-data-in' type='checkbox'/><label for='index-4f928d45-6df3-4efe-841f-45ea08d37338' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3fb8dc2c-430c-4bb7-97a2-d9ad9606c2f2' class='xr-section-summary-in' type='checkbox'  ><label for='section-3fb8dc2c-430c-4bb7-97a2-d9ad9606c2f2' class='xr-section-summary' >Attributes: <span>(65)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>Hybrid-restart from year 1600-01-01 of piControl</dd><dt><span>branch_time :</span></dt><dd>0.0</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>430335.0</dd><dt><span>cmor_version :</span></dt><dd>3.5.0</dd><dt><span>contact :</span></dt><dd>Please send any requests or bug reports to noresm-ncc@met.no.</dd><dt><span>creation_date :</span></dt><dd>2019-08-15T12:42:21Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.31</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCC.NorESM2-LM.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>finite-volume grid with 1.9x2.5 degree lat/lon resolution</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2019-08-15T12:42:21Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>NorESM Climate modeling Consortium consisting of CICERO (Center for International Climate and Environmental Research, Oslo 0349), MET-Norway (Norwegian Meteorological Institute, Oslo 0313), NERSC (Nansen Environmental and Remote Sensing Center, Bergen 5006), NILU (Norwegian Institute for Air Research, Kjeller 2027), UiB (University of Bergen, Bergen 5007), UiO (University of Oslo, Oslo 0313) and UNI (Uni Research, Bergen 5008), Norway. Mailing address: NCC, c/o MET-Norway, Henrik Mohns plass 1, Oslo 0313, Norway</dd><dt><span>institution_id :</span></dt><dd>NCC</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by NCC is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https:///pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_id :</span></dt><dd>NorESM2-LM</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>NorESM2-LM</dd><dt><span>parent_sub_experiment_id :</span></dt><dd>none</dd><dt><span>parent_time_units :</span></dt><dd>days since 0421-01-01</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>N/A</dd><dt><span>source :</span></dt><dd>NorESM2-LM (2017): 
+aerosol: OsloAero
+atmos: CAM-OSLO (2 degree resolution; 144 x 96; 32 levels; top level 3 mb)
+atmosChem: OsloChemSimp
+land: CLM
+landIce: CISM
+ocean: MICOM (1 degree resolution; 360 x 384; 70 levels; top grid cell minimum 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data])
+ocnBgchem: HAMOCC
+seaIce: CICE</dd><dt><span>source_id :</span></dt><dd>NorESM2-LM</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>status :</span></dt><dd>2020-04-30;created; by gcs.cmip6.ldeo@gmail.com</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(24 July 2019) MD5:08e314340b9dd440c36c1b8e484514f4</dd><dt><span>title :</span></dt><dd>NorESM2-LM output prepared for CMIP6</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/2486cf87-033c-4848-ab3e-e828c3b7c759
+hdl:21.14100/8d2ec216-30d3-4f90-8664-7cf75e29780b
+hdl:21.14100/9f798305-d0cf-4eac-89b0-b13dc25574ca
+hdl:21.14100/e0da9277-4784-446b-b3b5-ba33bb18cc3a
+hdl:21.14100/ca48487c-955a-4b15-9582-5ce55ce39c73
+hdl:21.14100/fc7602aa-fd09-49d8-94c6-e619622c211b
+hdl:21.14100/cd51a9c2-0a94-45b2-8d9b-59bcb3467214
+hdl:21.14100/9b7ad334-1217-4229-98e8-b5a9287c0e5e
+hdl:21.14100/043ca527-40c7-451f-990b-ccc94720f612
+hdl:21.14100/a9613498-ea0d-4be4-97e8-77661872798d
+hdl:21.14100/52699832-d86c-491b-a0a4-2f27d9ee4d69
+hdl:21.14100/358c4a18-33b2-4c44-bd30-f6125a4df63c
+hdl:21.14100/77254eaf-90ca-44e7-9a3c-763a840e188f
+hdl:21.14100/62aed49c-6ca5-4027-80fe-4ddd99af575a
+hdl:21.14100/83ffe172-769b-42b1-b979-b92d768f60fd
+hdl:21.14100/91a8c4e2-d33b-4b87-a978-0247d8112ef3
+hdl:21.14100/e8fb384f-d5a7-41e1-bf12-b8de3e2ffb80</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/2486cf87-033c-4848-ab3e-e828c3b7c759
+hdl:21.14100/8d2ec216-30d3-4f90-8664-7cf75e29780b
+hdl:21.14100/9f798305-d0cf-4eac-89b0-b13dc25574ca
+hdl:21.14100/e0da9277-4784-446b-b3b5-ba33bb18cc3a
+hdl:21.14100/ca48487c-955a-4b15-9582-5ce55ce39c73
+hdl:21.14100/fc7602aa-fd09-49d8-94c6-e619622c211b
+hdl:21.14100/cd51a9c2-0a94-45b2-8d9b-59bcb3467214
+hdl:21.14100/9b7ad334-1217-4229-98e8-b5a9287c0e5e
+hdl:21.14100/043ca527-40c7-451f-990b-ccc94720f612
+hdl:21.14100/a9613498-ea0d-4be4-97e8-77661872798d
+hdl:21.14100/52699832-d86c-491b-a0a4-2f27d9ee4d69
+hdl:21.14100/358c4a18-33b2-4c44-bd30-f6125a4df63c
+hdl:21.14100/77254eaf-90ca-44e7-9a3c-763a840e188f
+hdl:21.14100/62aed49c-6ca5-4027-80fe-4ddd99af575a
+hdl:21.14100/83ffe172-769b-42b1-b979-b92d768f60fd
+hdl:21.14100/91a8c4e2-d33b-4b87-a978-0247d8112ef3
+hdl:21.14100/e8fb384f-d5a7-41e1-bf12-b8de3e2ffb80</dd><dt><span>version_id :</span></dt><dd>v20190815</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;tas&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCC</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>NorESM2-LM</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>Amon</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>tas</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historical/r1i1p1f1/Amon/tas/gn/v20190815/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190815</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCC.NorESM2-LM.historical.Amon.gn</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<p>Plot the first timestep</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">projection</span> <span class="o">=</span> <span class="n">ccrs</span><span class="o">.</span><span class="n">Mercator</span><span class="p">(</span><span class="n">central_longitude</span><span class="o">=-</span><span class="mi">10</span><span class="p">)</span>
+
+<span class="n">f</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">subplot_kw</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span><span class="n">projection</span><span class="o">=</span><span class="n">projection</span><span class="p">))</span>
+
+<span class="n">dset</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">time</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">transform</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">PlateCarree</span><span class="p">(),</span> <span class="n">cbar_kwargs</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span><span class="n">shrink</span><span class="o">=</span><span class="mf">0.7</span><span class="p">),</span> <span class="n">cmap</span><span class="o">=</span><span class="s1">&#39;coolwarm&#39;</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">coastlines</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;cartopy.mpl.feature_artist.FeatureArtist at 0x7fb9527cac50&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/c62d39a9587c386e8bf18f627664ea1fcf29f92c54d14a01086aaf2c9860372a.png" src="../../../_images/c62d39a9587c386e8bf18f627664ea1fcf29f92c54d14a01086aaf2c9860372a.png" />
+</div>
+</div>
+</section>
+<section id="compute-weighted-mean">
+<h2>Compute weighted mean<a class="headerlink" href="#compute-weighted-mean" title="Link to this heading">#</a></h2>
+<ol class="arabic simple">
+<li><p>Creating weights: for a rectangular grid the cosine of the latitude is proportional to the grid cell area.</p></li>
+<li><p>Compute weighted mean values</p></li>
+</ol>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">computeWeightedMean</span><span class="p">(</span><span class="n">ds</span><span class="p">):</span>
+    <span class="c1"># Compute weights based on the xarray you pass</span>
+    <span class="n">weights</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">deg2rad</span><span class="p">(</span><span class="n">ds</span><span class="o">.</span><span class="n">lat</span><span class="p">))</span>
+    <span class="n">weights</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;weights&quot;</span>
+    <span class="c1"># Compute weighted mean</span>
+    <span class="n">air_weighted</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">weighted</span><span class="p">(</span><span class="n">weights</span><span class="p">)</span>
+    <span class="n">weighted_mean</span> <span class="o">=</span> <span class="n">air_weighted</span><span class="o">.</span><span class="n">mean</span><span class="p">((</span><span class="s2">&quot;lon&quot;</span><span class="p">,</span> <span class="s2">&quot;lat&quot;</span><span class="p">))</span>
+    <span class="k">return</span> <span class="n">weighted_mean</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="compute-weighted-average-over-the-entire-globe">
+<h2>Compute weighted average over the entire globe<a class="headerlink" href="#compute-weighted-average-over-the-entire-globe" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">weighted_mean</span> <span class="o">=</span> <span class="n">computeWeightedMean</span><span class="p">(</span><span class="n">dset</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="comparison-with-unweighted-mean">
+<h2>Comparison with unweighted mean<a class="headerlink" href="#comparison-with-unweighted-mean" title="Link to this heading">#</a></h2>
+<ul class="simple">
+<li><p>We select a time range</p></li>
+<li><p>Note how the weighted mean temperature is higher than the unweighted.</p></li>
+</ul>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">weighted_mean</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">time</span><span class="o">=</span><span class="nb">slice</span><span class="p">(</span><span class="s1">&#39;2000-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2010-01-01&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="s2">&quot;weighted&quot;</span><span class="p">)</span>
+<span class="n">dset</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">time</span><span class="o">=</span><span class="nb">slice</span><span class="p">(</span><span class="s1">&#39;2000-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2010-01-01&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">mean</span><span class="p">((</span><span class="s2">&quot;lon&quot;</span><span class="p">,</span> <span class="s2">&quot;lat&quot;</span><span class="p">))</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="s2">&quot;unweighted&quot;</span><span class="p">)</span>
+
+<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7fb9516e4110&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/05abc347535f613ad6ad87c928ecc5df8d00ffd9f29ea431d4818aa55d1b77ca.png" src="../../../_images/05abc347535f613ad6ad87c928ecc5df8d00ffd9f29ea431d4818aa55d1b77ca.png" />
+</div>
+</div>
+</section>
+<section id="compute-weigted-arctic-average">
+<h2>Compute Weigted arctic average<a class="headerlink" href="#compute-weigted-arctic-average" title="Link to this heading">#</a></h2>
+<p>Let’s try to also take only the data above 60$^\circ$</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">weighted_mean</span> <span class="o">=</span> <span class="n">computeWeightedMean</span><span class="p">(</span><span class="n">dset</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">dset</span><span class="p">[</span><span class="s1">&#39;lat&#39;</span><span class="p">]</span><span class="o">&gt;</span><span class="mf">60.</span><span class="p">))</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">weighted_mean</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">time</span><span class="o">=</span><span class="nb">slice</span><span class="p">(</span><span class="s1">&#39;2000-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2010-01-01&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="s2">&quot;weighted&quot;</span><span class="p">)</span>
+<span class="n">dset</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">dset</span><span class="p">[</span><span class="s1">&#39;lat&#39;</span><span class="p">]</span><span class="o">&gt;</span><span class="mf">60.</span><span class="p">)</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">time</span><span class="o">=</span><span class="nb">slice</span><span class="p">(</span><span class="s1">&#39;2000-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2010-01-01&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">mean</span><span class="p">((</span><span class="s2">&quot;lon&quot;</span><span class="p">,</span> <span class="s2">&quot;lat&quot;</span><span class="p">))</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="s2">&quot;unweighted&quot;</span><span class="p">)</span>
+
+<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7fb9505cf450&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/2e300fdb9e3d686b4e6129664057b8ccab1ec2c92c3ca1b340fbb103fda5d255.png" src="../../../_images/2e300fdb9e3d686b4e6129664057b8ccab1ec2c92c3ca1b340fbb103fda5d255.png" />
+</div>
+</div>
+</section>
+</section>
+
+
+                </article>
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+    <i class="fa-solid fa-list"></i> Contents
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+  <nav class="bd-toc-nav page-toc">
+    <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#import-python-packages">Import python packages</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#search-data">Search data</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#create-dictionary-from-the-list-of-datasets-we-found">Create dictionary from the list of datasets we found</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#compute-weighted-mean">Compute weighted mean</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#compute-weighted-average-over-the-entire-globe">Compute weighted average over the entire globe</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#comparison-with-unweighted-mean">Comparison with unweighted mean</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#compute-weigted-arctic-average">Compute Weigted arctic average</a></li>
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+<div id="jb-print-docs-body" class="onlyprint">
+    <h1>Using cartopy and projections for plotting</h1>
+    <!-- Table of contents -->
+    <div id="print-main-content">
+        <div id="jb-print-toc">
+            
+            <div>
+                <h2> Contents </h2>
+            </div>
+            <nav aria-label="Page">
+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#open-era5-dataset">Open ERA5 dataset</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#reading-and-browsing-the-catalog">Reading and browsing the catalog</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#browsing-the-catalog-compering-the-change-in-aod-over-the-historical-period-across-cmip6-models">Browsing the catalog: Compering the change in AOD over the historical period across CMIP6 models</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#get-metadata">Get metadata</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#get-variable-metadata-air-temperature-at-2-metres">Get variable metadata (air_temperature_at_2_metres)</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#select-time">Select time</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#visualize-data">Visualize data</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#simple-visualization-from-xarray-plotting-method">Simple visualization from xarray plotting method</a><ul class="nav section-nav flex-column">
+<li class="toc-h4 nav-item toc-entry"><a class="reference internal nav-link" href="#same-plot-but-with-local-file">Same plot but with local file</a></li>
+</ul>
+</li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#customize-plot">Customize plot</a><ul class="nav section-nav flex-column">
+<li class="toc-h4 nav-item toc-entry"><a class="reference internal nav-link" href="#set-the-size-of-the-figure-and-add-coastlines">Set the size of the figure and add coastlines</a></li>
+<li class="toc-h4 nav-item toc-entry"><a class="reference internal nav-link" href="#change-plotting-projection">Change plotting projection</a></li>
+<li class="toc-h4 nav-item toc-entry"><a class="reference internal nav-link" href="#choose-extent-of-values">Choose extent of values</a></li>
+</ul>
+</li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#combine-plots-with-different-projections">Combine plots with different projections</a></li>
+</ul>
+</li>
+</ul>
+            </nav>
+        </div>
+    </div>
+</div>
+
+              
+                
+<div id="searchbox"></div>
+                <article class="bd-article">
+                  
+  <section id="using-cartopy-and-projections-for-plotting">
+<h1>Using cartopy and projections for plotting<a class="headerlink" href="#using-cartopy-and-projections-for-plotting" title="Link to this heading">#</a></h1>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">s3fs</span>
+<span class="kn">import</span> <span class="nn">xarray</span> <span class="k">as</span> <span class="nn">xr</span>
+<span class="kn">import</span> <span class="nn">cartopy.crs</span> <span class="k">as</span> <span class="nn">ccrs</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+</pre></div>
+</div>
+</div>
+</div>
+<section id="open-era5-dataset">
+<h2>Open ERA5 dataset<a class="headerlink" href="#open-era5-dataset" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Importing the required packages</span>
+<span class="kn">import</span> <span class="nn">intake</span>
+<span class="kn">import</span> <span class="nn">xarray</span> <span class="k">as</span> <span class="nn">xr</span>
+<span class="kn">import</span> <span class="nn">intake_esm</span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">from</span> <span class="nn">dask.distributed</span> <span class="kn">import</span> <span class="n">Client</span><span class="p">,</span> <span class="n">LocalCluster</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="reading-and-browsing-the-catalog">
+<h2>Reading and browsing the catalog<a class="headerlink" href="#reading-and-browsing-the-catalog" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Open the catalog</span>
+
+<span class="c1"># col = intake.open_esm_datastore(&#39;https://storage.googleapis.com/cmip6/pangeo-cmip6.json&#39;) # Remote Pangeo</span>
+
+<span class="n">col</span> <span class="o">=</span> <span class="n">intake</span><span class="o">.</span><span class="n">open_esm_datastore</span><span class="p">(</span><span class="s1">&#39;/mnt/craas1-ns9989k-geo4992/data/cmip6.json&#39;</span><span class="p">)</span> <span class="c1"># Local data stored on NIRD</span>
+<span class="n">col</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><p><strong>cmip6 catalog with 155 dataset(s) from 536945 asset(s)</strong>:</p> <div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>unique</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>variable_id</th>
+      <td>583</td>
+    </tr>
+    <tr>
+      <th>table_id</th>
+      <td>24</td>
+    </tr>
+    <tr>
+      <th>source_id</th>
+      <td>75</td>
+    </tr>
+    <tr>
+      <th>experiment_id</th>
+      <td>94</td>
+    </tr>
+    <tr>
+      <th>member_id</th>
+      <td>190</td>
+    </tr>
+    <tr>
+      <th>grid_label</th>
+      <td>11</td>
+    </tr>
+    <tr>
+      <th>time_range</th>
+      <td>9100</td>
+    </tr>
+    <tr>
+      <th>activity_id</th>
+      <td>18</td>
+    </tr>
+    <tr>
+      <th>institution_id</th>
+      <td>35</td>
+    </tr>
+    <tr>
+      <th>version</th>
+      <td>577</td>
+    </tr>
+    <tr>
+      <th>path</th>
+      <td>536945</td>
+    </tr>
+    <tr>
+      <th>dcpp_init_year</th>
+      <td>0</td>
+    </tr>
+    <tr>
+      <th>derived_variable_id</th>
+      <td>0</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+<section id="browsing-the-catalog-compering-the-change-in-aod-over-the-historical-period-across-cmip6-models">
+<h3>Browsing the catalog: Compering the change in AOD over the historical period across CMIP6 models<a class="headerlink" href="#browsing-the-catalog-compering-the-change-in-aod-over-the-historical-period-across-cmip6-models" title="Link to this heading">#</a></h3>
+<p>The keywords when browsing is columns of the table.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">col</span> <span class="o">=</span> <span class="n">col</span><span class="o">.</span><span class="n">search</span><span class="p">(</span>
+    <span class="n">experiment_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;historical&#39;</span><span class="p">],</span>
+    <span class="n">source_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;CESM2&#39;</span><span class="p">],</span> 
+    <span class="n">table_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Amon&#39;</span><span class="p">],</span>
+    <span class="n">variable_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">,],</span> 
+    <span class="n">member_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;r1i1p1f1&#39;</span><span class="p">]</span>
+    
+<span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Models available for this request:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">col</span><span class="o">.</span><span class="n">unique</span><span class="p">()[</span><span class="s1">&#39;source_id&#39;</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&#39;CESM2&#39;]
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># dataset_dict = col.to_dataset_dict()</span>
+<span class="n">dataset_dict</span> <span class="o">=</span> <span class="n">col</span><span class="o">.</span><span class="n">to_dataset_dict</span><span class="p">(</span><span class="n">xarray_open_kwargs</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;use_cftime&#39;</span><span class="p">:</span><span class="kc">True</span><span class="p">,</span> <span class="s1">&#39;chunks&#39;</span><span class="p">:{</span><span class="s1">&#39;time&#39;</span><span class="p">:</span><span class="mi">48</span><span class="p">}},</span> 
+                           <span class="n">aggregate</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+                               <span class="c1">#preprocess=calculate_global_avg_and_resample,</span>
+                                   <span class="c1">#skip_on_error=True,</span>
+                            <span class="n">xarray_combine_by_coords</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;combine_attrs&#39;</span><span class="p">:</span> <span class="s1">&#39;override&#39;</span><span class="p">}</span>
+                            
+                          <span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--&gt; The keys in the returned dictionary of datasets are constructed as follows:
+	&#39;activity_id.institution_id&#39;
+</pre></div>
+</div>
+<div class="output text_html">
+<style>
+    /* Turns off some styling */
+    progress {
+        /* gets rid of default border in Firefox and Opera. */
+        border: none;
+        /* Needs to be in here for Safari polyfill so background images work as expected. */
+        background-size: auto;
+    }
+    progress:not([value]), progress:not([value])::-webkit-progress-bar {
+        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);
+    }
+    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {
+        background: #F44336;
+    }
+</style>
+</div><div class="output text_html">
+    <div>
+      <progress value='1' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>
+      100.00% [1/1 00:00&lt;00:00]
+    </div>
+    </div><div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/opt/conda/envs/pangeo-notebook/lib/python3.11/site-packages/xarray/conventions.py:286: SerializationWarning: variable &#39;tas&#39; has multiple fill values {1e+20, 1e+20} defined, decoding all values to NaN.
+  var = coder.decode(var, name=name)
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dset</span> <span class="o">=</span> <span class="n">dataset_dict</span><span class="p">[</span><span class="s1">&#39;CMIP.NCAR&#39;</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+</section>
+<section id="get-metadata">
+<h2>Get metadata<a class="headerlink" href="#get-metadata" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dset</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><div><svg style="position: absolute; width: 0; height: 0; overflow: hidden">
+<defs>
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+.xr-header > div,
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+  display: inline;
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+  margin-bottom: 0;
+}
+
+.xr-obj-type,
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+  margin-left: 2px;
+  margin-right: 10px;
+}
+
+.xr-obj-type {
+  color: var(--xr-font-color2);
+}
+
+.xr-sections {
+  padding-left: 0 !important;
+  display: grid;
+  grid-template-columns: 150px auto auto 1fr 20px 20px;
+}
+
+.xr-section-item {
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+}
+
+.xr-section-item input {
+  display: none;
+}
+
+.xr-section-item input + label {
+  color: var(--xr-disabled-color);
+}
+
+.xr-section-item input:enabled + label {
+  cursor: pointer;
+  color: var(--xr-font-color2);
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+  grid-column: 1 / -1;
+  margin-bottom: 5px;
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+  padding: 0;
+  margin: 0;
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+  margin-bottom: 0;
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 438MB
+Dimensions:    (member_id: 1, time: 1980, lat: 192, lon: 288, nbnd: 2)
+Coordinates:
+  * lat        (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0
+  * lon        (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8
+  * time       (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00
+  * member_id  (member_id) object 8B &#x27;r1i1p1f1&#x27;
+Dimensions without coordinates: nbnd
+Data variables:
+    tas        (member_id, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 48, 192, 288), meta=np.ndarray&gt;
+    time_bnds  (time, nbnd) object 32kB dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;
+    lat_bnds   (lat, nbnd) float32 2kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;
+    lon_bnds   (lon, nbnd) float32 2kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+Attributes: (12/59)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    case_id:                          15
+    cesm_casename:                    b.e21.BHIST.f09_g17.CMIP6-historical.001
+    contact:                          cesm_cmip6@ucar.edu
+    creation_date:                    2019-01-16T23:34:05Z
+    ...                               ...
+    intake_esm_attrs:activity_id:     CMIP
+    intake_esm_attrs:institution_id:  NCAR
+    intake_esm_attrs:version:         v20190308
+    intake_esm_attrs:path:            /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...
+    intake_esm_attrs:_data_format_:   netcdf
+    intake_esm_dataset_key:           CMIP.NCAR</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b4f3183e-9e36-4d6a-b5c7-f4ca1ed1cb1f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b4f3183e-9e36-4d6a-b5c7-f4ca1ed1cb1f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-319f3381-98b9-4c44-8fc1-d7325a90532c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-319f3381-98b9-4c44-8fc1-d7325a90532c' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-a9f36114-1eaa-46fe-82fb-42802a8a35c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9f36114-1eaa-46fe-82fb-42802a8a35c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d55b032-64ab-426c-86e1-ea2cb89ee637' class='xr-var-data-in' type='checkbox'><label for='data-9d55b032-64ab-426c-86e1-ea2cb89ee637' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-4d38248d-a2f7-43a3-aff6-31d52888754a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d38248d-a2f7-43a3-aff6-31d52888754a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fba6e39-b3b5-43b2-83fc-f11e20d54a01' class='xr-var-data-in' type='checkbox'><label for='data-4fba6e39-b3b5-43b2-83fc-f11e20d54a01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-5fb64c82-c94f-4d58-8161-a251c161f19b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fb64c82-c94f-4d58-8161-a251c161f19b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbc1ffd6-83b8-4546-805b-029a90a5f987' class='xr-var-data-in' type='checkbox'><label for='data-dbc1ffd6-83b8-4546-805b-029a90a5f987' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-27866ed2-3741-4d60-ba0f-f59b2df0ef03' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-27866ed2-3741-4d60-ba0f-f59b2df0ef03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52bd08b8-b29a-4f5b-9486-a60bc35004e2' class='xr-var-data-in' type='checkbox'><label for='data-52bd08b8-b29a-4f5b-9486-a60bc35004e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d9e1f21-6434-47b8-9d50-18ff76b4d9a7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7d9e1f21-6434-47b8-9d50-18ff76b4d9a7' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 48, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-30d32fca-e22d-4064-8d58-f82f149646dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30d32fca-e22d-4064-8d58-f82f149646dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13e5f9a4-5de3-4f2f-9476-ab2c1a7f67ec' class='xr-var-data-in' type='checkbox'><label for='data-13e5f9a4-5de3-4f2f-9476-ab2c1a7f67ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 417.66 MiB </td>
+                        <td> 10.12 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1980, 192, 288) </td>
+                        <td> (1, 48, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 42 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
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+  <line x1="206" y1="70" x2="206" y2="109" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="165.58823529411765,70.58823529411765 206.14509559394764,70.58823529411765 206.14509559394764,109.01386754281697 165.58823529411765,109.01386754281697" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="185.866665" y="129.013868" font-size="1.0rem" font-weight="100" text-anchor="middle" >288</text>
+  <text x="226.145096" y="89.801051" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,226.145096,89.801051)">192</text>
+  <text x="120.294118" y="93.719750" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(45,120.294118,93.719750)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(48, 2), meta=np.ndarray&gt;</div><input id='attrs-ba86a7b2-970e-4a7d-ab32-05f1d36a1f4f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba86a7b2-970e-4a7d-ab32-05f1d36a1f4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5f16676-a339-441c-a86d-30cb4bf24a31' class='xr-var-data-in' type='checkbox'><label for='data-f5f16676-a339-441c-a86d-30cb4bf24a31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 30.94 kiB </td>
+                        <td> 768 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1980, 2) </td>
+                        <td> (48, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 42 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="5" x2="25" y2="5" />
+  <line x1="0" y1="11" x2="25" y2="11" />
+  <line x1="0" y1="17" x2="25" y2="17" />
+  <line x1="0" y1="23" x2="25" y2="23" />
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+  <line x1="0" y1="107" x2="25" y2="107" />
+  <line x1="0" y1="113" x2="25" y2="113" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#8B4903A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, nbnd)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;</div><input id='attrs-730e4497-953a-40f8-a67a-884b3d0db34d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-730e4497-953a-40f8-a67a-884b3d0db34d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3cd890b-b560-40a4-b4bc-1f7c5a29b8fe' class='xr-var-data-in' type='checkbox'><label for='data-e3cd890b-b560-40a4-b4bc-1f7c5a29b8fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 1.50 kiB </td>
+                        <td> 1.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (192, 2) </td>
+                        <td> (192, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.60913412115106,0.0 25.60913412115106,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.804567" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.609134" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.609134,60.000000)">192</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-0ec9ce2d-633b-4edd-adb5-19341a1c61dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ec9ce2d-633b-4edd-adb5-19341a1c61dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c566b42-2f59-4a97-80ed-107bd6771b23' class='xr-var-data-in' type='checkbox'><label for='data-3c566b42-2f59-4a97-80ed-107bd6771b23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 2.25 kiB </td>
+                        <td> 2.25 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-b3629ddc-9b98-4283-9aaf-fc1effe83f93' class='xr-section-summary-in' type='checkbox'  ><label for='section-b3629ddc-9b98-4283-9aaf-fc1effe83f93' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b57a7f8c-5f3c-4488-8990-93aaa4b4afc9' class='xr-index-data-in' type='checkbox'/><label for='index-b57a7f8c-5f3c-4488-8990-93aaa4b4afc9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,
+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1be18e37-2795-4d2b-9aaf-67195dbe3424' class='xr-index-data-in' type='checkbox'/><label for='index-1be18e37-2795-4d2b-9aaf-67195dbe3424' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-43f0be5c-4e31-429f-9aa3-393d47783219' class='xr-index-data-in' type='checkbox'/><label for='index-43f0be5c-4e31-429f-9aa3-393d47783219' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,
+             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,
+             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,
+             1850-10-15 12:00:00,
+             ...
+             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,
+             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,
+             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,
+             2014-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d73a17c2-6162-4e41-92f3-3424b146cb08' class='xr-index-data-in' type='checkbox'/><label for='index-d73a17c2-6162-4e41-92f3-3424b146cb08' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-582ae9e0-8afd-4819-9d44-f78267c08713' class='xr-section-summary-in' type='checkbox'  ><label for='section-582ae9e0-8afd-4819-9d44-f78267c08713' class='xr-section-summary' >Attributes: <span>(59)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T23:34:05Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/d9a7225a-49c3-4470-b7ab-a8180926f839</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;tas&#x27;]</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>tas</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>Amon</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:time_range :</span></dt><dd>185001-201412</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>v20190308</dd><dt><span>intake_esm_attrs:path :</span></dt><dd>/mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/Amon/tas/gn/v20190308/tas_Amon_CESM2_historical_r1i1p1f1_gn_185001-201412.nc</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>netcdf</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<section id="get-variable-metadata-air-temperature-at-2-metres">
+<h3>Get variable metadata (air_temperature_at_2_metres)<a class="headerlink" href="#get-variable-metadata-air-temperature-at-2-metres" title="Link to this heading">#</a></h3>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dset</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">]</span>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (member_id: 1, time: 1980, lat: 192, lon: 288)&gt; Size: 438MB
+dask.array&lt;broadcast_to, shape=(1, 1980, 192, 288), dtype=float32, chunksize=(1, 48, 192, 288), chunktype=numpy.ndarray&gt;
+Coordinates:
+  * lat        (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0
+  * lon        (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8
+  * time       (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00
+  * member_id  (member_id) object 8B &#x27;r1i1p1f1&#x27;
+Attributes: (12/19)
+    cell_measures:  area: areacella
+    cell_methods:   area: time: mean
+    comment:        near-surface (usually, 2 meter) air temperature
+    description:    near-surface (usually, 2 meter) air temperature
+    frequency:      mon
+    id:             tas
+    ...             ...
+    time_label:     time-mean
+    time_title:     Temporal mean
+    title:          Near-Surface Air Temperature
+    type:           real
+    units:          K
+    variable_id:    tas</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6a6f527b-e2f7-4aa1-bc0e-28c1195649fe' class='xr-array-in' type='checkbox' checked><label for='section-6a6f527b-e2f7-4aa1-bc0e-28c1195649fe' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 48, 192, 288), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>
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+                    
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+  <line x1="25" y1="0" x2="25" y2="25" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,25.412616514582485 0.0,25.412616514582485" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="45.412617" font-size="1.0rem" font-weight="100" text-anchor="middle" >1</text>
+  <text x="45.412617" y="12.706308" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,45.412617,12.706308)">1</text>
+
+
+  <!-- Horizontal lines -->
+  <line x1="95" y1="0" x2="165" y2="70" style="stroke-width:2" />
+  <line x1="95" y1="38" x2="165" y2="109" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="95" y1="0" x2="95" y2="38" style="stroke-width:2" />
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+  <line x1="163" y1="68" x2="163" y2="106" />
+  <line x1="165" y1="70" x2="165" y2="109" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="95.0,0.0 165.58823529411765,70.58823529411765 165.58823529411765,109.01386754281697 95.0,38.42563224869931" style="fill:#8B4903A0;stroke-width:0"/>
+
+  <!-- Horizontal lines -->
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+  <line x1="96" y1="1" x2="137" y2="1" />
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+  <line x1="165" y1="70" x2="206" y2="70" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="95" y1="0" x2="165" y2="70" style="stroke-width:2" />
+  <line x1="135" y1="0" x2="206" y2="70" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="95.0,0.0 135.55686029983002,0.0 206.14509559394767,70.58823529411765 165.58823529411765,70.58823529411765" style="fill:#8B4903A0;stroke-width:0"/>
+
+  <!-- Horizontal lines -->
+  <line x1="165" y1="70" x2="206" y2="70" style="stroke-width:2" />
+  <line x1="165" y1="109" x2="206" y2="109" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="165" y1="70" x2="165" y2="109" style="stroke-width:2" />
+  <line x1="206" y1="70" x2="206" y2="109" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="165.58823529411765,70.58823529411765 206.14509559394764,70.58823529411765 206.14509559394764,109.01386754281697 165.58823529411765,109.01386754281697" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="185.866665" y="129.013868" font-size="1.0rem" font-weight="100" text-anchor="middle" >288</text>
+  <text x="226.145096" y="89.801051" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,226.145096,89.801051)">192</text>
+  <text x="120.294118" y="93.719750" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(45,120.294118,93.719750)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></div></li><li class='xr-section-item'><input id='section-26ff334d-b432-4041-948d-47865fcc9468' class='xr-section-summary-in' type='checkbox'  checked><label for='section-26ff334d-b432-4041-948d-47865fcc9468' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-3abdb9c8-42f6-41ec-8ff7-e26831ff02a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3abdb9c8-42f6-41ec-8ff7-e26831ff02a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1ebd11f-2331-48cb-a009-b9fe66e19d8c' class='xr-var-data-in' type='checkbox'><label for='data-e1ebd11f-2331-48cb-a009-b9fe66e19d8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-e515765a-4903-4b8e-b055-ad36f2cd1a67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e515765a-4903-4b8e-b055-ad36f2cd1a67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f25e12a-0f08-4d70-854e-0b06c93dc925' class='xr-var-data-in' type='checkbox'><label for='data-0f25e12a-0f08-4d70-854e-0b06c93dc925' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-c3293032-1842-45ad-9109-fb57b0b5663c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3293032-1842-45ad-9109-fb57b0b5663c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d37d595-189f-4766-b993-057c45db5e5f' class='xr-var-data-in' type='checkbox'><label for='data-8d37d595-189f-4766-b993-057c45db5e5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-e6810e1d-4ed8-45a2-961c-9166c250a7a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6810e1d-4ed8-45a2-961c-9166c250a7a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a495505-37ae-4946-982e-8e61dd5b2174' class='xr-var-data-in' type='checkbox'><label for='data-2a495505-37ae-4946-982e-8e61dd5b2174' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-315e02a3-33eb-4601-9b35-f269b6bd18f4' class='xr-section-summary-in' type='checkbox'  ><label for='section-315e02a3-33eb-4601-9b35-f269b6bd18f4' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bdd24540-a3b1-4fd3-86fc-6482317d84bd' class='xr-index-data-in' type='checkbox'/><label for='index-bdd24540-a3b1-4fd3-86fc-6482317d84bd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,
+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cf5f40a1-71b1-4ea9-9aa4-7612a6097553' class='xr-index-data-in' type='checkbox'/><label for='index-cf5f40a1-71b1-4ea9-9aa4-7612a6097553' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f65e320d-6d46-4ae8-815a-89d9873aafba' class='xr-index-data-in' type='checkbox'/><label for='index-f65e320d-6d46-4ae8-815a-89d9873aafba' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,
+             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,
+             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,
+             1850-10-15 12:00:00,
+             ...
+             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,
+             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,
+             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,
+             2014-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6e693a08-e4f7-456e-a618-c831e9fabfa9' class='xr-index-data-in' type='checkbox'/><label for='index-6e693a08-e4f7-456e-a618-c831e9fabfa9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b919d258-73e6-44be-927b-699daa3f456f' class='xr-section-summary-in' type='checkbox'  ><label for='section-b919d258-73e6-44be-927b-699daa3f456f' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div></li></ul></div></div></div></div>
+</div>
+</section>
+</section>
+<section id="select-time">
+<h2>Select time<a class="headerlink" href="#select-time" title="Link to this heading">#</a></h2>
+<ul class="simple">
+<li><p>Check time format when selecting a specific time</p></li>
+</ul>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">tas_plt</span> <span class="o">=</span> <span class="n">dset</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">time</span><span class="o">=</span><span class="nb">slice</span><span class="p">(</span><span class="s1">&#39;2013-01-01&#39;</span><span class="p">,</span><span class="s1">&#39;2014-01-01&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="s1">&#39;time&#39;</span><span class="p">)</span><span class="o">-</span><span class="mf">273.15</span>
+<span class="n">tas_plt</span><span class="o">.</span><span class="n">attrs</span><span class="p">[</span><span class="s1">&#39;units&#39;</span><span class="p">]</span> <span class="o">=</span><span class="s1">&#39;deg C&#39;</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">tas_plt</span> <span class="o">=</span> <span class="n">tas_plt</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="visualize-data">
+<h2>Visualize data<a class="headerlink" href="#visualize-data" title="Link to this heading">#</a></h2>
+<section id="simple-visualization-from-xarray-plotting-method">
+<h3>Simple visualization from xarray plotting method<a class="headerlink" href="#simple-visualization-from-xarray-plotting-method" title="Link to this heading">#</a></h3>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span> 
+<span class="n">tas_plt</span><span class="o">.</span><span class="n">load</span><span class="p">()</span>
+<span class="n">tas_plt</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span><span class="c1">#cmap = &#39;coolwarm&#39;)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 323 ms, sys: 27.9 ms, total: 351 ms
+Wall time: 352 ms
+</pre></div>
+</div>
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f792165c790&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/775e0817a0cfb6913529db1d9d0d7aa9c99c2d229c99b2d2a74c6d7caa208f67.png" src="../../../_images/775e0817a0cfb6913529db1d9d0d7aa9c99c2d229c99b2d2a74c6d7caa208f67.png" />
+</div>
+</div>
+<section id="same-plot-but-with-local-file">
+<h4>Same plot but with local file<a class="headerlink" href="#same-plot-but-with-local-file" title="Link to this heading">#</a></h4>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span> 
+<span class="n">tas_plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">cmap</span> <span class="o">=</span> <span class="s1">&#39;coolwarm&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 22.7 ms, sys: 1.84 ms, total: 24.6 ms
+Wall time: 23.8 ms
+</pre></div>
+</div>
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f7943263690&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/561ad834c348219ec22649b094811ebbc2cb578d05bc84201e86298880bb1377.png" src="../../../_images/561ad834c348219ec22649b094811ebbc2cb578d05bc84201e86298880bb1377.png" />
+</div>
+</div>
+</section>
+</section>
+<section id="customize-plot">
+<h3>Customize plot<a class="headerlink" href="#customize-plot" title="Link to this heading">#</a></h3>
+<section id="set-the-size-of-the-figure-and-add-coastlines">
+<h4>Set the size of the figure and add coastlines<a class="headerlink" href="#set-the-size-of-the-figure-and-add-coastlines" title="Link to this heading">#</a></h4>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span>
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">[</span><span class="mi">30</span><span class="p">,</span><span class="mi">13</span><span class="p">])</span>
+
+<span class="c1"># Set the projection to use for plotting</span>
+<span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">projection</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">PlateCarree</span><span class="p">())</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">coastlines</span><span class="p">()</span>
+
+<span class="c1"># Pass ax as an argument when plotting. Here we assume data is in the same coordinate reference system than the projection chosen for plotting</span>
+<span class="c1"># isel allows to select by indices instead of the time values</span>
+<span class="n">tas_plt</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">pcolormesh</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s1">&#39;coolwarm&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 402 ms, sys: 1.89 ms, total: 404 ms
+Wall time: 405 ms
+</pre></div>
+</div>
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;cartopy.mpl.geocollection.GeoQuadMesh at 0x7f7940407390&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/f97b0a53cfb2c11333984a983bd8999880f1850b5984576f6860aa0df8a90184.png" src="../../../_images/f97b0a53cfb2c11333984a983bd8999880f1850b5984576f6860aa0df8a90184.png" />
+</div>
+</div>
+</section>
+<section id="change-plotting-projection">
+<h4>Change plotting projection<a class="headerlink" href="#change-plotting-projection" title="Link to this heading">#</a></h4>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span>
+
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">,</span><span class="mi">10</span><span class="p">])</span>
+
+<span class="c1"># We&#39;re using cartopy and are plotting in Orthographic projection </span>
+<span class="c1"># (see documentation on cartopy)</span>
+<span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">projection</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">Orthographic</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">90</span><span class="p">))</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">coastlines</span><span class="p">()</span>
+
+<span class="c1"># We need to project our data to the new Orthographic projection and for this we use `transform`.</span>
+<span class="c1"># we set the original data projection in transform (here PlateCarree)</span>
+<span class="n">tas_plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">PlateCarree</span><span class="p">(),</span> <span class="n">cmap</span><span class="o">=</span><span class="s1">&#39;coolwarm&#39;</span><span class="p">)</span>
+
+<span class="c1"># One way to customize your title</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;CESM air temperature at 2 avg over 2013&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">18</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 57.7 ms, sys: 4.09 ms, total: 61.8 ms
+Wall time: 61.2 ms
+</pre></div>
+</div>
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Text(0.5, 1.0, &#39;CESM air temperature at 2 avg over 2013&#39;)
+</pre></div>
+</div>
+<img alt="../../../_images/9fe2f6633bd27f83b99ee0e73e1172936d18ec9b542ac2a3df0000a2878f38c6.png" src="../../../_images/9fe2f6633bd27f83b99ee0e73e1172936d18ec9b542ac2a3df0000a2878f38c6.png" />
+</div>
+</div>
+</section>
+<section id="choose-extent-of-values">
+<h4>Choose extent of values<a class="headerlink" href="#choose-extent-of-values" title="Link to this heading">#</a></h4>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span>
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">,</span><span class="mi">10</span><span class="p">])</span>
+
+<span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">projection</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">Orthographic</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">90</span><span class="p">))</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">coastlines</span><span class="p">()</span>
+
+<span class="c1"># Fix extent</span>
+<span class="n">minval</span> <span class="o">=</span> <span class="o">-</span><span class="mi">10</span>
+<span class="n">maxval</span> <span class="o">=</span> <span class="mi">20</span>
+
+<span class="c1"># pass extent with vmin and vmax parameters</span>
+<span class="n">tas_plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">vmin</span><span class="o">=</span><span class="n">minval</span><span class="p">,</span> <span class="n">vmax</span><span class="o">=</span><span class="n">maxval</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">PlateCarree</span><span class="p">(),</span> <span class="n">cmap</span><span class="o">=</span><span class="s1">&#39;coolwarm&#39;</span><span class="p">)</span>
+
+<span class="c1"># One way to customize your title</span>
+<span class="c1">#plt.title(&quot;ERA5 air temperature at 2 metres\n 30th June 2020 at 21:00 UTC&quot;, fontsize=18)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;CESM air temperature at 2 avg over 2013&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">18</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 53.2 ms, sys: 2.45 ms, total: 55.7 ms
+Wall time: 54.9 ms
+</pre></div>
+</div>
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Text(0.5, 1.0, &#39;CESM air temperature at 2 avg over 2013&#39;)
+</pre></div>
+</div>
+<img alt="../../../_images/dbf4c9d4db04395facf7ca0e4cb4ca98881a7f8c830c6aba9ef0232e96359fee.png" src="../../../_images/dbf4c9d4db04395facf7ca0e4cb4ca98881a7f8c830c6aba9ef0232e96359fee.png" />
+</div>
+</div>
+</section>
+</section>
+<section id="combine-plots-with-different-projections">
+<h3>Combine plots with different projections<a class="headerlink" href="#combine-plots-with-different-projections" title="Link to this heading">#</a></h3>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">%%time</span>
+<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">[</span><span class="mi">20</span><span class="p">,</span><span class="mi">10</span><span class="p">])</span>
+
+<span class="c1"># Fix extent</span>
+<span class="n">minval</span> <span class="o">=</span> <span class="o">-</span><span class="mi">10</span>
+<span class="n">maxval</span> <span class="o">=</span> <span class="mi">20</span>
+
+<span class="c1"># Plot 1 for Northern Hemisphere subplot argument (nrows, ncols, nplot)</span>
+<span class="c1"># here 1 row, 2 columns and 1st plot</span>
+<span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">projection</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">Orthographic</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">90</span><span class="p">))</span>
+
+<span class="c1"># Plot 2 for Southern Hemisphere</span>
+<span class="c1"># 2nd plot </span>
+<span class="n">ax2</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">projection</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">Orthographic</span><span class="p">(</span><span class="mi">180</span><span class="p">,</span> <span class="o">-</span><span class="mi">90</span><span class="p">))</span>
+
+<span class="n">tsel</span> <span class="o">=</span> <span class="mi">0</span>
+<span class="k">for</span> <span class="n">ax</span><span class="p">,</span><span class="n">t</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">([</span><span class="n">ax1</span><span class="p">,</span> <span class="n">ax2</span><span class="p">],</span> <span class="p">[</span><span class="s2">&quot;Northern&quot;</span><span class="p">,</span> <span class="s2">&quot;Southern&quot;</span><span class="p">]):</span>
+    <span class="nb">map</span> <span class="o">=</span> <span class="n">tas_plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">vmin</span><span class="o">=</span><span class="n">minval</span><span class="p">,</span> <span class="n">vmax</span><span class="o">=</span><span class="n">maxval</span><span class="p">,</span> 
+                                           <span class="n">transform</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">PlateCarree</span><span class="p">(),</span> 
+                                           <span class="n">cmap</span><span class="o">=</span><span class="s1">&#39;coolwarm&#39;</span><span class="p">,</span> 
+                                           <span class="n">add_colorbar</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">t</span> <span class="o">+</span> <span class="s2">&quot; Hemisphere </span><span class="se">\n</span><span class="s2">&quot;</span> <span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">coastlines</span><span class="p">()</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">gridlines</span><span class="p">()</span>
+
+<span class="c1"># Title for both plots</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s1">&#39;CESM air temperature at 2 avg over 2013&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
+
+
+<span class="n">cb_ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.325</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">,</span> <span class="mf">0.4</span><span class="p">,</span> <span class="mf">0.04</span><span class="p">])</span>
+
+<span class="n">cbar</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="nb">map</span><span class="p">,</span> <span class="n">cax</span><span class="o">=</span><span class="n">cb_ax</span><span class="p">,</span> <span class="n">extend</span><span class="o">=</span><span class="s1">&#39;both&#39;</span><span class="p">,</span> <span class="n">orientation</span><span class="o">=</span><span class="s1">&#39;horizontal&#39;</span><span class="p">,</span> <span class="n">fraction</span><span class="o">=</span><span class="mf">0.046</span><span class="p">,</span> <span class="n">pad</span><span class="o">=</span><span class="mf">0.04</span><span class="p">)</span>
+<span class="n">cbar</span><span class="o">.</span><span class="n">ax</span><span class="o">.</span><span class="n">tick_params</span><span class="p">(</span><span class="n">labelsize</span><span class="o">=</span><span class="mi">25</span><span class="p">)</span>
+<span class="n">cbar</span><span class="o">.</span><span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;K&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">25</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 98.4 ms, sys: 1.93 ms, total: 100 ms
+Wall time: 99.6 ms
+</pre></div>
+</div>
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Text(0, 0.5, &#39;K&#39;)
+</pre></div>
+</div>
+<img alt="../../../_images/37baf6723552741b214d14845d5885aea364e44804081ab2c3d4ef475cb76151.png" src="../../../_images/37baf6723552741b214d14845d5885aea364e44804081ab2c3d4ef475cb76151.png" />
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+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#open-era5-dataset">Open ERA5 dataset</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#reading-and-browsing-the-catalog">Reading and browsing the catalog</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#browsing-the-catalog-compering-the-change-in-aod-over-the-historical-period-across-cmip6-models">Browsing the catalog: Compering the change in AOD over the historical period across CMIP6 models</a></li>
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+<div id="jb-print-docs-body" class="onlyprint">
+    <h1>Some tips with xarray and pandas</h1>
+    <!-- Table of contents -->
+    <div id="print-main-content">
+        <div id="jb-print-toc">
+            
+            <div>
+                <h2> Contents </h2>
+            </div>
+            <nav aria-label="Page">
+                <ul class="visible nav section-nav flex-column">
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#">Some tips with xarray and pandas</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#print-hey-world">print(‘Hey world’)</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#what-are-pandas-and-xarray">What are pandas and xarray?</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#pandas">Pandas</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#xarray">Xarray</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#read-in-cmip6-data-we-will-skip-this-next-part-but-you-can-check-it-later-to-read-data">1. Read in CMIP6 data: We will skip this next part, but you can check it later to read data:</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#import-python-packages">Import python packages</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#open-cmip6-online-catalog">Open CMIP6 online catalog</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#search-corresponding-data">Search corresponding data</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#create-dictionary-from-the-list-of-datasets-we-found">Create dictionary from the list of datasets we found</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#open-dataset">Open dataset</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#reading-in-the-data-from-file">1.1 Reading in the data from file:</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#opening-multiple-files">Opening multiple files:</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#check-how-your-dataset-looks">2. Check how your dataset looks</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#different-types-of-information-data">Different types of information/data:</a></li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#sometimes-we-want-to-do-some-nice-tweaks-before-we-start">3. Sometimes we want to do some nice tweaks before we start:</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#selecting-data-and-super-quick-plotting">Selecting data and super quick plotting:</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#see-here-for-nice-overview">See here for nice overview</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#slice-in-time-the-sel-method">Slice in time: the sel method</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#isel-sel-index-selecting">isel, sel: index selecting</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#calculates-variables-and-assign-attributes">3.2 Calculates variables and assign attributes!</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#convert-longitude">3.3 Convert longitude:</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#the-easiest-interpolation-select-with-nearest-neighboor">4. The easiest interpolation: select with ‘nearest’ neighboor</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#super-quick-averaging-etc">Super quick averaging etc</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#mask-data-and-groupby-pick-out-seasons">Mask data and groupby: pick out seasons</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#controle-the-plot-visuals">Controle the plot visuals:</a></li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#plotting-with-cartopy">5. Plotting with cartopy</a></li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#global-average-weighted-means">6. Global average: weighted means!</a></li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#convert-to-pandas-do-some-random-fun-stuff">7. Convert to pandas &amp; do some random fun stuff:</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#pick-out-station">Pick out station:</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#resample">Resample:</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#lets-do-something-unnecesarily-complicated-d">lets do something unnecesarily complicated :D</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#qcut-cut">qcut, cut</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#convert-back-to-xarray-if-we-need">Convert back to xarray if we need:</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#mask-by-category">mask by category</a></li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
+
+            </nav>
+        </div>
+    </div>
+</div>
+
+              
+                
+<div id="searchbox"></div>
+                <article class="bd-article">
+                  
+  <section id="some-tips-with-xarray-and-pandas">
+<h1>Some tips with xarray and pandas<a class="headerlink" href="#some-tips-with-xarray-and-pandas" title="Link to this heading">#</a></h1>
+<ul class="simple">
+<li><p>We have massively different levels here</p></li>
+<li><p>Try to make some aims for technical skills you can learn!</p></li>
+<li><p>If you are beginning with python –&gt; learn the basics</p></li>
+<li><p>If you are good at basic python –&gt; learn new packages</p></li>
+<li><p>If you know all the packages –&gt; improve your skills with producing your own software etc.</p></li>
+<li><p>If you don’t know git and github –&gt; get better at this!</p></li>
+</ul>
+<section id="print-hey-world">
+<h2>print(‘Hey world’)<a class="headerlink" href="#print-hey-world" title="Link to this heading">#</a></h2>
+<span style="color:red;font-weight:700;font-size:20px">
+Please feel free to come with suggestions and extra input as we go! 
+</span>
+<span style="color:blue;font-weight:700;font-size:20px">
+Questions:
+<ul class="simple">
+<li><p>How many have used jupyter lab?</p></li>
+<li><p>How many have used pandas?</p></li>
+<li><p>How many have used xarray?
+</span></p></li>
+</ul>
+</section>
+<section id="what-are-pandas-and-xarray">
+<h2>What are pandas and xarray?<a class="headerlink" href="#what-are-pandas-and-xarray" title="Link to this heading">#</a></h2>
+<ul class="simple">
+<li><p>Pandas –&gt; like a spreadsheet 2D data with columns and rows</p></li>
+<li><p>xarray –&gt; like pandas, but in N dimensions</p></li>
+<li><p><strong>Use the functionality these packages gives you! Will help you avoid mistakes. Try to get as good as possible :)</strong></p></li>
+</ul>
+<section id="pandas">
+<h3>Pandas<a class="headerlink" href="#pandas" title="Link to this heading">#</a></h3>
+<p><img alt="image.png" src="learning/notebooks/attachment:4f3ffb45-6681-426e-a674-87ff7d3a7472.png" />
+(Source: https://www.geeksforgeeks.org/python-pandas-dataframe/)</p>
+</section>
+<section id="xarray">
+<h3>Xarray<a class="headerlink" href="#xarray" title="Link to this heading">#</a></h3>
+<p><img alt="image.png" src="learning/notebooks/attachment:1f171b31-582b-4003-be00-7d731d031ab9.png" />
+(Source: https://docs.xarray.dev/)</p>
+</section>
+</section>
+</section>
+<section id="read-in-cmip6-data-we-will-skip-this-next-part-but-you-can-check-it-later-to-read-data">
+<h1>1. Read in CMIP6 data: We will skip this next part, but you can check it later to read data:<a class="headerlink" href="#read-in-cmip6-data-we-will-skip-this-next-part-but-you-can-check-it-later-to-read-data" title="Link to this heading">#</a></h1>
+<section id="import-python-packages">
+<h2>Import python packages<a class="headerlink" href="#import-python-packages" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">xarray</span> <span class="k">as</span> <span class="nn">xr</span>
+<span class="n">xr</span><span class="o">.</span><span class="n">set_options</span><span class="p">(</span><span class="n">display_style</span><span class="o">=</span><span class="s1">&#39;html&#39;</span><span class="p">)</span>
+<span class="kn">import</span> <span class="nn">intake</span>
+<span class="kn">import</span> <span class="nn">cftime</span>
+<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+<span class="kn">import</span> <span class="nn">cartopy.crs</span> <span class="k">as</span> <span class="nn">ccrs</span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
+<span class="kn">import</span> <span class="nn">datetime</span>
+<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="open-cmip6-online-catalog">
+<h2>Open CMIP6 online catalog<a class="headerlink" href="#open-cmip6-online-catalog" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">cat_url</span> <span class="o">=</span> <span class="s2">&quot;https://storage.googleapis.com/cmip6/pangeo-cmip6.json&quot;</span>
+<span class="n">col</span> <span class="o">=</span> <span class="n">intake</span><span class="o">.</span><span class="n">open_esm_datastore</span><span class="p">(</span><span class="n">cat_url</span><span class="p">)</span>
+<span class="n">col</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><p><strong>pangeo-cmip6 catalog with 7674 dataset(s) from 514818 asset(s)</strong>:</p> <div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>unique</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>activity_id</th>
+      <td>18</td>
+    </tr>
+    <tr>
+      <th>institution_id</th>
+      <td>36</td>
+    </tr>
+    <tr>
+      <th>source_id</th>
+      <td>88</td>
+    </tr>
+    <tr>
+      <th>experiment_id</th>
+      <td>170</td>
+    </tr>
+    <tr>
+      <th>member_id</th>
+      <td>657</td>
+    </tr>
+    <tr>
+      <th>table_id</th>
+      <td>37</td>
+    </tr>
+    <tr>
+      <th>variable_id</th>
+      <td>700</td>
+    </tr>
+    <tr>
+      <th>grid_label</th>
+      <td>10</td>
+    </tr>
+    <tr>
+      <th>zstore</th>
+      <td>514818</td>
+    </tr>
+    <tr>
+      <th>dcpp_init_year</th>
+      <td>60</td>
+    </tr>
+    <tr>
+      <th>version</th>
+      <td>736</td>
+    </tr>
+    <tr>
+      <th>derived_variable_id</th>
+      <td>0</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+</section>
+<section id="search-corresponding-data">
+<h2>Search corresponding data<a class="headerlink" href="#search-corresponding-data" title="Link to this heading">#</a></h2>
+<p>Please check <a class="reference external" href="https://pangeo-data.github.io/escience-2022/pangeo101/data_discovery.html?highlight=cmip6">here</a> for info about CMIP and variables :)</p>
+<p>Particularly useful is maybe the variable search which you find here: https://clipc-services.ceda.ac.uk/dreq/mipVars.html</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">cat</span> <span class="o">=</span> <span class="n">col</span><span class="o">.</span><span class="n">search</span><span class="p">(</span><span class="n">source_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;CESM2&#39;</span><span class="p">],</span> <span class="n">experiment_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;historical&#39;</span><span class="p">],</span> <span class="n">table_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Amon&#39;</span><span class="p">,</span><span class="s1">&#39;fx&#39;</span><span class="p">,</span><span class="s1">&#39;AERmon&#39;</span><span class="p">],</span> 
+                 <span class="n">variable_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">,</span><span class="s1">&#39;hurs&#39;</span><span class="p">,</span> <span class="s1">&#39;areacella&#39;</span><span class="p">,</span><span class="s1">&#39;mmrso4&#39;</span> <span class="p">],</span> <span class="n">member_id</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;r1i1p1f1&#39;</span><span class="p">])</span>
+<span class="n">cat</span><span class="o">.</span><span class="n">df</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>activity_id</th>
+      <th>institution_id</th>
+      <th>source_id</th>
+      <th>experiment_id</th>
+      <th>member_id</th>
+      <th>table_id</th>
+      <th>variable_id</th>
+      <th>grid_label</th>
+      <th>zstore</th>
+      <th>dcpp_init_year</th>
+      <th>version</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>0</th>
+      <td>CMIP</td>
+      <td>NCAR</td>
+      <td>CESM2</td>
+      <td>historical</td>
+      <td>r1i1p1f1</td>
+      <td>fx</td>
+      <td>areacella</td>
+      <td>gn</td>
+      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...</td>
+      <td>NaN</td>
+      <td>20190308</td>
+    </tr>
+    <tr>
+      <th>1</th>
+      <td>CMIP</td>
+      <td>NCAR</td>
+      <td>CESM2</td>
+      <td>historical</td>
+      <td>r1i1p1f1</td>
+      <td>AERmon</td>
+      <td>mmrso4</td>
+      <td>gn</td>
+      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...</td>
+      <td>NaN</td>
+      <td>20190308</td>
+    </tr>
+    <tr>
+      <th>2</th>
+      <td>CMIP</td>
+      <td>NCAR</td>
+      <td>CESM2</td>
+      <td>historical</td>
+      <td>r1i1p1f1</td>
+      <td>Amon</td>
+      <td>hurs</td>
+      <td>gn</td>
+      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...</td>
+      <td>NaN</td>
+      <td>20190308</td>
+    </tr>
+    <tr>
+      <th>3</th>
+      <td>CMIP</td>
+      <td>NCAR</td>
+      <td>CESM2</td>
+      <td>historical</td>
+      <td>r1i1p1f1</td>
+      <td>Amon</td>
+      <td>tas</td>
+      <td>gn</td>
+      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...</td>
+      <td>NaN</td>
+      <td>20190308</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+</section>
+<section id="create-dictionary-from-the-list-of-datasets-we-found">
+<h2>Create dictionary from the list of datasets we found<a class="headerlink" href="#create-dictionary-from-the-list-of-datasets-we-found" title="Link to this heading">#</a></h2>
+<ul class="simple">
+<li><p>This step may take several minutes so be patient!</p></li>
+</ul>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dset_dict</span> <span class="o">=</span> <span class="n">cat</span><span class="o">.</span><span class="n">to_dataset_dict</span><span class="p">(</span><span class="n">zarr_kwargs</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;use_cftime&#39;</span><span class="p">:</span><span class="kc">True</span><span class="p">})</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--&gt; The keys in the returned dictionary of datasets are constructed as follows:
+	&#39;activity_id.institution_id.source_id.experiment_id.table_id.grid_label&#39;
+</pre></div>
+</div>
+<div class="output text_html">
+<style>
+    /* Turns off some styling */
+    progress {
+        /* gets rid of default border in Firefox and Opera. */
+        border: none;
+        /* Needs to be in here for Safari polyfill so background images work as expected. */
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+    }
+    progress:not([value]), progress:not([value])::-webkit-progress-bar {
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+        background: #F44336;
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+    <div>
+      <progress value='3' class='' max='3' style='width:300px; height:20px; vertical-align: middle;'></progress>
+      100.00% [3/3 00:11&lt;00:00]
+    </div>
+    </div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="nb">list</span><span class="p">(</span><span class="n">dset_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&#39;CMIP.NCAR.CESM2.historical.fx.gn&#39;,
+ &#39;CMIP.NCAR.CESM2.historical.AERmon.gn&#39;,
+ &#39;CMIP.NCAR.CESM2.historical.Amon.gn&#39;]
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dset_dict</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>{&#39;CMIP.NCAR.CESM2.historical.fx.gn&#39;: &lt;xarray.Dataset&gt; Size: 229kB
+ Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,
+                      nbnd: 2)
+ Coordinates:
+   * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+     lat_bnds        (lat, nbnd) float32 2kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;
+   * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+     lon_bnds        (lon, nbnd) float32 2kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+   * member_id       (member_id) object 8B &#39;r1i1p1f1&#39;
+   * dcpp_init_year  (dcpp_init_year) float64 8B nan
+ Dimensions without coordinates: nbnd
+ Data variables:
+     areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+ Attributes: (12/60)
+     Conventions:                      CF-1.7 CMIP-6.2
+     activity_id:                      CMIP
+     branch_method:                    standard
+     branch_time_in_child:             674885.0
+     branch_time_in_parent:            219000.0
+     case_id:                          15
+     ...                               ...
+     intake_esm_attrs:variable_id:     areacella
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+     intake_esm_attrs:version:         20190308
+     intake_esm_attrs:_data_format_:   zarr
+     intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn,
+ &#39;CMIP.NCAR.CESM2.historical.AERmon.gn&#39;: &lt;xarray.Dataset&gt; Size: 14GB
+ Dimensions:         (lev: 32, nbnd: 2, lat: 192, lon: 288, member_id: 1,
+                      dcpp_init_year: 1, time: 1980)
+ Coordinates:
+     a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+     b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+   * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+     lat_bnds        (lat, nbnd) float64 3kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;
+   * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6
+     lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+   * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+     lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+   * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...
+     time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;
+   * member_id       (member_id) object 8B &#39;r1i1p1f1&#39;
+   * dcpp_init_year  (dcpp_init_year) float64 8B nan
+ Dimensions without coordinates: nbnd
+ Data variables:
+     a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+     b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+     mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;
+     p0              float32 4B ...
+     ps              (time, lat, lon) float32 438MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;
+ Attributes: (12/61)
+     Conventions:                      CF-1.7 CMIP-6.2
+     activity_id:                      CMIP
+     branch_method:                    standard
+     branch_time_in_child:             674885.0
+     branch_time_in_parent:            219000.0
+     case_id:                          15
+     ...                               ...
+     intake_esm_attrs:variable_id:     mmrso4
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+     intake_esm_attrs:version:         20190308
+     intake_esm_attrs:_data_format_:   zarr
+     intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.AERmon.gn,
+ &#39;CMIP.NCAR.CESM2.historical.Amon.gn&#39;: &lt;xarray.Dataset&gt; Size: 876MB
+ Dimensions:         (member_id: 1, dcpp_init_year: 1, time: 1980, lat: 192,
+                      lon: 288, nbnd: 2)
+ Coordinates:
+   * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+     lat_bnds        (lat, nbnd) float32 2kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;
+   * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+     lon_bnds        (lon, nbnd) float32 2kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+   * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...
+     time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;
+   * member_id       (member_id) object 8B &#39;r1i1p1f1&#39;
+   * dcpp_init_year  (dcpp_init_year) float64 8B nan
+ Dimensions without coordinates: nbnd
+ Data variables:
+     hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+     tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+ Attributes: (12/54)
+     Conventions:                      CF-1.7 CMIP-6.2
+     activity_id:                      CMIP
+     branch_method:                    standard
+     branch_time_in_child:             674885.0
+     branch_time_in_parent:            219000.0
+     case_id:                          15
+     ...                               ...
+     intake_esm_attrs:member_id:       r1i1p1f1
+     intake_esm_attrs:table_id:        Amon
+     intake_esm_attrs:grid_label:      gn
+     intake_esm_attrs:version:         20190308
+     intake_esm_attrs:_data_format_:   zarr
+     intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.Amon.gn}
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="open-dataset">
+<h2>Open dataset<a class="headerlink" href="#open-dataset" title="Link to this heading">#</a></h2>
+<ul class="simple">
+<li><p>Use <code class="docutils literal notranslate"><span class="pre">xarray</span></code> python package to analyze netCDF dataset</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">open_dataset</span></code> allows to get all the metadata without loading data into memory.</p></li>
+<li><p>with <code class="docutils literal notranslate"><span class="pre">xarray</span></code>, we only load into memory what is needed.</p></li>
+</ul>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds1</span> <span class="o">=</span> <span class="n">dset_dict</span><span class="p">[</span><span class="s1">&#39;CMIP.NCAR.CESM2.historical.Amon.gn&#39;</span><span class="p">]</span>
+<span class="n">ds2</span> <span class="o">=</span> <span class="n">dset_dict</span><span class="p">[</span><span class="s1">&#39;CMIP.NCAR.CESM2.historical.fx.gn&#39;</span><span class="p">]</span>
+<span class="n">ds3</span> <span class="o">=</span> <span class="n">dset_dict</span><span class="p">[</span><span class="s1">&#39;CMIP.NCAR.CESM2.historical.AERmon.gn&#39;</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds1</span>
+</pre></div>
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+  margin: 0;
+  display: grid;
+  grid-template-columns: 125px auto;
+}
+
+.xr-attrs dt,
+.xr-attrs dd {
+  padding: 0;
+  margin: 0;
+  float: left;
+  padding-right: 10px;
+  width: auto;
+}
+
+.xr-attrs dt {
+  font-weight: normal;
+  grid-column: 1;
+}
+
+.xr-attrs dt:hover span {
+  display: inline-block;
+  background: var(--xr-background-color);
+  padding-right: 10px;
+}
+
+.xr-attrs dd {
+  grid-column: 2;
+  white-space: pre-wrap;
+  word-break: break-all;
+}
+
+.xr-icon-database,
+.xr-icon-file-text2,
+.xr-no-icon {
+  display: inline-block;
+  vertical-align: middle;
+  width: 1em;
+  height: 1.5em !important;
+  stroke-width: 0;
+  stroke: currentColor;
+  fill: currentColor;
+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 876MB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, time: 1980, lat: 192,
+                     lon: 288, nbnd: 2)
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+    lat_bnds        (lat, nbnd) float32 2kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;
+  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+    lon_bnds        (lon, nbnd) float32 2kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...
+    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+Dimensions without coordinates: nbnd
+Data variables:
+    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+Attributes: (12/54)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:member_id:       r1i1p1f1
+    intake_esm_attrs:table_id:        Amon
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.Amon.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-19cad1a0-3409-49eb-9c05-2e91922b629d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-19cad1a0-3409-49eb-9c05-2e91922b629d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8f2a1b68-aa56-4f1a-9d28-85a7396c8882' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8f2a1b68-aa56-4f1a-9d28-85a7396c8882' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-6daf1120-1ad0-4209-bcb0-6de1c203c7b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6daf1120-1ad0-4209-bcb0-6de1c203c7b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b206aed-5c0b-42fd-88d9-276f8e774795' class='xr-var-data-in' type='checkbox'><label for='data-1b206aed-5c0b-42fd-88d9-276f8e774795' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, nbnd)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;</div><input id='attrs-5bd66430-8c69-45c3-8f7d-f36815f6f316' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5bd66430-8c69-45c3-8f7d-f36815f6f316' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-addb38f3-374b-4c65-a4d7-4df850924178' class='xr-var-data-in' type='checkbox'><label for='data-addb38f3-374b-4c65-a4d7-4df850924178' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 1.50 kiB </td>
+                        <td> 1.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (192, 2) </td>
+                        <td> (192, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 5 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.60913412115106,0.0 25.60913412115106,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.804567" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.609134" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.609134,60.000000)">192</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-9c64ff37-717d-4468-b27b-87fc3a42a398' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c64ff37-717d-4468-b27b-87fc3a42a398' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2bef3518-effb-471f-86ad-c511f8c11bfd' class='xr-var-data-in' type='checkbox'><label for='data-2bef3518-effb-471f-86ad-c511f8c11bfd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-a0387bbd-b232-4efa-a445-032530a5146c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0387bbd-b232-4efa-a445-032530a5146c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fb657a4-ec9d-48ff-b938-abb8d6144076' class='xr-var-data-in' type='checkbox'><label for='data-3fb657a4-ec9d-48ff-b938-abb8d6144076' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 2.25 kiB </td>
+                        <td> 2.25 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 5 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-1b2e2506-f9d5-46b2-adf5-824ba7091ad6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b2e2506-f9d5-46b2-adf5-824ba7091ad6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a54bd7c1-8a33-441a-996a-fead39d549fe' class='xr-var-data-in' type='checkbox'><label for='data-a54bd7c1-8a33-441a-996a-fead39d549fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-7aa31124-3287-4413-9f9d-8d1cc21899a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7aa31124-3287-4413-9f9d-8d1cc21899a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18d4fe6d-226c-47cd-b569-8cd133697bf4' class='xr-var-data-in' type='checkbox'><label for='data-18d4fe6d-226c-47cd-b569-8cd133697bf4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 30.94 kiB </td>
+                        <td> 30.94 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1980, 2) </td>
+                        <td> (1980, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 5 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-fd99a088-7101-45d3-8096-130a86412e9d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd99a088-7101-45d3-8096-130a86412e9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecc88eb2-c6e1-4523-9f04-080aa6a17bdf' class='xr-var-data-in' type='checkbox'><label for='data-ecc88eb2-c6e1-4523-9f04-080aa6a17bdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-1a0e6776-97f1-4dbc-a895-ca9518c010a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a0e6776-97f1-4dbc-a895-ca9518c010a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1dd16820-715a-47f5-af1b-8c17b67fbdd0' class='xr-var-data-in' type='checkbox'><label for='data-1dd16820-715a-47f5-af1b-8c17b67fbdd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b128bf1f-fa65-4177-967f-5835953e3cc0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b128bf1f-fa65-4177-967f-5835953e3cc0' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-faeb3046-321c-489a-a084-699ec6e4cf5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-faeb3046-321c-489a-a084-699ec6e4cf5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30a1fcf3-21f9-4f2f-a1b1-cb2cb9f22f59' class='xr-var-data-in' type='checkbox'><label for='data-30a1fcf3-21f9-4f2f-a1b1-cb2cb9f22f59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 417.66 MiB </td>
+                        <td> 126.56 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 192, 288) </td>
+                        <td> (1, 1, 600, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 4 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
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+  <text x="120.294118" y="93.719750" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(45,120.294118,93.719750)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-3a3eaabb-27dc-4c00-b719-a39e5d8fff1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a3eaabb-27dc-4c00-b719-a39e5d8fff1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a55f7f7c-f661-48bb-862b-8e1bb435f091' class='xr-var-data-in' type='checkbox'><label for='data-a55f7f7c-f661-48bb-862b-8e1bb435f091' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 417.66 MiB </td>
+                        <td> 126.56 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 192, 288) </td>
+                        <td> (1, 1, 600, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 4 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="351" height="159" style="stroke:rgb(0,0,0);stroke-width:1" >
+
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+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-229fc39d-795e-499b-bca6-a0bff06439b4' class='xr-section-summary-in' type='checkbox'  ><label for='section-229fc39d-795e-499b-bca6-a0bff06439b4' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4a1f9dbf-e8f3-4714-a489-e2763aa20ede' class='xr-index-data-in' type='checkbox'/><label for='index-4a1f9dbf-e8f3-4714-a489-e2763aa20ede' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,
+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-95145dd8-4bed-44b3-8cf2-955cdd71858a' class='xr-index-data-in' type='checkbox'/><label for='index-95145dd8-4bed-44b3-8cf2-955cdd71858a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-28b50fab-c4d8-40eb-bc31-12cfe1ec7c3d' class='xr-index-data-in' type='checkbox'/><label for='index-28b50fab-c4d8-40eb-bc31-12cfe1ec7c3d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,
+             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,
+             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,
+             1850-10-15 12:00:00,
+             ...
+             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,
+             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,
+             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,
+             2014-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a3d1f863-73fb-4531-b3e1-417ad9100297' class='xr-index-data-in' type='checkbox'/><label for='index-a3d1f863-73fb-4531-b3e1-417ad9100297' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-edff9bda-e3e8-4844-ab38-23c849967fde' class='xr-index-data-in' type='checkbox'/><label for='index-edff9bda-e3e8-4844-ab38-23c849967fde' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f8f37539-6046-479b-8ae8-0f01515f42b9' class='xr-section-summary-in' type='checkbox'  ><label for='section-f8f37539-6046-479b-8ae8-0f01515f42b9' class='xr-section-summary' >Attributes: <span>(54)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>Amon</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.Amon.gn</dd></dl></div></li></ul></div></div></div></div>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 14GB
+Dimensions:         (lev: 32, nbnd: 2, lat: 192, lon: 288, member_id: 1,
+                     dcpp_init_year: 1, time: 1980)
+Coordinates:
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+    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+    lat_bnds        (lat, nbnd) float64 3kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;
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+    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...
+    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+Dimensions without coordinates: nbnd
+Data variables:
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+    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
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+    p0              float32 4B ...
+    ps              (time, lat, lon) float32 438MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;
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+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
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+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.AERmon.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c166d8ac-7778-48a6-9330-9bc7cb6ea739' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c166d8ac-7778-48a6-9330-9bc7cb6ea739' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lev</span>: 32</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-92ac6c37-f641-4bd3-9225-44ce54fbcf2f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-92ac6c37-f641-4bd3-9225-44ce54fbcf2f' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-deed4b9b-e2a3-4373-a710-ce2c21846f30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-deed4b9b-e2a3-4373-a710-ce2c21846f30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d08035a-7364-42fe-ac9e-c0cb866fe462' class='xr-var-data-in' type='checkbox'><label for='data-5d08035a-7364-42fe-ac9e-c0cb866fe462' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-6f2ffd96-ef07-4b14-b3fc-7d28fa3b6fe4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f2ffd96-ef07-4b14-b3fc-7d28fa3b6fe4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f255b7f0-c048-4225-8913-d7fce636e50b' class='xr-var-data-in' type='checkbox'><label for='data-f255b7f0-c048-4225-8913-d7fce636e50b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-01d9b51c-7a26-4aec-b47a-470f2f658084' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01d9b51c-7a26-4aec-b47a-470f2f658084' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a31eaf-fe25-48f4-bdce-e9f8e924d822' class='xr-var-data-in' type='checkbox'><label for='data-84a31eaf-fe25-48f4-bdce-e9f8e924d822' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;</div><input id='attrs-8130a583-5f51-4f2e-af44-9e8987a3e1cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8130a583-5f51-4f2e-af44-9e8987a3e1cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25cdac0f-a60e-46b7-85f5-7791b4d4546c' class='xr-var-data-in' type='checkbox'><label for='data-25cdac0f-a60e-46b7-85f5-7791b4d4546c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 3.00 kiB </td>
+                        <td> 3.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (192, 2) </td>
+                        <td> (192, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.60913412115106,0.0 25.60913412115106,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.804567" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.609134" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.609134,60.000000)">192</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-1ac05413-c935-4ec8-a48f-04649cc082cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ac05413-c935-4ec8-a48f-04649cc082cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90b761f3-6a54-4ac5-b30d-5d6e8ed51a84' class='xr-var-data-in' type='checkbox'><label for='data-90b761f3-6a54-4ac5-b30d-5d6e8ed51a84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,
+        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,
+       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,
+       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,
+       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,
+       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,
+       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-5ec9b59f-e16f-4716-8c82-904ab9943b16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ec9b59f-e16f-4716-8c82-904ab9943b16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28094f69-d286-4fe0-b73f-40135852211f' class='xr-var-data-in' type='checkbox'><label for='data-28094f69-d286-4fe0-b73f-40135852211f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-ca3cad7c-74e6-4832-8e61-179e7cdfceff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca3cad7c-74e6-4832-8e61-179e7cdfceff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0e37d9e-639b-41fd-839d-7f1094955a75' class='xr-var-data-in' type='checkbox'><label for='data-a0e37d9e-639b-41fd-839d-7f1094955a75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-eb62ad28-4de9-43ee-96c6-00ebcfac0d6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb62ad28-4de9-43ee-96c6-00ebcfac0d6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dee7a12-aff0-4302-973d-53fc3752dc62' class='xr-var-data-in' type='checkbox'><label for='data-3dee7a12-aff0-4302-973d-53fc3752dc62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-f54b4670-2a98-4936-bebf-1fbc7b1e02e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f54b4670-2a98-4936-bebf-1fbc7b1e02e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65b46556-0db4-49a6-9164-f8378d3a4d27' class='xr-var-data-in' type='checkbox'><label for='data-65b46556-0db4-49a6-9164-f8378d3a4d27' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-88520582-3ea9-456d-9146-28bdbab904ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88520582-3ea9-456d-9146-28bdbab904ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91147058-abbb-4de6-9de3-f101a9bf0210' class='xr-var-data-in' type='checkbox'><label for='data-91147058-abbb-4de6-9de3-f101a9bf0210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 30.94 kiB </td>
+                        <td> 30.94 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1980, 2) </td>
+                        <td> (1980, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-c2d44599-5940-4fe8-ba5c-2a4ded67b17e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2d44599-5940-4fe8-ba5c-2a4ded67b17e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e300d6c-edee-4e32-b486-66aa184f65bc' class='xr-var-data-in' type='checkbox'><label for='data-5e300d6c-edee-4e32-b486-66aa184f65bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e215e719-0647-4431-b8fe-795bd943a72b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e215e719-0647-4431-b8fe-795bd943a72b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6ab0c9b-4a8a-4250-bbc1-3485321521eb' class='xr-var-data-in' type='checkbox'><label for='data-a6ab0c9b-4a8a-4250-bbc1-3485321521eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d88aa10-6a43-4a7e-9159-906418246052' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7d88aa10-6a43-4a7e-9159-906418246052' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-7ce7ec97-9e6f-4cf4-8d99-03c0e6ce189a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ce7ec97-9e6f-4cf4-8d99-03c0e6ce189a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4d6f304-074d-441f-a0a4-5802c906dd08' class='xr-var-data-in' type='checkbox'><label for='data-e4d6f304-074d-441f-a0a4-5802c906dd08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 256 B </td>
+                        <td> 256 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32,) </td>
+                        <td> (32,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="81" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="31" x2="120" y2="31" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="31" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="31" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,31.635229193102678 0.0,31.635229193102678" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="51.635229" font-size="1.0rem" font-weight="100" text-anchor="middle" >32</text>
+  <text x="140.000000" y="15.817615" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,15.817615)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-f7f45bb7-ba2a-4fe1-996b-ecf93c498a0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7f45bb7-ba2a-4fe1-996b-ecf93c498a0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06ab2e35-a678-43ab-98bf-506908c03170' class='xr-var-data-in' type='checkbox'><label for='data-06ab2e35-a678-43ab-98bf-506908c03170' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 256 B </td>
+                        <td> 256 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32,) </td>
+                        <td> (32,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="81" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="31" x2="120" y2="31" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="31" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="31" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,31.635229193102678 0.0,31.635229193102678" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="51.635229" font-size="1.0rem" font-weight="100" text-anchor="middle" >32</text>
+  <text x="140.000000" y="15.817615" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,15.817615)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-3028cae2-9a1f-4490-bb79-eacda5102097' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3028cae2-9a1f-4490-bb79-eacda5102097' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3c1312b-9993-4b7b-a972-3dd2840fa9f3' class='xr-var-data-in' type='checkbox'><label for='data-d3c1312b-9993-4b7b-a972-3dd2840fa9f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 13.05 GiB </td>
+                        <td> 67.50 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 32, 192, 288) </td>
+                        <td> (1, 1, 10, 32, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 198 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="534" height="104" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="10" y1="0" x2="24" y2="14" style="stroke-width:2" />
+  <line x1="10" y1="25" x2="24" y2="40" style="stroke-width:2" />
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dffb4786-c992-49cc-9333-bf0cde9a52ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dffb4786-c992-49cc-9333-bf0cde9a52ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a717249-2b8d-4662-b340-6dac06b15ec0' class='xr-var-data-in' type='checkbox'><label for='data-5a717249-2b8d-4662-b340-6dac06b15ec0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-7dd891a8-6485-4e35-9033-4cd8c9a8cf87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7dd891a8-6485-4e35-9033-4cd8c9a8cf87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2efda39-757a-4b25-9a7a-a9f4f2a58be8' class='xr-var-data-in' type='checkbox'><label for='data-b2efda39-757a-4b25-9a7a-a9f4f2a58be8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 417.66 MiB </td>
+                        <td> 2.11 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1980, 192, 288) </td>
+                        <td> (10, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 198 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e1cc7aad-18cf-4047-9c70-d281d3944bfb' class='xr-index-data-in' type='checkbox'/><label for='index-e1cc7aad-18cf-4047-9c70-d281d3944bfb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,
+       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,
+        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,
+        -87.82123029232025, -103.31712663173676, -121.54724076390266,
+       -142.99403876066208, -168.22507977485657,  -197.9080867022276,
+       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,
+       -379.10090386867523,   -445.992574095726,  -524.6871747076511,
+        -609.7786948084831,  -691.3894303143024,   -763.404481112957,
+        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,
+         -912.644546944648,  -936.1983984708786,   -957.485479535535,
+         -976.325407391414,   -992.556095123291],
+      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3dfdac6e-2864-4ad9-b94d-849b46f2cdaa' class='xr-index-data-in' type='checkbox'/><label for='index-3dfdac6e-2864-4ad9-b94d-849b46f2cdaa' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c490b542-0f84-4568-b8e7-5602ffe8a757' class='xr-index-data-in' type='checkbox'/><label for='index-c490b542-0f84-4568-b8e7-5602ffe8a757' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,
+             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,
+             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,
+             1850-10-15 12:00:00,
+             ...
+             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,
+             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,
+             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,
+             2014-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b465b924-e9e5-4694-a7c2-ba786e8639eb' class='xr-index-data-in' type='checkbox'/><label for='index-b465b924-e9e5-4694-a7c2-ba786e8639eb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b82590fe-0f90-4289-b3ec-cdac68eb2eaa' class='xr-index-data-in' type='checkbox'/><label for='index-b82590fe-0f90-4289-b3ec-cdac68eb2eaa' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-442f75a5-5816-49cc-8566-8669f3a9b75b' class='xr-section-summary-in' type='checkbox'  ><label for='section-442f75a5-5816-49cc-8566-8669f3a9b75b' class='xr-section-summary' >Attributes: <span>(61)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-03-07T14:55:48Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>AERmon</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/068116b9-bea7-4f4d-a942-e0bbee279412</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-11-04;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/068116b9-bea7-4f4d-a942-e0bbee279412</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;mmrso4&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>AERmon</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>mmrso4</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/AERmon/mmrso4/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.AERmon.gn</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<span style="color:black;font-weight:700;font-size:20px">
+Since I have already checked that these datasets are on the same grid, we can merge them:
+</span>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds_list</span> <span class="o">=</span> <span class="p">[</span><span class="n">dset_dict</span><span class="p">[</span><span class="n">l</span><span class="p">]</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;lat_bnds&#39;</span><span class="p">)</span> <span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="n">dset_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">()]</span>
+<span class="n">ds</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">ds_list</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_11040/2274112695.py:1: DeprecationWarning: dropping variables using `drop` is deprecated; use drop_vars.
+  ds_list = [dset_dict[l].drop(&#39;lat_bnds&#39;) for l in dset_dict.keys()]
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds</span>
+</pre></div>
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+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 15GB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,
+                     nbnd: 2, lev: 32, time: 1980)
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6
+    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...
+    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;
+Dimensions without coordinates: nbnd
+Data variables:
+    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;
+    p0              float32 4B ...
+    ps              (time, lat, lon) float32 438MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;
+    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+Attributes: (12/60)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:variable_id:     areacella
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e90c3490-46b3-4c21-aa9e-85d46e93dd8a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e90c3490-46b3-4c21-aa9e-85d46e93dd8a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c3e23b15-8ae9-4068-a4a3-ce2aa07869cd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c3e23b15-8ae9-4068-a4a3-ce2aa07869cd' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-3d47c756-08b8-4d36-a6b2-5ae1d5a7644b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d47c756-08b8-4d36-a6b2-5ae1d5a7644b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f2609c4-f4a8-4ecf-9d7a-9ce602ea5b96' class='xr-var-data-in' type='checkbox'><label for='data-4f2609c4-f4a8-4ecf-9d7a-9ce602ea5b96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-ce11782f-f5df-4003-a643-02ac30db87ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce11782f-f5df-4003-a643-02ac30db87ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27616872-4b8f-4715-83db-7cf1dc326409' class='xr-var-data-in' type='checkbox'><label for='data-27616872-4b8f-4715-83db-7cf1dc326409' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-39fafa3d-d120-45dd-95e3-5e0577ba59df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39fafa3d-d120-45dd-95e3-5e0577ba59df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bdd3382-1f07-4d38-a870-eb42acb012af' class='xr-var-data-in' type='checkbox'><label for='data-0bdd3382-1f07-4d38-a870-eb42acb012af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-885b4ffa-67eb-41c4-830b-2fc1c056abd4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-885b4ffa-67eb-41c4-830b-2fc1c056abd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b9541f2-134c-4dfd-900b-6c60933d5a7c' class='xr-var-data-in' type='checkbox'><label for='data-9b9541f2-134c-4dfd-900b-6c60933d5a7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2acc8cee-b77d-48e9-8b96-fb31813edeb8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2acc8cee-b77d-48e9-8b96-fb31813edeb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c0e4014-2d9d-4e13-acce-7e3af089071a' class='xr-var-data-in' type='checkbox'><label for='data-6c0e4014-2d9d-4e13-acce-7e3af089071a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-e310c819-d9c5-442e-b562-3184b2c2ff7f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e310c819-d9c5-442e-b562-3184b2c2ff7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6a516a4-0aac-4cb3-b89c-331c4f2ecacb' class='xr-var-data-in' type='checkbox'><label for='data-e6a516a4-0aac-4cb3-b89c-331c4f2ecacb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-669733f3-acf9-4ef6-b80c-c41501a0f55a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-669733f3-acf9-4ef6-b80c-c41501a0f55a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6bb0354-e0c2-43aa-a31d-c957485a9582' class='xr-var-data-in' type='checkbox'><label for='data-f6bb0354-e0c2-43aa-a31d-c957485a9582' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-39b3db86-5479-4b62-bac9-16a3bfeee0a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39b3db86-5479-4b62-bac9-16a3bfeee0a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b990322-3c4d-4c97-b4ce-38b84d01c0df' class='xr-var-data-in' type='checkbox'><label for='data-7b990322-3c4d-4c97-b4ce-38b84d01c0df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,
+        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,
+       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,
+       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,
+       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,
+       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,
+       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-1ea8d0b7-ae57-4fd4-812a-ed7a2436af69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ea8d0b7-ae57-4fd4-812a-ed7a2436af69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd889eec-7991-4ca6-86fe-000be471af2e' class='xr-var-data-in' type='checkbox'><label for='data-fd889eec-7991-4ca6-86fe-000be471af2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
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+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-0fc45a33-1edf-4733-a73f-e7bddc836891' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0fc45a33-1edf-4733-a73f-e7bddc836891' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3a3f239-e5e7-42c8-9811-51f48b272885' class='xr-var-data-in' type='checkbox'><label for='data-d3a3f239-e5e7-42c8-9811-51f48b272885' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-b55fec80-d040-4ea4-bfa4-99db455b7964' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b55fec80-d040-4ea4-bfa4-99db455b7964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd2c249f-f6b5-48de-97e7-81d37fb62b82' class='xr-var-data-in' type='checkbox'><label for='data-fd2c249f-f6b5-48de-97e7-81d37fb62b82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 30.94 kiB </td>
+                        <td> 30.94 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1980, 2) </td>
+                        <td> (1980, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 6 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7db91c7d-e443-48c8-9436-6473f83ba1cf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7db91c7d-e443-48c8-9436-6473f83ba1cf' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-f980b003-a669-4d0e-9714-a68165a2c38b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f980b003-a669-4d0e-9714-a68165a2c38b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bceeb408-e0ee-48ea-be77-007d28206bbc' class='xr-var-data-in' type='checkbox'><label for='data-bceeb408-e0ee-48ea-be77-007d28206bbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 192, 288) </td>
+                        <td> (1, 1, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="374" height="144" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="25" y2="25" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="25" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="25" style="stroke-width:2" />
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+
+  <!-- Text -->
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+
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+  <!-- Horizontal lines -->
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+  <!-- Vertical lines -->
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+  <text x="92.474299" y="107.474299" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(45,92.474299,107.474299)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-896ba7e5-aae5-484d-bca2-7801a5e9e3bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-896ba7e5-aae5-484d-bca2-7801a5e9e3bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e354c88e-20b1-439a-9d75-70047c822e25' class='xr-var-data-in' type='checkbox'><label for='data-e354c88e-20b1-439a-9d75-70047c822e25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 256 B </td>
+                        <td> 256 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32,) </td>
+                        <td> (32,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="81" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
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+                    <tr>
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+                        <td> (32,) </td>
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+                    <tr>
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+                    <tr>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-b78c1860-011f-4bea-a8bc-a592c14d89f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b78c1860-011f-4bea-a8bc-a592c14d89f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a9b9fe0-c297-412a-9e80-09937303fc63' class='xr-var-data-in' type='checkbox'><label for='data-6a9b9fe0-c297-412a-9e80-09937303fc63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
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+            <table style="border-collapse: collapse;">
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+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 417.66 MiB </td>
+                        <td> 126.56 MiB </td>
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+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 192, 288) </td>
+                        <td> (1, 1, 600, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 4 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+        </td>
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+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 417.66 MiB </td>
+                        <td> 126.56 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 192, 288) </td>
+                        <td> (1, 1, 600, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 4 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0540677b-1831-4c16-9eed-879221abbd66' class='xr-index-data-in' type='checkbox'/><label for='index-0540677b-1831-4c16-9eed-879221abbd66' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1518f381-b4f9-4ab4-9e8a-8457b988c5e0' class='xr-index-data-in' type='checkbox'/><label for='index-1518f381-b4f9-4ab4-9e8a-8457b988c5e0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-07bd4a92-bfc2-4b14-bb92-9a79c5b898a0' class='xr-index-data-in' type='checkbox'/><label for='index-07bd4a92-bfc2-4b14-bb92-9a79c5b898a0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-898d3593-fc78-47ac-b265-91f40157b8fd' class='xr-index-data-in' type='checkbox'/><label for='index-898d3593-fc78-47ac-b265-91f40157b8fd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,
+       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,
+        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,
+        -87.82123029232025, -103.31712663173676, -121.54724076390266,
+       -142.99403876066208, -168.22507977485657,  -197.9080867022276,
+       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,
+       -379.10090386867523,   -445.992574095726,  -524.6871747076511,
+        -609.7786948084831,  -691.3894303143024,   -763.404481112957,
+        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,
+         -912.644546944648,  -936.1983984708786,   -957.485479535535,
+         -976.325407391414,   -992.556095123291],
+      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2a86eceb-c979-4c56-9bdf-cb57ee1ef651' class='xr-index-data-in' type='checkbox'/><label for='index-2a86eceb-c979-4c56-9bdf-cb57ee1ef651' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,
+             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,
+             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,
+             1850-10-15 12:00:00,
+             ...
+             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,
+             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,
+             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,
+             2014-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3b69f123-2e06-43c3-bc8c-1db8564b4a0e' class='xr-section-summary-in' type='checkbox'  ><label for='section-3b69f123-2e06-43c3-bc8c-1db8564b4a0e' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
+</div>
+</section>
+<section id="reading-in-the-data-from-file">
+<h2>1.1 Reading in the data from file:<a class="headerlink" href="#reading-in-the-data-from-file" title="Link to this heading">#</a></h2>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">path</span><span class="o">=</span><span class="s1">&#39;filename.nc&#39;</span>
+<span class="n">ds</span> <span class="o">=</span> <span class="n">xr</span><span class="o">.</span><span class="n">open_dataset</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
+</pre></div>
+</div>
+<section id="opening-multiple-files">
+<h3>Opening multiple files:<a class="headerlink" href="#opening-multiple-files" title="Link to this heading">#</a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span>
+<span class="n">list_of_files</span> <span class="o">=</span> <span class="p">[</span>
+    <span class="s1">&#39;file1.nc&#39;</span><span class="p">,</span>
+    <span class="s1">&#39;file2.nc&#39;</span>
+<span class="p">]</span>
+<span class="n">xr</span><span class="o">.</span><span class="n">open_mfdataset</span><span class="p">(</span><span class="n">list_of_files</span><span class="p">,</span> <span class="n">concat_dim</span><span class="o">=</span><span class="s1">&#39;time&#39;</span><span class="p">,</span><span class="n">combine</span><span class="o">=</span><span class="s1">&#39;by_coords&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</section>
+</section>
+</section>
+<section id="check-how-your-dataset-looks">
+<h1>2. Check how your dataset looks<a class="headerlink" href="#check-how-your-dataset-looks" title="Link to this heading">#</a></h1>
+<section id="different-types-of-information-data">
+<h2>Different types of information/data:<a class="headerlink" href="#different-types-of-information-data" title="Link to this heading">#</a></h2>
+<ul class="simple">
+<li><p>Coordinates</p></li>
+<li><p>Data variables</p></li>
+<li><p>Global attributes</p></li>
+<li><p>Variable attributes</p></li>
+</ul>
+<div class="cell docutils container">
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+  width: auto;
+  z-index: 1;
+}
+
+.xr-var-attrs,
+.xr-var-data,
+.xr-index-data {
+  display: none;
+  background-color: var(--xr-background-color) !important;
+  padding-bottom: 5px !important;
+}
+
+.xr-var-attrs-in:checked ~ .xr-var-attrs,
+.xr-var-data-in:checked ~ .xr-var-data,
+.xr-index-data-in:checked ~ .xr-index-data {
+  display: block;
+}
+
+.xr-var-data > table {
+  float: right;
+}
+
+.xr-var-name span,
+.xr-var-data,
+.xr-index-name div,
+.xr-index-data,
+.xr-attrs {
+  padding-left: 25px !important;
+}
+
+.xr-attrs,
+.xr-var-attrs,
+.xr-var-data,
+.xr-index-data {
+  grid-column: 1 / -1;
+}
+
+dl.xr-attrs {
+  padding: 0;
+  margin: 0;
+  display: grid;
+  grid-template-columns: 125px auto;
+}
+
+.xr-attrs dt,
+.xr-attrs dd {
+  padding: 0;
+  margin: 0;
+  float: left;
+  padding-right: 10px;
+  width: auto;
+}
+
+.xr-attrs dt {
+  font-weight: normal;
+  grid-column: 1;
+}
+
+.xr-attrs dt:hover span {
+  display: inline-block;
+  background: var(--xr-background-color);
+  padding-right: 10px;
+}
+
+.xr-attrs dd {
+  grid-column: 2;
+  white-space: pre-wrap;
+  word-break: break-all;
+}
+
+.xr-icon-database,
+.xr-icon-file-text2,
+.xr-no-icon {
+  display: inline-block;
+  vertical-align: middle;
+  width: 1em;
+  height: 1.5em !important;
+  stroke-width: 0;
+  stroke: currentColor;
+  fill: currentColor;
+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 15GB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,
+                     nbnd: 2, lev: 32, time: 1980)
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6
+    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...
+    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;
+Dimensions without coordinates: nbnd
+Data variables:
+    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;
+    p0              float32 4B ...
+    ps              (time, lat, lon) float32 438MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;
+    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+Attributes: (12/60)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:variable_id:     areacella
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-048f0340-7b0f-4dd2-9ce8-dfca6e13d284' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-048f0340-7b0f-4dd2-9ce8-dfca6e13d284' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-bfd4b7b3-7882-49da-95cc-c847a58d2c48' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bfd4b7b3-7882-49da-95cc-c847a58d2c48' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-ad6ea541-3301-488d-b0a0-8a25b4521657' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad6ea541-3301-488d-b0a0-8a25b4521657' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69e81aea-bd14-4d0f-a94b-d225aeee528a' class='xr-var-data-in' type='checkbox'><label for='data-69e81aea-bd14-4d0f-a94b-d225aeee528a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-3f0afd85-77a3-40e6-9b5e-02d8d0b17e03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f0afd85-77a3-40e6-9b5e-02d8d0b17e03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fced7d30-1ca0-46a1-8d61-cd4ebc048b5f' class='xr-var-data-in' type='checkbox'><label for='data-fced7d30-1ca0-46a1-8d61-cd4ebc048b5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-defca196-9000-41a8-97cc-34c6c18ae078' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-defca196-9000-41a8-97cc-34c6c18ae078' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19c0b1e1-6b50-4816-b8e5-34f8d22f0785' class='xr-var-data-in' type='checkbox'><label for='data-19c0b1e1-6b50-4816-b8e5-34f8d22f0785' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-98a6a390-1ab0-4394-957a-8303d9e4116e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98a6a390-1ab0-4394-957a-8303d9e4116e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c5b634b-44c8-47b3-ae0d-c032627ca0cf' class='xr-var-data-in' type='checkbox'><label for='data-5c5b634b-44c8-47b3-ae0d-c032627ca0cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e8517f54-c0ff-49a6-a4bb-b8414bf4634c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8517f54-c0ff-49a6-a4bb-b8414bf4634c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-323b0bfd-ff29-4350-af4a-6aa6d3c99aa5' class='xr-var-data-in' type='checkbox'><label for='data-323b0bfd-ff29-4350-af4a-6aa6d3c99aa5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-58a74926-b720-4689-bfbb-4d532e3b1ae8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58a74926-b720-4689-bfbb-4d532e3b1ae8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed2273d8-9ddb-487c-8743-576814085cfa' class='xr-var-data-in' type='checkbox'><label for='data-ed2273d8-9ddb-487c-8743-576814085cfa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-9209ae5b-c488-4af8-9b58-bb9852d08fb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9209ae5b-c488-4af8-9b58-bb9852d08fb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b405acc-005d-4930-ab70-bfda83a805b5' class='xr-var-data-in' type='checkbox'><label for='data-4b405acc-005d-4930-ab70-bfda83a805b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
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+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-a04deb06-2249-447c-b045-14de2c44c964' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a04deb06-2249-447c-b045-14de2c44c964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc82fbef-e2fb-41de-a0b0-8fb38cea525f' class='xr-var-data-in' type='checkbox'><label for='data-bc82fbef-e2fb-41de-a0b0-8fb38cea525f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,
+        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,
+       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,
+       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,
+       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,
+       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,
+       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-13f091da-c8a5-47e1-a704-63a7d4cc7629' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-13f091da-c8a5-47e1-a704-63a7d4cc7629' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec58db63-e3dc-4ff5-b3d2-487737922a67' class='xr-var-data-in' type='checkbox'><label for='data-ec58db63-e3dc-4ff5-b3d2-487737922a67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-a53dee04-f5e7-4816-a860-dcc66e1c249b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a53dee04-f5e7-4816-a860-dcc66e1c249b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6df1e86-0fde-40ce-9ff4-76f31f50de28' class='xr-var-data-in' type='checkbox'><label for='data-f6df1e86-0fde-40ce-9ff4-76f31f50de28' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-cada893c-525d-4458-b03b-fd38d1613380' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cada893c-525d-4458-b03b-fd38d1613380' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92cda687-0618-47bf-9557-67aa3cb27c0b' class='xr-var-data-in' type='checkbox'><label for='data-92cda687-0618-47bf-9557-67aa3cb27c0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 30.94 kiB </td>
+                        <td> 30.94 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1980, 2) </td>
+                        <td> (1980, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 6 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-38e982e6-59be-4833-8991-2625cc71d292' class='xr-section-summary-in' type='checkbox'  checked><label for='section-38e982e6-59be-4833-8991-2625cc71d292' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-d6c069d2-2064-4e23-8460-e27a0c8f31bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6c069d2-2064-4e23-8460-e27a0c8f31bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81d9d8ac-96cf-4ce5-afba-f4bf54df694a' class='xr-var-data-in' type='checkbox'><label for='data-81d9d8ac-96cf-4ce5-afba-f4bf54df694a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 192, 288) </td>
+                        <td> (1, 1, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="374" height="144" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="25" y2="25" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="25" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="25" style="stroke-width:2" />
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+
+  <!-- Text -->
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+  <text x="92.474299" y="107.474299" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(45,92.474299,107.474299)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-385a7520-dae5-4ace-bc27-9ada8698ae85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-385a7520-dae5-4ace-bc27-9ada8698ae85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c139d309-60a7-438b-9d24-98cc8d737d98' class='xr-var-data-in' type='checkbox'><label for='data-c139d309-60a7-438b-9d24-98cc8d737d98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
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+                        <td> 256 B </td>
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+                    <tr>
+                        <th> Shape </th>
+                        <td> (32,) </td>
+                        <td> (32,) </td>
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+                    <tr>
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+                    </tr>
+                    <tr>
+                        <th> Data type </th>
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+                        <th> Chunk </th>
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+                </thead>
+                <tbody>
+                    
+                    <tr>
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+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 32, 192, 288) </td>
+                        <td> (1, 1, 10, 32, 192, 288) </td>
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+                        <th> Dask graph </th>
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+                    </tr>
+                    <tr>
+                        <th> Data type </th>
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+                    <tr>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-14d7761a-6669-4484-9ad4-d0748eca7d38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14d7761a-6669-4484-9ad4-d0748eca7d38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fc57e0f-3a9e-4b28-9bde-2defb048a2da' class='xr-var-data-in' type='checkbox'><label for='data-7fc57e0f-3a9e-4b28-9bde-2defb048a2da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>
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+                        <th> Chunk </th>
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+                    <tr>
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+                        <td> 417.66 MiB </td>
+                        <td> 126.56 MiB </td>
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+                    
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+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 192, 288) </td>
+                        <td> (1, 1, 600, 192, 288) </td>
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+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 4 chunks in 3 graph layers </td>
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+                    <tr>
+                        <th> Data type </th>
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+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
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+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 417.66 MiB </td>
+                        <td> 126.56 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 192, 288) </td>
+                        <td> (1, 1, 600, 192, 288) </td>
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+                        <th> Dask graph </th>
+                        <td colspan="2"> 4 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
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+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-81acf561-dc10-4004-8f4b-6919609378be' class='xr-index-data-in' type='checkbox'/><label for='index-81acf561-dc10-4004-8f4b-6919609378be' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9d496204-3030-41de-a627-34fa83574d92' class='xr-index-data-in' type='checkbox'/><label for='index-9d496204-3030-41de-a627-34fa83574d92' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-92cb847a-4d3f-4d47-8c26-b397187d151a' class='xr-index-data-in' type='checkbox'/><label for='index-92cb847a-4d3f-4d47-8c26-b397187d151a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3eaa50cd-6bc3-436a-a7df-a938e7813094' class='xr-index-data-in' type='checkbox'/><label for='index-3eaa50cd-6bc3-436a-a7df-a938e7813094' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,
+       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,
+        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,
+        -87.82123029232025, -103.31712663173676, -121.54724076390266,
+       -142.99403876066208, -168.22507977485657,  -197.9080867022276,
+       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,
+       -379.10090386867523,   -445.992574095726,  -524.6871747076511,
+        -609.7786948084831,  -691.3894303143024,   -763.404481112957,
+        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,
+         -912.644546944648,  -936.1983984708786,   -957.485479535535,
+         -976.325407391414,   -992.556095123291],
+      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8cdffeb8-dbf1-46c5-90dc-b0814af92357' class='xr-index-data-in' type='checkbox'/><label for='index-8cdffeb8-dbf1-46c5-90dc-b0814af92357' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,
+             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,
+             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,
+             1850-10-15 12:00:00,
+             ...
+             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,
+             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,
+             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,
+             2014-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8dff8441-bc8b-400e-aff5-87a03bfc94c9' class='xr-section-summary-in' type='checkbox'  ><label for='section-8dff8441-bc8b-400e-aff5-87a03bfc94c9' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
+</div>
+</section>
+</section>
+<section id="sometimes-we-want-to-do-some-nice-tweaks-before-we-start">
+<h1>3. Sometimes we want to do some nice tweaks before we start:<a class="headerlink" href="#sometimes-we-want-to-do-some-nice-tweaks-before-we-start" title="Link to this heading">#</a></h1>
+<section id="selecting-data-and-super-quick-plotting">
+<h2>Selecting data and super quick plotting:<a class="headerlink" href="#selecting-data-and-super-quick-plotting" title="Link to this heading">#</a></h2>
+<p>xarray loads data only when it needs to (it’s lazy, Anne can explain), and you might want to early on define the subset of data you want to look at so that you don’t end up loading a lot of extra data.</p>
+<section id="see-here-for-nice-overview">
+<h3>See <a class="reference external" href="http://xarray.pydata.org/en/stable/user-guide/indexing.html">here</a> for nice overview<a class="headerlink" href="#see-here-for-nice-overview" title="Link to this heading">#</a></h3>
+<p>In order to reduce unecessary calculations and loading of data, think about which part of the data you want, and slice early on.</p>
+</section>
+</section>
+<section id="slice-in-time-the-sel-method">
+<h2>Slice in time: the sel method<a class="headerlink" href="#slice-in-time-the-sel-method" title="Link to this heading">#</a></h2>
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+.xr-index-data {
+  grid-column: 1 / -1;
+}
+
+dl.xr-attrs {
+  padding: 0;
+  margin: 0;
+  display: grid;
+  grid-template-columns: 125px auto;
+}
+
+.xr-attrs dt,
+.xr-attrs dd {
+  padding: 0;
+  margin: 0;
+  float: left;
+  padding-right: 10px;
+  width: auto;
+}
+
+.xr-attrs dt {
+  font-weight: normal;
+  grid-column: 1;
+}
+
+.xr-attrs dt:hover span {
+  display: inline-block;
+  background: var(--xr-background-color);
+  padding-right: 10px;
+}
+
+.xr-attrs dd {
+  grid-column: 2;
+  white-space: pre-wrap;
+  word-break: break-all;
+}
+
+.xr-icon-database,
+.xr-icon-file-text2,
+.xr-no-icon {
+  display: inline-block;
+  vertical-align: middle;
+  width: 1em;
+  height: 1.5em !important;
+  stroke-width: 0;
+  stroke: currentColor;
+  fill: currentColor;
+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 15GB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,
+                     nbnd: 2, lev: 32, time: 1980)
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6
+    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * time            (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:...
+    time_bnds       (time, nbnd) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;
+Dimensions without coordinates: nbnd
+Data variables:
+    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 14GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;
+    p0              float32 4B ...
+    ps              (time, lat, lon) float32 438MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;
+    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, time, lat, lon) float32 438MB dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;
+Attributes: (12/60)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:variable_id:     areacella
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5d456d01-e285-4c04-979c-86679c5b19bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5d456d01-e285-4c04-979c-86679c5b19bc' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f0c87daa-804c-4a47-9a1b-eb20b9613a50' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f0c87daa-804c-4a47-9a1b-eb20b9613a50' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-5a9ed2f4-1772-47d7-86cd-bb392085876f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a9ed2f4-1772-47d7-86cd-bb392085876f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dcb6fd3-0ca2-47ba-85e6-9b34f1a80e72' class='xr-var-data-in' type='checkbox'><label for='data-0dcb6fd3-0ca2-47ba-85e6-9b34f1a80e72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-6505f85e-b703-4b32-a019-3ca324034e48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6505f85e-b703-4b32-a019-3ca324034e48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-787b338e-497d-489c-a116-53a60c5b952f' class='xr-var-data-in' type='checkbox'><label for='data-787b338e-497d-489c-a116-53a60c5b952f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-74396d85-2069-417f-86e3-2c0b18b49dd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74396d85-2069-417f-86e3-2c0b18b49dd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01a1b832-61ef-4351-bed2-fa0853824b39' class='xr-var-data-in' type='checkbox'><label for='data-01a1b832-61ef-4351-bed2-fa0853824b39' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-ff6c56f2-76fe-4786-8a78-4c75dbe816f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff6c56f2-76fe-4786-8a78-4c75dbe816f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8487dd41-2956-4037-8abc-7a9d74f42b60' class='xr-var-data-in' type='checkbox'><label for='data-8487dd41-2956-4037-8abc-7a9d74f42b60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-28c7ff17-54ec-46b9-8f9d-a7baf5efbd24' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28c7ff17-54ec-46b9-8f9d-a7baf5efbd24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1b12f45-b183-400d-9a94-d66a72ecb2aa' class='xr-var-data-in' type='checkbox'><label for='data-a1b12f45-b183-400d-9a94-d66a72ecb2aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-70f62d83-1535-4b08-834b-ebf5ccca1d47' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70f62d83-1535-4b08-834b-ebf5ccca1d47' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e34abcc-9067-42e3-b72b-a09dd0c81328' class='xr-var-data-in' type='checkbox'><label for='data-7e34abcc-9067-42e3-b72b-a09dd0c81328' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-eb0ddb85-4485-4c21-a6ca-04718a911c40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb0ddb85-4485-4c21-a6ca-04718a911c40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d156658d-706e-4482-939e-b68596c8eaf5' class='xr-var-data-in' type='checkbox'><label for='data-d156658d-706e-4482-939e-b68596c8eaf5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
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+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-5318b861-8d7a-4a9d-a8be-faf17e7c119f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5318b861-8d7a-4a9d-a8be-faf17e7c119f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8db3584-0241-44b0-8b72-d448643dc545' class='xr-var-data-in' type='checkbox'><label for='data-c8db3584-0241-44b0-8b72-d448643dc545' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,
+        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,
+       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,
+       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,
+       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,
+       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,
+       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-abc64fb2-5d1e-4623-8bb2-06b527614f42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abc64fb2-5d1e-4623-8bb2-06b527614f42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24ffa659-db65-4af5-b2f8-ece4d59ec735' class='xr-var-data-in' type='checkbox'><label for='data-24ffa659-db65-4af5-b2f8-ece4d59ec735' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
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+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-f59664a6-7313-41a7-8a90-ac6367f2da7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f59664a6-7313-41a7-8a90-ac6367f2da7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e311fc82-3688-42fc-8ad4-395689b94309' class='xr-var-data-in' type='checkbox'><label for='data-e311fc82-3688-42fc-8ad4-395689b94309' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-9b3ccf50-dbd9-4f4f-9d81-b1718e173489' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b3ccf50-dbd9-4f4f-9d81-b1718e173489' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d719a95-80f5-4af5-8d9e-1cdf971aca86' class='xr-var-data-in' type='checkbox'><label for='data-4d719a95-80f5-4af5-8d9e-1cdf971aca86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 30.94 kiB </td>
+                        <td> 30.94 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1980, 2) </td>
+                        <td> (1980, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 6 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">1980</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-647b18f9-0938-4974-b6ca-ce11eb5e3471' class='xr-section-summary-in' type='checkbox'  checked><label for='section-647b18f9-0938-4974-b6ca-ce11eb5e3471' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-811b88e5-497f-4951-814f-38bbb2735397' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-811b88e5-497f-4951-814f-38bbb2735397' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-667455df-e72e-42a1-94f7-fe492b171406' class='xr-var-data-in' type='checkbox'><label for='data-667455df-e72e-42a1-94f7-fe492b171406' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 192, 288) </td>
+                        <td> (1, 1, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="374" height="144" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="25" y2="25" style="stroke-width:2" />
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+  <!-- Vertical lines -->
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+
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+  <text x="92.474299" y="107.474299" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(45,92.474299,107.474299)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-114ea8b5-438e-4317-96de-1239ce9aca62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-114ea8b5-438e-4317-96de-1239ce9aca62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e820f9c3-59ba-482f-b23d-50e0e00988a4' class='xr-var-data-in' type='checkbox'><label for='data-e820f9c3-59ba-482f-b23d-50e0e00988a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 256 B </td>
+                        <td> 256 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32,) </td>
+                        <td> (32,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="81" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="31" x2="120" y2="31" style="stroke-width:2" />
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+                    <tr>
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+                        <td> (32,) </td>
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+                    <tr>
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+                    </tr>
+                    <tr>
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+                        <th> Chunk </th>
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+                </thead>
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+                    <tr>
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+                        <td> (1, 1, 10, 32, 192, 288) </td>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 600, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-9c19fbfe-76a2-41c1-a29e-10598558f3e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c19fbfe-76a2-41c1-a29e-10598558f3e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c3de56c-267c-491f-b488-6f85a0897e1f' class='xr-var-data-in' type='checkbox'><label for='data-9c3de56c-267c-491f-b488-6f85a0897e1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>
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+                        <th> Chunk </th>
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+                        <td> 417.66 MiB </td>
+                        <td> 126.56 MiB </td>
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+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 192, 288) </td>
+                        <td> (1, 1, 600, 192, 288) </td>
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+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 4 chunks in 3 graph layers </td>
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+                    <tr>
+                        <th> Data type </th>
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+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 417.66 MiB </td>
+                        <td> 126.56 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 1980, 192, 288) </td>
+                        <td> (1, 1, 600, 192, 288) </td>
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+                        <th> Dask graph </th>
+                        <td colspan="2"> 4 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-10d5af22-d58c-49e5-8a66-9ba84d8d8fb8' class='xr-index-data-in' type='checkbox'/><label for='index-10d5af22-d58c-49e5-8a66-9ba84d8d8fb8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-53898e4e-1f5a-4fae-aa68-6d5f5e5afdd4' class='xr-index-data-in' type='checkbox'/><label for='index-53898e4e-1f5a-4fae-aa68-6d5f5e5afdd4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4d887f90-48b4-420c-91d7-6b1af23bfd90' class='xr-index-data-in' type='checkbox'/><label for='index-4d887f90-48b4-420c-91d7-6b1af23bfd90' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4f2340fd-5d58-40dc-b3b6-5b3471779b2e' class='xr-index-data-in' type='checkbox'/><label for='index-4f2340fd-5d58-40dc-b3b6-5b3471779b2e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,
+       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,
+        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,
+        -87.82123029232025, -103.31712663173676, -121.54724076390266,
+       -142.99403876066208, -168.22507977485657,  -197.9080867022276,
+       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,
+       -379.10090386867523,   -445.992574095726,  -524.6871747076511,
+        -609.7786948084831,  -691.3894303143024,   -763.404481112957,
+        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,
+         -912.644546944648,  -936.1983984708786,   -957.485479535535,
+         -976.325407391414,   -992.556095123291],
+      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-822197fe-3cff-42e7-af63-c6bd4c1cb890' class='xr-index-data-in' type='checkbox'/><label for='index-822197fe-3cff-42e7-af63-c6bd4c1cb890' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,
+             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,
+             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,
+             1850-10-15 12:00:00,
+             ...
+             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,
+             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,
+             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,
+             2014-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-88c803d6-1cea-49ea-aae9-18a68cd5dc2a' class='xr-section-summary-in' type='checkbox'  ><label for='section-88c803d6-1cea-49ea-aae9-18a68cd5dc2a' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
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+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">time</span> <span class="o">=</span> <span class="nb">slice</span><span class="p">(</span><span class="s1">&#39;1990-01-01&#39;</span><span class="p">,</span><span class="s1">&#39;2010-01-01&#39;</span><span class="p">))</span>
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+  display: inline-block;
+  background: var(--xr-background-color);
+  padding-right: 10px;
+}
+
+.xr-attrs dd {
+  grid-column: 2;
+  white-space: pre-wrap;
+  word-break: break-all;
+}
+
+.xr-icon-database,
+.xr-icon-file-text2,
+.xr-no-icon {
+  display: inline-block;
+  vertical-align: middle;
+  width: 1em;
+  height: 1.5em !important;
+  stroke-width: 0;
+  stroke: currentColor;
+  fill: currentColor;
+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,
+                     nbnd: 2, lev: 32, time: 240)
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6
+    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...
+    time_bnds       (time, nbnd) object 4kB dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;
+Dimensions without coordinates: nbnd
+Data variables:
+    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 2GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;
+    p0              float32 4B ...
+    ps              (time, lat, lon) float32 53MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;
+    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;
+Attributes: (12/60)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:variable_id:     areacella
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8220c364-3477-4f77-b9ce-02dc7e75afb5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8220c364-3477-4f77-b9ce-02dc7e75afb5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-670427de-485b-43b7-9cf6-52683f428f54' class='xr-section-summary-in' type='checkbox'  checked><label for='section-670427de-485b-43b7-9cf6-52683f428f54' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-597bd880-ad1d-4bb1-b5c2-38fd64a1440e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-597bd880-ad1d-4bb1-b5c2-38fd64a1440e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adfb6acf-5dca-4e2a-8268-de740094a419' class='xr-var-data-in' type='checkbox'><label for='data-adfb6acf-5dca-4e2a-8268-de740094a419' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-69d3d1a9-6a5e-4edd-89f9-3ee7d50c3480' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69d3d1a9-6a5e-4edd-89f9-3ee7d50c3480' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a104b75-2af2-4e64-9427-8148bf8ef4aa' class='xr-var-data-in' type='checkbox'><label for='data-6a104b75-2af2-4e64-9427-8148bf8ef4aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-7a7a2a3e-2106-4000-8cb8-9bc1f8762e8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a7a2a3e-2106-4000-8cb8-9bc1f8762e8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73a8ad79-6000-4393-809e-f93b0fe0851e' class='xr-var-data-in' type='checkbox'><label for='data-73a8ad79-6000-4393-809e-f93b0fe0851e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-2c0f45c8-5e56-48c0-b6a8-c4054335a301' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c0f45c8-5e56-48c0-b6a8-c4054335a301' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04e19313-7fca-4d7c-a1d3-4d18ce66fadb' class='xr-var-data-in' type='checkbox'><label for='data-04e19313-7fca-4d7c-a1d3-4d18ce66fadb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4793e73f-6e9d-4f07-9037-ba7b62e34e0c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4793e73f-6e9d-4f07-9037-ba7b62e34e0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78d28831-8308-4f81-bdbc-3f239acf9a6a' class='xr-var-data-in' type='checkbox'><label for='data-78d28831-8308-4f81-bdbc-3f239acf9a6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-390630aa-f569-4731-80b8-00c88ef02913' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-390630aa-f569-4731-80b8-00c88ef02913' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8a4e911-7e95-46d2-9b5d-bc5bf630d38d' class='xr-var-data-in' type='checkbox'><label for='data-a8a4e911-7e95-46d2-9b5d-bc5bf630d38d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-1a33044e-b0af-4005-9982-b8100e0144a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a33044e-b0af-4005-9982-b8100e0144a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8ac9951-8cd9-4e8f-8ce8-b21369158a65' class='xr-var-data-in' type='checkbox'><label for='data-c8ac9951-8cd9-4e8f-8ce8-b21369158a65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-5e2878a0-908f-4b1f-8d7d-5d2797c9fb62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e2878a0-908f-4b1f-8d7d-5d2797c9fb62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04a6f1f6-f9eb-4b6c-a5ea-4a88444e5b6a' class='xr-var-data-in' type='checkbox'><label for='data-04a6f1f6-f9eb-4b6c-a5ea-4a88444e5b6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,
+        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,
+       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,
+       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,
+       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,
+       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,
+       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-11450798-096b-478a-87b0-6bf54ab1f2b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11450798-096b-478a-87b0-6bf54ab1f2b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6effd2a4-2bb3-40fa-8797-1f12b2798c5d' class='xr-var-data-in' type='checkbox'><label for='data-6effd2a4-2bb3-40fa-8797-1f12b2798c5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-32eaa2ad-11f2-4741-8a43-5ffa3f38db0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32eaa2ad-11f2-4741-8a43-5ffa3f38db0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73599167-b6db-4efb-8379-6df3c5526ca4' class='xr-var-data-in' type='checkbox'><label for='data-73599167-b6db-4efb-8379-6df3c5526ca4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-f018d94b-683d-4ebd-bb1b-31ddb86a315b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f018d94b-683d-4ebd-bb1b-31ddb86a315b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-915d3a2b-1d25-4a79-98c9-4df41a2df884' class='xr-var-data-in' type='checkbox'><label for='data-915d3a2b-1d25-4a79-98c9-4df41a2df884' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 3.75 kiB </td>
+                        <td> 3.75 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (240, 2) </td>
+                        <td> (240, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 7 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c3a4ccaf-94e2-47ce-b8c9-2f68bb107454' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c3a4ccaf-94e2-47ce-b8c9-2f68bb107454' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-1b2e86b2-3a2e-489a-8f01-5f6662c650c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b2e86b2-3a2e-489a-8f01-5f6662c650c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5ef78c4-c214-48d7-a946-b3b480fe9c85' class='xr-var-data-in' type='checkbox'><label for='data-c5ef78c4-c214-48d7-a946-b3b480fe9c85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 192, 288) </td>
+                        <td> (1, 1, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="374" height="144" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-0c3de282-d07e-42f4-af20-7479a7b122a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c3de282-d07e-42f4-af20-7479a7b122a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbddf06c-5d64-4a14-94f1-e2e2dc9c2eb4' class='xr-var-data-in' type='checkbox'><label for='data-bbddf06c-5d64-4a14-94f1-e2e2dc9c2eb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 256 B </td>
+                        <td> 256 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32,) </td>
+                        <td> (32,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="81" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
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+                        <td> (32,) </td>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-1bc87903-7180-4019-a283-2c2537dae629' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bc87903-7180-4019-a283-2c2537dae629' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26952d42-27d2-45f3-ab1f-3004519408c7' class='xr-var-data-in' type='checkbox'><label for='data-26952d42-27d2-45f3-ab1f-3004519408c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>
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+            <table style="border-collapse: collapse;">
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+                        <th> Chunk </th>
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+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 50.62 MiB </td>
+                        <td> 25.31 MiB </td>
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+                    <tr>
+                        <th> Shape </th>
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+                        <td> (1, 1, 120, 192, 288) </td>
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+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 4 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
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+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 50.62 MiB </td>
+                        <td> 25.31 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240, 192, 288) </td>
+                        <td> (1, 1, 120, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 4 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
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+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ce436c77-b9e2-4f38-b0a8-ca5b695346ff' class='xr-index-data-in' type='checkbox'/><label for='index-ce436c77-b9e2-4f38-b0a8-ca5b695346ff' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2cb18fcf-8c5d-48f9-983f-81d06eac3001' class='xr-index-data-in' type='checkbox'/><label for='index-2cb18fcf-8c5d-48f9-983f-81d06eac3001' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-13c08cf1-5f10-4d91-80aa-62a8aa6cfbb1' class='xr-index-data-in' type='checkbox'/><label for='index-13c08cf1-5f10-4d91-80aa-62a8aa6cfbb1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2e8814cc-ccac-4360-82cd-3e38c5930607' class='xr-index-data-in' type='checkbox'/><label for='index-2e8814cc-ccac-4360-82cd-3e38c5930607' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,
+       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,
+        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,
+        -87.82123029232025, -103.31712663173676, -121.54724076390266,
+       -142.99403876066208, -168.22507977485657,  -197.9080867022276,
+       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,
+       -379.10090386867523,   -445.992574095726,  -524.6871747076511,
+        -609.7786948084831,  -691.3894303143024,   -763.404481112957,
+        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,
+         -912.644546944648,  -936.1983984708786,   -957.485479535535,
+         -976.325407391414,   -992.556095123291],
+      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ff6b705f-1344-4b9f-85a2-5b9a68b8764f' class='xr-index-data-in' type='checkbox'/><label for='index-ff6b705f-1344-4b9f-85a2-5b9a68b8764f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,
+             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,
+             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,
+             1990-10-15 12:00:00,
+             ...
+             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,
+             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,
+             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,
+             2009-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-084b135d-a421-46b2-b771-c118461b124c' class='xr-section-summary-in' type='checkbox'  ><label for='section-084b135d-a421-46b2-b771-c118461b124c' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<span style="color:red;font-weight:700;font-size:20px">
+NB: Always check that the function you are using is doing what you expect!
+</span>
+<p>You might even select only the arctic e.g.:</p>
+<section id="isel-sel-index-selecting">
+<h3>isel, sel: index selecting<a class="headerlink" href="#isel-sel-index-selecting" title="Link to this heading">#</a></h3>
+<p>Select the surface (which in this case is the last index :)</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span>
+</pre></div>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,
+                     nbnd: 2, lev: 32, time: 240)
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6
+    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * time            (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:0...
+    time_bnds       (time, nbnd) object 4kB dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;
+Dimensions without coordinates: nbnd
+Data variables:
+    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 2GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;
+    p0              float32 4B ...
+    ps              (time, lat, lon) float32 53MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;
+    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;
+Attributes: (12/60)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:variable_id:     areacella
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7077d0cd-a175-4adf-9ca6-914b74155a73' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7077d0cd-a175-4adf-9ca6-914b74155a73' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-47111de8-7674-47f9-bd63-b7aacaa9249e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-47111de8-7674-47f9-bd63-b7aacaa9249e' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-43d59d81-2f5d-43de-bdd8-9850c6508539' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43d59d81-2f5d-43de-bdd8-9850c6508539' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eafb3b7d-1d2b-42b8-8b40-6a9dea4499ff' class='xr-var-data-in' type='checkbox'><label for='data-eafb3b7d-1d2b-42b8-8b40-6a9dea4499ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-96e8173b-c8dc-46fd-82d6-6b4a87cfba20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96e8173b-c8dc-46fd-82d6-6b4a87cfba20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fd11f61-da06-4a0d-a189-dcde9e40fa1c' class='xr-var-data-in' type='checkbox'><label for='data-3fd11f61-da06-4a0d-a189-dcde9e40fa1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-1f152a9c-b7e9-494d-b2bd-6eb6e0ec12de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f152a9c-b7e9-494d-b2bd-6eb6e0ec12de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a799f3ce-ac82-48fc-8ded-5aefbb1a4a99' class='xr-var-data-in' type='checkbox'><label for='data-a799f3ce-ac82-48fc-8ded-5aefbb1a4a99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-86439893-b693-4c60-abc8-3bcc3574ead8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86439893-b693-4c60-abc8-3bcc3574ead8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45eae2f8-2c89-4a4a-99b1-bd1926fd349e' class='xr-var-data-in' type='checkbox'><label for='data-45eae2f8-2c89-4a4a-99b1-bd1926fd349e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-3f1801b8-052f-4c96-b74e-54d33e1429e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3f1801b8-052f-4c96-b74e-54d33e1429e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-828d65b9-fdb3-4f93-a5c4-f3a09b6b9125' class='xr-var-data-in' type='checkbox'><label for='data-828d65b9-fdb3-4f93-a5c4-f3a09b6b9125' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-1b62cfcb-8ecf-4bf9-94a8-93850254ab95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b62cfcb-8ecf-4bf9-94a8-93850254ab95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41e95c9a-109b-4f81-9049-38155b9bf9fc' class='xr-var-data-in' type='checkbox'><label for='data-41e95c9a-109b-4f81-9049-38155b9bf9fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-69abe9b6-04a9-43f3-a0df-ccae7d350b32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69abe9b6-04a9-43f3-a0df-ccae7d350b32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cab393cc-32a3-4cc7-a703-e7b373072142' class='xr-var-data-in' type='checkbox'><label for='data-cab393cc-32a3-4cc7-a703-e7b373072142' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-7f4e121a-0f89-48c6-aa3a-56fae93f9a0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f4e121a-0f89-48c6-aa3a-56fae93f9a0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f4650a0-f748-45f3-a43a-4ae04a2c601e' class='xr-var-data-in' type='checkbox'><label for='data-9f4650a0-f748-45f3-a43a-4ae04a2c601e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,
+        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,
+       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,
+       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,
+       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,
+       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,
+       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-7265b689-d4cd-44cb-9026-6b14b87b4130' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7265b689-d4cd-44cb-9026-6b14b87b4130' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f78d8c5-b63c-4298-8850-af7030d463de' class='xr-var-data-in' type='checkbox'><label for='data-4f78d8c5-b63c-4298-8850-af7030d463de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-8aff2af4-4c4f-412b-b059-aefe65d72e5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8aff2af4-4c4f-412b-b059-aefe65d72e5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa908b24-7424-4be9-9966-e677b7e84063' class='xr-var-data-in' type='checkbox'><label for='data-aa908b24-7424-4be9-9966-e677b7e84063' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-24470e9c-c0f0-42a1-a612-c3d670ba68ec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24470e9c-c0f0-42a1-a612-c3d670ba68ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dda272e7-5473-489a-9d56-935c7660a33b' class='xr-var-data-in' type='checkbox'><label for='data-dda272e7-5473-489a-9d56-935c7660a33b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 3.75 kiB </td>
+                        <td> 3.75 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (240, 2) </td>
+                        <td> (240, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 7 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-796bf9c0-4bbb-484b-bee8-dc098ec6a2f5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-796bf9c0-4bbb-484b-bee8-dc098ec6a2f5' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-5ee3d78c-f83e-407f-b25e-94935856da97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ee3d78c-f83e-407f-b25e-94935856da97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ec30d3b-588a-4f3a-bc88-ce11eb92fac7' class='xr-var-data-in' type='checkbox'><label for='data-8ec30d3b-588a-4f3a-bc88-ce11eb92fac7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 192, 288) </td>
+                        <td> (1, 1, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="374" height="144" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="25" y2="25" style="stroke-width:2" />
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+  <!-- Vertical lines -->
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+  <text x="92.474299" y="107.474299" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(45,92.474299,107.474299)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-7ed3b1f5-54a7-4c1d-8af1-0d7db6010130' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ed3b1f5-54a7-4c1d-8af1-0d7db6010130' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e37e032-9460-4b16-a696-a99f541b6ab2' class='xr-var-data-in' type='checkbox'><label for='data-3e37e032-9460-4b16-a696-a99f541b6ab2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 256 B </td>
+                        <td> 256 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32,) </td>
+                        <td> (32,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="81" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-edb5b770-ffd3-4a51-8ff0-fc20a6a20c33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edb5b770-ffd3-4a51-8ff0-fc20a6a20c33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e6d45bb-203b-4ab4-b00c-7996fdc8f9bd' class='xr-var-data-in' type='checkbox'><label for='data-9e6d45bb-203b-4ab4-b00c-7996fdc8f9bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 256 B </td>
+                        <td> 256 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32,) </td>
+                        <td> (32,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="81" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-f2049904-0171-4fd3-884f-d054518b1bf1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2049904-0171-4fd3-884f-d054518b1bf1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1292ec5c-0b11-4fa1-a3c4-7ffcfacdcb71' class='xr-var-data-in' type='checkbox'><label for='data-1292ec5c-0b11-4fa1-a3c4-7ffcfacdcb71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>
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+        <td>
+            <table style="border-collapse: collapse;">
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+                        <th> Chunk </th>
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+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 50.62 MiB </td>
+                        <td> 25.31 MiB </td>
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+                    <tr>
+                        <th> Shape </th>
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+                        <td> (1, 1, 120, 192, 288) </td>
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+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 4 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-8bbc4ee5-61a3-4bd9-9e3d-f1cacdd9ab54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8bbc4ee5-61a3-4bd9-9e3d-f1cacdd9ab54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c9f6203-eb52-4092-9817-2f3d80c68b11' class='xr-var-data-in' type='checkbox'><label for='data-3c9f6203-eb52-4092-9817-2f3d80c68b11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 50.62 MiB </td>
+                        <td> 25.31 MiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240, 192, 288) </td>
+                        <td> (1, 1, 120, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 4 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-eb7e5956-d275-4cc7-a934-9fbbb52f6b95' class='xr-index-data-in' type='checkbox'/><label for='index-eb7e5956-d275-4cc7-a934-9fbbb52f6b95' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-48e90d37-22d7-44ef-983d-4064ded225e1' class='xr-index-data-in' type='checkbox'/><label for='index-48e90d37-22d7-44ef-983d-4064ded225e1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0ac44de4-539e-4966-bce0-dcd56fbb7e0e' class='xr-index-data-in' type='checkbox'/><label for='index-0ac44de4-539e-4966-bce0-dcd56fbb7e0e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f346f419-ab55-473b-aa10-5aca1cec459d' class='xr-index-data-in' type='checkbox'/><label for='index-f346f419-ab55-473b-aa10-5aca1cec459d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,
+       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,
+        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,
+        -87.82123029232025, -103.31712663173676, -121.54724076390266,
+       -142.99403876066208, -168.22507977485657,  -197.9080867022276,
+       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,
+       -379.10090386867523,   -445.992574095726,  -524.6871747076511,
+        -609.7786948084831,  -691.3894303143024,   -763.404481112957,
+        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,
+         -912.644546944648,  -936.1983984708786,   -957.485479535535,
+         -976.325407391414,   -992.556095123291],
+      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a3073d83-6acb-4705-a395-00fe9660ff70' class='xr-index-data-in' type='checkbox'/><label for='index-a3073d83-6acb-4705-a395-00fe9660ff70' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,
+             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,
+             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,
+             1990-10-15 12:00:00,
+             ...
+             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,
+             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,
+             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,
+             2009-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f6768113-dbeb-43d4-9882-0054c7b2c5eb' class='xr-section-summary-in' type='checkbox'  ><label for='section-f6768113-dbeb-43d4-9882-0054c7b2c5eb' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
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+<div class="cell docutils container">
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+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss_s</span> <span class="o">=</span> <span class="n">dss</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">lev</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 213MB
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+                     nbnd: 2, time: 240)
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+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
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+Dimensions without coordinates: nbnd
+Data variables:
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+    p0              float32 4B ...
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+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
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+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-57631753-fc24-46fa-8adb-ed85a66cd516' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-57631753-fc24-46fa-8adb-ed85a66cd516' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1b2fea94-91b4-4851-8874-2d017d7b6312' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b2fea94-91b4-4851-8874-2d017d7b6312' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-a93ab33d-f04c-403c-b1fb-b07c25d3150e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a93ab33d-f04c-403c-b1fb-b07c25d3150e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65e329dc-2590-43c7-aacb-22fc4efd430d' class='xr-var-data-in' type='checkbox'><label for='data-65e329dc-2590-43c7-aacb-22fc4efd430d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-4d867e34-a50a-46b9-b55c-6b7ed9c60b1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d867e34-a50a-46b9-b55c-6b7ed9c60b1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7e7d572-5941-45c7-941b-d3dd73f99e32' class='xr-var-data-in' type='checkbox'><label for='data-b7e7d572-5941-45c7-941b-d3dd73f99e32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-9a0a1759-2810-4c92-ad30-ed9145141ea5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a0a1759-2810-4c92-ad30-ed9145141ea5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6fe0061-69ec-462b-b7a3-b2702ed54d4c' class='xr-var-data-in' type='checkbox'><label for='data-c6fe0061-69ec-462b-b7a3-b2702ed54d4c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-940e27a9-7bcb-4fd8-8c7c-8a8751268427' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-940e27a9-7bcb-4fd8-8c7c-8a8751268427' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12ba3fcb-7151-40f3-83db-4bf1e20552b3' class='xr-var-data-in' type='checkbox'><label for='data-12ba3fcb-7151-40f3-83db-4bf1e20552b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4928f9dd-ff9f-4401-8dbb-c2c5f90ac7e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4928f9dd-ff9f-4401-8dbb-c2c5f90ac7e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe5ded26-d288-4638-a24a-6729376434cf' class='xr-var-data-in' type='checkbox'><label for='data-fe5ded26-d288-4638-a24a-6729376434cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-529cc299-29e1-446e-b879-b9cce7dacbbb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-529cc299-29e1-446e-b879-b9cce7dacbbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a39c99e7-9b51-4c1b-8de2-af5fb2462b0d' class='xr-var-data-in' type='checkbox'><label for='data-a39c99e7-9b51-4c1b-8de2-af5fb2462b0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 16 B </td>
+                        <td> 16 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (2,) </td>
+                        <td> (2,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="110" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="60" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="60" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="80.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="140.000000" y="30.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,30.000000)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-9a2ceb22-b0c5-4abb-8b20-cf6187929c2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a2ceb22-b0c5-4abb-8b20-cf6187929c2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a0e79d3-ee63-4a4b-bbef-70b763bad94c' class='xr-var-data-in' type='checkbox'><label for='data-4a0e79d3-ee63-4a4b-bbef-70b763bad94c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 16 B </td>
+                        <td> 16 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (2,) </td>
+                        <td> (2,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="110" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="60" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="60" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="80.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="140.000000" y="30.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,30.000000)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-992.6</div><input id='attrs-f466ad22-d19e-4f26-b457-7f98ede59adf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f466ad22-d19e-4f26-b457-7f98ede59adf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5299ccd4-de61-4e59-a6a6-9fe3cefe29e7' class='xr-var-data-in' type='checkbox'><label for='data-5299ccd4-de61-4e59-a6a6-9fe3cefe29e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array(-992.55609512)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-95547b69-4a81-4ada-a968-fbcf2fb2e771' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95547b69-4a81-4ada-a968-fbcf2fb2e771' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-845c970d-303f-4304-bbef-d90e29eafec7' class='xr-var-data-in' type='checkbox'><label for='data-845c970d-303f-4304-bbef-d90e29eafec7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 16 B </td>
+                        <td> 16 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (2,) </td>
+                        <td> (2,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="110" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-e0b26014-f400-46ac-8dff-27df86cc2af6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0b26014-f400-46ac-8dff-27df86cc2af6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-010a58bf-3dc0-4f5c-bd2a-8b7429b526d8' class='xr-var-data-in' type='checkbox'><label for='data-010a58bf-3dc0-4f5c-bd2a-8b7429b526d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-8e9505b6-7416-4ecb-b721-e6980e4a10f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8e9505b6-7416-4ecb-b721-e6980e4a10f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d81abd4-f099-49b1-8ec6-e14355199085' class='xr-var-data-in' type='checkbox'><label for='data-9d81abd4-f099-49b1-8ec6-e14355199085' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 3.75 kiB </td>
+                        <td> 3.75 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (240, 2) </td>
+                        <td> (240, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 7 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
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+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-443b222b-8db3-4fe6-9ba8-b9cee925deeb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-443b222b-8db3-4fe6-9ba8-b9cee925deeb' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-ba6f9b1a-b167-4987-9777-3c3e132db94d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba6f9b1a-b167-4987-9777-3c3e132db94d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a304aff-e616-4677-abae-b8bfa6f4c7e9' class='xr-var-data-in' type='checkbox'><label for='data-9a304aff-e616-4677-abae-b8bfa6f4c7e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 192, 288) </td>
+                        <td> (1, 1, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="374" height="144" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="25" y2="25" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-4f29448a-29aa-43b1-b72d-5ae9b70c45a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f29448a-29aa-43b1-b72d-5ae9b70c45a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0fef89f-1b64-44e8-adbb-f266b754b24f' class='xr-var-data-in' type='checkbox'><label for='data-a0fef89f-1b64-44e8-adbb-f266b754b24f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 8 B </td>
+                        <td> 8 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> () </td>
+                        <td> () </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-39ac93a5-4026-48fd-87af-1c5004ae5412' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39ac93a5-4026-48fd-87af-1c5004ae5412' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-265bd1ed-82b4-49f7-a768-bd87dd752308' class='xr-var-data-in' type='checkbox'><label for='data-265bd1ed-82b4-49f7-a768-bd87dd752308' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 8 B </td>
+                        <td> 8 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> () </td>
+                        <td> () </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        
+        </td>
+    </tr>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-26de26ad-d18a-4771-a903-2ecdca6739e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26de26ad-d18a-4771-a903-2ecdca6739e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f4275b9-19b0-408e-a5f1-dcc64953670c' class='xr-var-data-in' type='checkbox'><label for='data-6f4275b9-19b0-408e-a5f1-dcc64953670c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>
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+                        <th> Chunk </th>
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+                        <th> Bytes </th>
+                        <td> 50.62 MiB </td>
+                        <td> 25.31 MiB </td>
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+                    <tr>
+                        <th> Shape </th>
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+                        <td> (1, 1, 120, 192, 288) </td>
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+                        <th> Data type </th>
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+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5da3881a-ef28-470b-b7c6-8984cf32b5c5' class='xr-section-summary-in' type='checkbox'  ><label for='section-5da3881a-ef28-470b-b7c6-8984cf32b5c5' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-21cdf139-e5fe-4852-9136-966c5a04b155' class='xr-index-data-in' type='checkbox'/><label for='index-21cdf139-e5fe-4852-9136-966c5a04b155' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,
+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-81ba0b0d-a689-436a-a23a-9a89adf9ce51' class='xr-index-data-in' type='checkbox'/><label for='index-81ba0b0d-a689-436a-a23a-9a89adf9ce51' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a25c9db7-9ebe-415d-ad0c-bd27c56c5946' class='xr-index-data-in' type='checkbox'/><label for='index-a25c9db7-9ebe-415d-ad0c-bd27c56c5946' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9f5b5461-705e-4951-b9cc-cf75e625aa71' class='xr-index-data-in' type='checkbox'/><label for='index-9f5b5461-705e-4951-b9cc-cf75e625aa71' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d095bdb9-3069-4c3f-9465-7f89984f096e' class='xr-index-data-in' type='checkbox'/><label for='index-d095bdb9-3069-4c3f-9465-7f89984f096e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,
+             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,
+             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,
+             1990-10-15 12:00:00,
+             ...
+             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,
+             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,
+             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,
+             2009-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4cf22325-da59-498a-a6eb-f10e7eb3f999' class='xr-section-summary-in' type='checkbox'  ><label for='section-4cf22325-da59-498a-a6eb-f10e7eb3f999' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss_s</span><span class="p">[</span><span class="s1">&#39;mmrso4&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">time</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">robust</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f3a1471b810&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/35860f8e5c62b642d91bc8968d442f59fab3df81ba35379c3e0c0b2df9f93569.png" src="../../../_images/35860f8e5c62b642d91bc8968d442f59fab3df81ba35379c3e0c0b2df9f93569.png" />
+</div>
+</div>
+</section>
+</section>
+<section id="calculates-variables-and-assign-attributes">
+<h2>3.2 Calculates variables and assign attributes!<a class="headerlink" href="#calculates-variables-and-assign-attributes" title="Link to this heading">#</a></h2>
+<p>Nice for plotting and to keep track of what is in your dataset (especially ‘units’ and ‘standard_name’/’long_name’ will be looked for by xarray.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">dss</span><span class="p">[</span><span class="s1">&#39;tas&#39;</span><span class="p">]</span><span class="o">-</span><span class="mf">273.15</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">dss</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">assign_attrs</span><span class="p">({</span><span class="s1">&#39;units&#39;</span><span class="p">:</span> <span class="s1">&#39;$^\circ$C&#39;</span><span class="p">})</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span>
+</pre></div>
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+                         lon: 288)&gt; Size: 53MB
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+  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
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+Attributes:
+    units:    $^\circ$C</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'T_C'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 240</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-16f38a7b-0ebf-4356-85f4-7bd6d371b794' class='xr-array-in' type='checkbox' checked><label for='section-16f38a7b-0ebf-4356-85f4-7bd6d371b794' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>
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+  <text x="213.823529" y="158.823529" font-size="1.0rem" font-weight="100" text-anchor="middle" >288</text>
+  <text x="293.823529" y="98.823529" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,293.823529,98.823529)">192</text>
+  <text x="114.411765" y="129.411765" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(45,114.411765,129.411765)">240</text>
+</svg>
+        </td>
+    </tr>
+</table></div></div></li><li class='xr-section-item'><input id='section-e7d8cacd-409d-4916-8d39-1f8ef9582fb9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e7d8cacd-409d-4916-8d39-1f8ef9582fb9' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-65b66b99-7dc1-46a8-bdc4-e7aa5b297397' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65b66b99-7dc1-46a8-bdc4-e7aa5b297397' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7d11e60-1fdb-4076-9e77-5efa6cafb5d7' class='xr-var-data-in' type='checkbox'><label for='data-b7d11e60-1fdb-4076-9e77-5efa6cafb5d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-1448faec-52ab-45ae-8a4b-cc65239e586b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1448faec-52ab-45ae-8a4b-cc65239e586b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d109ba0d-d109-4b74-ae85-f7574d58e60d' class='xr-var-data-in' type='checkbox'><label for='data-d109ba0d-d109-4b74-ae85-f7574d58e60d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-e8ae2ceb-cb32-41b5-b20d-c6babf9e98d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8ae2ceb-cb32-41b5-b20d-c6babf9e98d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d5b77a1-2a8f-462a-b092-f6471121d55b' class='xr-var-data-in' type='checkbox'><label for='data-9d5b77a1-2a8f-462a-b092-f6471121d55b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-adefa5e1-6e99-446a-ab2f-167ded05259e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-adefa5e1-6e99-446a-ab2f-167ded05259e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a62c5cac-a580-4ef3-9bf2-e2411754019f' class='xr-var-data-in' type='checkbox'><label for='data-a62c5cac-a580-4ef3-9bf2-e2411754019f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-3e6ea819-771c-4565-8b87-47699b71fb77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e6ea819-771c-4565-8b87-47699b71fb77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-690d11e8-6d16-4732-b5b5-0f5aba9daed7' class='xr-var-data-in' type='checkbox'><label for='data-690d11e8-6d16-4732-b5b5-0f5aba9daed7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1237dea0-a0a6-4478-a151-a902e0c42d4a' class='xr-section-summary-in' type='checkbox'  ><label for='section-1237dea0-a0a6-4478-a151-a902e0c42d4a' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-61a0a3c7-0356-4971-ac16-3bd27b5be525' class='xr-index-data-in' type='checkbox'/><label for='index-61a0a3c7-0356-4971-ac16-3bd27b5be525' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,
+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-68d52203-871e-49ca-b966-e1d5b9921179' class='xr-index-data-in' type='checkbox'/><label for='index-68d52203-871e-49ca-b966-e1d5b9921179' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-143021a4-2b62-4d2d-a365-88ba3c2ffa32' class='xr-index-data-in' type='checkbox'/><label for='index-143021a4-2b62-4d2d-a365-88ba3c2ffa32' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0c24e6c5-0f9c-4045-a50a-455b1e6a9a3f' class='xr-index-data-in' type='checkbox'/><label for='index-0c24e6c5-0f9c-4045-a50a-455b1e6a9a3f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7b65f158-4fca-48dc-b246-1d9e0d532a39' class='xr-index-data-in' type='checkbox'/><label for='index-7b65f158-4fca-48dc-b246-1d9e0d532a39' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,
+             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,
+             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,
+             1990-10-15 12:00:00,
+             ...
+             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,
+             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,
+             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,
+             2009-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-307a7d40-517b-4cf1-a617-dc2b56173972' class='xr-section-summary-in' type='checkbox'  checked><label for='section-307a7d40-517b-4cf1-a617-dc2b56173972' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\circ$C</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<span style="color:green;font-weight:700;font-size:20px">
+May always be small things you need to adjust: 
+</span>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;time&#39;</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><div><svg style="position: absolute; width: 0; height: 0; overflow: hidden">
+<defs>
+<symbol id="icon-database" viewBox="0 0 32 32">
+<path d="M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z"></path>
+<path d="M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z"></path>
+<path d="M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z"></path>
+</symbol>
+<symbol id="icon-file-text2" viewBox="0 0 32 32">
+<path d="M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z"></path>
+<path d="M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z"></path>
+<path d="M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z"></path>
+<path d="M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z"></path>
+</symbol>
+</defs>
+</svg>
+<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.
+ *
+ */
+
+:root {
+  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));
+  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));
+  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));
+  --xr-border-color: var(--jp-border-color2, #e0e0e0);
+  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);
+  --xr-background-color: var(--jp-layout-color0, white);
+  --xr-background-color-row-even: var(--jp-layout-color1, white);
+  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);
+}
+
+html[theme=dark],
+body[data-theme=dark],
+body.vscode-dark {
+  --xr-font-color0: rgba(255, 255, 255, 1);
+  --xr-font-color2: rgba(255, 255, 255, 0.54);
+  --xr-font-color3: rgba(255, 255, 255, 0.38);
+  --xr-border-color: #1F1F1F;
+  --xr-disabled-color: #515151;
+  --xr-background-color: #111111;
+  --xr-background-color-row-even: #111111;
+  --xr-background-color-row-odd: #313131;
+}
+
+.xr-wrap {
+  display: block !important;
+  min-width: 300px;
+  max-width: 700px;
+}
+
+.xr-text-repr-fallback {
+  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */
+  display: none;
+}
+
+.xr-header {
+  padding-top: 6px;
+  padding-bottom: 6px;
+  margin-bottom: 4px;
+  border-bottom: solid 1px var(--xr-border-color);
+}
+
+.xr-header > div,
+.xr-header > ul {
+  display: inline;
+  margin-top: 0;
+  margin-bottom: 0;
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 240)&gt; Size: 2kB
+array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)
+Coordinates:
+  * time     (time) object 2kB 1990-01-15 12:00:00 ... 2009-12-15 12:00:00
+Attributes:
+    axis:           T
+    bounds:         time_bnds
+    standard_name:  time
+    title:          time
+    type:           double</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-62c80d0d-a472-4874-8239-941dd2d10deb' class='xr-array-in' type='checkbox' checked><label for='section-62c80d0d-a472-4874-8239-941dd2d10deb' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1990-01-15 12:00:00 1990-02-14 00:00:00 ... 2009-12-15 12:00:00</span></div><div class='xr-array-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></div></li><li class='xr-section-item'><input id='section-ab579307-1b0e-4fb0-8ef8-bf35a3a184f2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ab579307-1b0e-4fb0-8ef8-bf35a3a184f2' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1990-01-15 12:00:00 ... 2009-12-...</div><input id='attrs-99fa0e1f-9fa4-4b2f-bc48-70e46fb197cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99fa0e1f-9fa4-4b2f-bc48-70e46fb197cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f867744f-7019-4dc3-a1b1-6bcb1024c141' class='xr-var-data-in' type='checkbox'><label for='data-f867744f-7019-4dc3-a1b1-6bcb1024c141' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1990, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1990, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2009, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2009, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9bc5c033-1bfa-4c3d-825d-fc87102f8df9' class='xr-section-summary-in' type='checkbox'  ><label for='section-9bc5c033-1bfa-4c3d-825d-fc87102f8df9' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-892fa850-3733-4c7f-ada4-f01f2f50a83b' class='xr-index-data-in' type='checkbox'/><label for='index-892fa850-3733-4c7f-ada4-f01f2f50a83b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1990-01-15 12:00:00, 1990-02-14 00:00:00, 1990-03-15 12:00:00,
+             1990-04-15 00:00:00, 1990-05-15 12:00:00, 1990-06-15 00:00:00,
+             1990-07-15 12:00:00, 1990-08-15 12:00:00, 1990-09-15 00:00:00,
+             1990-10-15 12:00:00,
+             ...
+             2009-03-15 12:00:00, 2009-04-15 00:00:00, 2009-05-15 12:00:00,
+             2009-06-15 00:00:00, 2009-07-15 12:00:00, 2009-08-15 12:00:00,
+             2009-09-15 00:00:00, 2009-10-15 12:00:00, 2009-11-15 00:00:00,
+             2009-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=240, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-325bb4b6-dae6-4f96-9993-52675f554e60' class='xr-section-summary-in' type='checkbox'  checked><label for='section-325bb4b6-dae6-4f96-9993-52675f554e60' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<p>This calendar is in cftime and noLeap. Sometimes this causes issues when plotting timeseries, so just for fun we will convert to normal calendar because it’s anyway monthly.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;time&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">dss</span><span class="p">[</span><span class="s1">&#39;time&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">()</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">to_datetimeindex</span><span class="p">()</span>
+</pre></div>
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+<div class="cell_output docutils container">
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_11040/4195133999.py:1: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, &#39;noleap&#39;, to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.
+  dss[&#39;time&#39;] = dss[&#39;time&#39;].to_dataframe().index.to_datetimeindex()
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;time&#39;</span><span class="p">]</span>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 240)&gt; Size: 2kB
+array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,
+       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,
+       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)
+Coordinates:
+  * time     (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12-15T12:...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 240</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-490a5e84-8a88-4335-8cf2-1c309452f016' class='xr-array-in' type='checkbox' checked><label for='section-490a5e84-8a88-4335-8cf2-1c309452f016' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1990-01-15T12:00:00 1990-02-14 ... 2009-11-15 2009-12-15T12:00:00</span></div><div class='xr-array-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,
+       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,
+       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-7a1cc611-d902-4d11-a3b8-bcffc6b3df78' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7a1cc611-d902-4d11-a3b8-bcffc6b3df78' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-15T12:00:00 ... 2009-12-...</div><input id='attrs-4366eef1-1e9a-40f4-8b1d-5eee2af69940' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4366eef1-1e9a-40f4-8b1d-5eee2af69940' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d806627-0850-4100-8aaf-7c60b9d474b2' class='xr-var-data-in' type='checkbox'><label for='data-1d806627-0850-4100-8aaf-7c60b9d474b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,
+       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,
+       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-369c5f38-0118-4899-9e9f-0076e859bafd' class='xr-section-summary-in' type='checkbox'  ><label for='section-369c5f38-0118-4899-9e9f-0076e859bafd' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ca77bca3-bbc6-41c6-ab6f-1e74c79d55d3' class='xr-index-data-in' type='checkbox'/><label for='index-ca77bca3-bbc6-41c6-ab6f-1e74c79d55d3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-15 12:00:00&#x27;, &#x27;1990-02-14 00:00:00&#x27;,
+               &#x27;1990-03-15 12:00:00&#x27;, &#x27;1990-04-15 00:00:00&#x27;,
+               &#x27;1990-05-15 12:00:00&#x27;, &#x27;1990-06-15 00:00:00&#x27;,
+               &#x27;1990-07-15 12:00:00&#x27;, &#x27;1990-08-15 12:00:00&#x27;,
+               &#x27;1990-09-15 00:00:00&#x27;, &#x27;1990-10-15 12:00:00&#x27;,
+               ...
+               &#x27;2009-03-15 12:00:00&#x27;, &#x27;2009-04-15 00:00:00&#x27;,
+               &#x27;2009-05-15 12:00:00&#x27;, &#x27;2009-06-15 00:00:00&#x27;,
+               &#x27;2009-07-15 12:00:00&#x27;, &#x27;2009-08-15 12:00:00&#x27;,
+               &#x27;2009-09-15 00:00:00&#x27;, &#x27;2009-10-15 12:00:00&#x27;,
+               &#x27;2009-11-15 00:00:00&#x27;, &#x27;2009-12-15 12:00:00&#x27;],
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-25b8e1f0-67b3-4c93-860b-005702d58c4d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-25b8e1f0-67b3-4c93-860b-005702d58c4d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+</div>
+<span style="color:green;font-weight:700;font-size:20px">
+We get a warning, but it's ok as long as we know what we are doing. 
+</span>
+<section id="convert-longitude">
+<h3>3.3 Convert longitude:<a class="headerlink" href="#convert-longitude" title="Link to this heading">#</a></h3>
+<p>this data comes in 0–360 degrees, but often -180 to 180 is more convenient. So we can convert:</p>
+<p><strong>NOTE:</strong> Maybe you want to put this in a module? Or a package..</p>
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+.xr-index-data {
+  grid-column: 1 / -1;
+}
+
+dl.xr-attrs {
+  padding: 0;
+  margin: 0;
+  display: grid;
+  grid-template-columns: 125px auto;
+}
+
+.xr-attrs dt,
+.xr-attrs dd {
+  padding: 0;
+  margin: 0;
+  float: left;
+  padding-right: 10px;
+  width: auto;
+}
+
+.xr-attrs dt {
+  font-weight: normal;
+  grid-column: 1;
+}
+
+.xr-attrs dt:hover span {
+  display: inline-block;
+  background: var(--xr-background-color);
+  padding-right: 10px;
+}
+
+.xr-attrs dd {
+  grid-column: 2;
+  white-space: pre-wrap;
+  word-break: break-all;
+}
+
+.xr-icon-database,
+.xr-icon-file-text2,
+.xr-no-icon {
+  display: inline-block;
+  vertical-align: middle;
+  width: 1em;
+  height: 1.5em !important;
+  stroke-width: 0;
+  stroke: currentColor;
+  fill: currentColor;
+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,
+                     nbnd: 2, lev: 32, time: 240)
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+  * lon             (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 356.2 357.5 358.8
+    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6
+    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * time            (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12...
+    time_bnds       (time, nbnd) object 4kB dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;
+Dimensions without coordinates: nbnd
+Data variables:
+    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    mmrso4          (member_id, dcpp_init_year, time, lev, lat, lon) float32 2GB dask.array&lt;chunksize=(1, 1, 10, 32, 192, 288), meta=np.ndarray&gt;
+    p0              float32 4B ...
+    ps              (time, lat, lon) float32 53MB dask.array&lt;chunksize=(10, 192, 288), meta=np.ndarray&gt;
+    hurs            (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;
+    T_C             (member_id, dcpp_init_year, time, lat, lon) float32 53MB dask.array&lt;chunksize=(1, 1, 120, 192, 288), meta=np.ndarray&gt;
+Attributes: (12/60)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:variable_id:     areacella
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8179e209-a9b0-4b1d-8612-b0f578a502a6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8179e209-a9b0-4b1d-8612-b0f578a502a6' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6569d756-d1d8-446d-bd3a-5d2f913ba495' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6569d756-d1d8-446d-bd3a-5d2f913ba495' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-0ce22ada-6a97-4acd-bf37-b00822a7f00c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ce22ada-6a97-4acd-bf37-b00822a7f00c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09a3df3c-6f3a-42bd-805a-3abdb75de44a' class='xr-var-data-in' type='checkbox'><label for='data-09a3df3c-6f3a-42bd-805a-3abdb75de44a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.25 2.5 ... 356.2 357.5 358.8</div><input id='attrs-24ea265d-caab-40d9-ab3e-679f55865b94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24ea265d-caab-40d9-ab3e-679f55865b94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcbb4e9b-6afe-4a84-a2d1-b3033667546d' class='xr-var-data-in' type='checkbox'><label for='data-dcbb4e9b-6afe-4a84-a2d1-b3033667546d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-c9e7c052-7a12-4b55-b511-c59d0b68b97b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9e7c052-7a12-4b55-b511-c59d0b68b97b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce39dbba-1d92-4c1f-a911-d71690fb02c3' class='xr-var-data-in' type='checkbox'><label for='data-ce39dbba-1d92-4c1f-a911-d71690fb02c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-e22c37fd-1eb9-4fa5-a4f7-e1cb28378b07' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e22c37fd-1eb9-4fa5-a4f7-e1cb28378b07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64867cfe-ae54-43de-ad5b-d6ad62608ec4' class='xr-var-data-in' type='checkbox'><label for='data-64867cfe-ae54-43de-ad5b-d6ad62608ec4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-d0c9f6d9-50ea-49e6-a898-7c0b08879bd9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0c9f6d9-50ea-49e6-a898-7c0b08879bd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c9771e4-b806-45da-b8df-775ea3e26454' class='xr-var-data-in' type='checkbox'><label for='data-6c9771e4-b806-45da-b8df-775ea3e26454' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-67c57826-b33f-4182-839c-65151ed97fa6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67c57826-b33f-4182-839c-65151ed97fa6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f88e1d8-2bba-465e-a6c9-bfae41e0d34b' class='xr-var-data-in' type='checkbox'><label for='data-7f88e1d8-2bba-465e-a6c9-bfae41e0d34b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-2a467e0e-a2b2-49fe-a714-81bc0b54f7d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a467e0e-a2b2-49fe-a714-81bc0b54f7d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ab080bf-ebc9-43e2-b499-53fa3a018e5e' class='xr-var-data-in' type='checkbox'><label for='data-5ab080bf-ebc9-43e2-b499-53fa3a018e5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-19dd20e1-9626-4e81-8256-4164238bd171' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19dd20e1-9626-4e81-8256-4164238bd171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdd5f79a-8753-413f-b96b-c038c8da88ac' class='xr-var-data-in' type='checkbox'><label for='data-fdd5f79a-8753-413f-b96b-c038c8da88ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,
+        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,
+       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,
+       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,
+       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,
+       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,
+       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-f8fcc718-209c-4dc0-ab07-fe08d9e28c60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8fcc718-209c-4dc0-ab07-fe08d9e28c60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7442f197-9dd6-4609-9fc5-9f7af23a75d4' class='xr-var-data-in' type='checkbox'><label for='data-7442f197-9dd6-4609-9fc5-9f7af23a75d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
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+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-15T12:00:00 ... 2009-12-...</div><input id='attrs-cfd057c8-0c85-40da-8f1d-5f4d5d4485cf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cfd057c8-0c85-40da-8f1d-5f4d5d4485cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-429e084b-74c1-472e-bc1f-bfc6b42e5594' class='xr-var-data-in' type='checkbox'><label for='data-429e084b-74c1-472e-bc1f-bfc6b42e5594' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,
+       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,
+       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-f85e04c7-a70a-4652-90c0-2be4f9b7ce17' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f85e04c7-a70a-4652-90c0-2be4f9b7ce17' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcfb9e9f-8ad6-42f2-bfce-499d057fb309' class='xr-var-data-in' type='checkbox'><label for='data-dcfb9e9f-8ad6-42f2-bfce-499d057fb309' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 3.75 kiB </td>
+                        <td> 3.75 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (240, 2) </td>
+                        <td> (240, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 7 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
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+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-b23b2dbf-5d5d-43cb-a92f-30786be24e28' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b23b2dbf-5d5d-43cb-a92f-30786be24e28' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-48d14d0e-3a70-4a00-8572-d6b3826906ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48d14d0e-3a70-4a00-8572-d6b3826906ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-905ed74b-6bdc-461d-bb4d-6e1460d8d763' class='xr-var-data-in' type='checkbox'><label for='data-905ed74b-6bdc-461d-bb4d-6e1460d8d763' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 192, 288) </td>
+                        <td> (1, 1, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="374" height="144" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-0d674740-8e70-43fd-baf2-75baf06d9a7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d674740-8e70-43fd-baf2-75baf06d9a7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fa67ef9-269c-4238-8319-f9716b64e098' class='xr-var-data-in' type='checkbox'><label for='data-7fa67ef9-269c-4238-8319-f9716b64e098' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>a_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 256 B </td>
+                        <td> 256 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32,) </td>
+                        <td> (32,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="81" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
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+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b3194e2-0335-4ffc-aedb-549008e33ac6' class='xr-section-summary-in' type='checkbox'  ><label for='section-6b3194e2-0335-4ffc-aedb-549008e33ac6' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a2411746-f485-4773-a663-04513e4e8361' class='xr-index-data-in' type='checkbox'/><label for='index-a2411746-f485-4773-a663-04513e4e8361' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,
+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7956913a-78ad-4c48-a0d4-f7d1fdffe4c6' class='xr-index-data-in' type='checkbox'/><label for='index-7956913a-78ad-4c48-a0d4-f7d1fdffe4c6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,   1.25,    2.5,   3.75,    5.0,   6.25,    7.5,   8.75,   10.0,
+        11.25,
+       ...
+        347.5, 348.75,  350.0, 351.25,  352.5, 353.75,  355.0, 356.25,  357.5,
+       358.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2b1504f1-debf-4e96-af49-948fba1ad173' class='xr-index-data-in' type='checkbox'/><label for='index-2b1504f1-debf-4e96-af49-948fba1ad173' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b330423a-a2e0-48e1-ae01-8ace5526ad7c' class='xr-index-data-in' type='checkbox'/><label for='index-b330423a-a2e0-48e1-ae01-8ace5526ad7c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c8f7eba7-82df-4eac-961a-668b4fa20f24' class='xr-index-data-in' type='checkbox'/><label for='index-c8f7eba7-82df-4eac-961a-668b4fa20f24' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,
+       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,
+        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,
+        -87.82123029232025, -103.31712663173676, -121.54724076390266,
+       -142.99403876066208, -168.22507977485657,  -197.9080867022276,
+       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,
+       -379.10090386867523,   -445.992574095726,  -524.6871747076511,
+        -609.7786948084831,  -691.3894303143024,   -763.404481112957,
+        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,
+         -912.644546944648,  -936.1983984708786,   -957.485479535535,
+         -976.325407391414,   -992.556095123291],
+      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d46453f2-e055-4de5-a4c5-61ff4a5d8c1a' class='xr-index-data-in' type='checkbox'/><label for='index-d46453f2-e055-4de5-a4c5-61ff4a5d8c1a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-15 12:00:00&#x27;, &#x27;1990-02-14 00:00:00&#x27;,
+               &#x27;1990-03-15 12:00:00&#x27;, &#x27;1990-04-15 00:00:00&#x27;,
+               &#x27;1990-05-15 12:00:00&#x27;, &#x27;1990-06-15 00:00:00&#x27;,
+               &#x27;1990-07-15 12:00:00&#x27;, &#x27;1990-08-15 12:00:00&#x27;,
+               &#x27;1990-09-15 00:00:00&#x27;, &#x27;1990-10-15 12:00:00&#x27;,
+               ...
+               &#x27;2009-03-15 12:00:00&#x27;, &#x27;2009-04-15 00:00:00&#x27;,
+               &#x27;2009-05-15 12:00:00&#x27;, &#x27;2009-06-15 00:00:00&#x27;,
+               &#x27;2009-07-15 12:00:00&#x27;, &#x27;2009-08-15 12:00:00&#x27;,
+               &#x27;2009-09-15 00:00:00&#x27;, &#x27;2009-10-15 12:00:00&#x27;,
+               &#x27;2009-11-15 00:00:00&#x27;, &#x27;2009-12-15 12:00:00&#x27;],
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0658d920-9972-4c8d-ad0f-f8e397f8abc2' class='xr-section-summary-in' type='checkbox'  ><label for='section-0658d920-9972-4c8d-ad0f-f8e397f8abc2' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">convert_lon_to_180</span><span class="p">(</span><span class="n">ds</span><span class="p">):</span>
+    <span class="n">ds</span><span class="p">[</span><span class="s1">&#39;lon&#39;</span><span class="p">]</span> <span class="o">=</span><span class="p">(</span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;lon&#39;</span><span class="p">]</span><span class="o">+</span> <span class="mi">180</span><span class="p">)</span> <span class="o">%</span> <span class="mi">360</span> <span class="o">-</span> <span class="mi">180</span>
+    <span class="n">ds</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">sortby</span><span class="p">(</span><span class="s1">&#39;lon&#39;</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">ds</span>
+
+<span class="k">def</span> <span class="nf">convert_lon_to_360</span><span class="p">(</span><span class="n">ds</span><span class="p">):</span>
+    <span class="n">ds</span><span class="p">[</span><span class="s1">&#39;lon&#39;</span><span class="p">]</span> <span class="o">=</span><span class="n">ds</span><span class="p">[</span><span class="s1">&#39;lon&#39;</span><span class="p">]</span><span class="o">%</span> <span class="mi">360</span>
+    <span class="n">ds</span> <span class="o">=</span> <span class="n">ds</span><span class="o">.</span><span class="n">sortby</span><span class="p">(</span><span class="s1">&#39;lon&#39;</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">lon</span> <span class="o">%</span> <span class="mi">360</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>(migth want to move this to a module!)</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span> <span class="o">=</span> <span class="n">convert_lon_to_180</span><span class="p">(</span><span class="n">dss</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;lon&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">attrs</span><span class="p">[</span><span class="s1">&#39;units&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;$^\circ$ East&#39;</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Notice how the labels use both the attribute “standard_name” and “units” from the dataset.</p>
+</section>
+</section>
+</section>
+<section id="the-easiest-interpolation-select-with-nearest-neighboor">
+<h1>4. The easiest interpolation: select with ‘nearest’ neighboor<a class="headerlink" href="#the-easiest-interpolation-select-with-nearest-neighboor" title="Link to this heading">#</a></h1>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">lon</span><span class="o">=</span><span class="mf">1.3</span><span class="p">,</span><span class="n">method</span><span class="o">=</span><span class="s1">&#39;nearest&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">&#39;time&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f39f04b5a90&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/0dcd0c43b0746a3782885a6de1ca0c5ec865fa6707208affc6436b5f5da77a2b.png" src="../../../_images/0dcd0c43b0746a3782885a6de1ca0c5ec865fa6707208affc6436b5f5da77a2b.png" />
+</div>
+</div>
+<p>Example: let’s select zeppelin station:
+78.906661, 11.889203</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">lat_zep</span> <span class="o">=</span><span class="mf">78.906661</span>
+<span class="n">lon_zep</span> <span class="o">=</span> <span class="mf">11.889203</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">lon</span><span class="o">=</span><span class="n">lon_zep</span><span class="p">,</span> <span class="n">lat</span><span class="o">=</span><span class="n">lat_zep</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">&#39;nearest&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7f39f0598090&gt;]
+</pre></div>
+</div>
+<img alt="../../../_images/71d4a69eb7ff1affe22d2964504823c8882372ee3cbfc72abb3daa32ff57b0f8.png" src="../../../_images/71d4a69eb7ff1affe22d2964504823c8882372ee3cbfc72abb3daa32ff57b0f8.png" />
+</div>
+</div>
+<section id="super-quick-averaging-etc">
+<h2>Super quick averaging etc<a class="headerlink" href="#super-quick-averaging-etc" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">da_so4</span> <span class="o">=</span> <span class="n">dss</span><span class="p">[</span><span class="s1">&#39;mmrso4&#39;</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Mean:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">da_so4</span><span class="o">.</span><span class="n">mean</span><span class="p">([</span><span class="s1">&#39;time&#39;</span><span class="p">,</span><span class="s1">&#39;lon&#39;</span><span class="p">],</span> <span class="n">keep_attrs</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span><span class="c1">#ylim=[1000,100], yscale=&#39;log&#39;)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f39f0552450&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/88bd7cc6ce60155545514ddbdb2034ff1f0ef4c083e0ef0d09fc55f8dc7eb969.png" src="../../../_images/88bd7cc6ce60155545514ddbdb2034ff1f0ef4c083e0ef0d09fc55f8dc7eb969.png" />
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">da_so4</span><span class="p">[</span><span class="s1">&#39;lev&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">da_so4</span><span class="p">[</span><span class="s1">&#39;lev&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">da_so4</span><span class="o">.</span><span class="n">mean</span><span class="p">([</span><span class="s1">&#39;time&#39;</span><span class="p">,</span><span class="s1">&#39;lon&#39;</span><span class="p">],</span> <span class="n">keep_attrs</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ylim</span><span class="o">=</span><span class="p">[</span><span class="mi">1000</span><span class="p">,</span><span class="mi">100</span><span class="p">],</span> <span class="n">yscale</span><span class="o">=</span><span class="s1">&#39;log&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f39f030c790&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/f2036c3df2360cca07e9c48e0cabd0afefcac1e1eb25bf2a1c046bb9b5d76a11.png" src="../../../_images/f2036c3df2360cca07e9c48e0cabd0afefcac1e1eb25bf2a1c046bb9b5d76a11.png" />
+</div>
+</div>
+<p>Standard deviation</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">std</span><span class="p">([</span><span class="s1">&#39;time&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f39f0291b10&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/9366f65d6d91082ee23dc0a715489b7408ee832b1aaddf04a8611d2ed9c1afe4.png" src="../../../_images/9366f65d6d91082ee23dc0a715489b7408ee832b1aaddf04a8611d2ed9c1afe4.png" />
+</div>
+</div>
+<p>Temperature change much stronger over land than ocean…</p>
+</section>
+<section id="mask-data-and-groupby-pick-out-seasons">
+<h2>Mask data and groupby: pick out seasons<a class="headerlink" href="#mask-data-and-groupby-pick-out-seasons" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">month</span> <span class="o">=</span> <span class="n">ds</span><span class="p">[</span><span class="s1">&#39;time.month&#39;</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">month</span>
+</pre></div>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;month&#x27; (time: 1980)&gt; Size: 16kB
+array([ 1,  2,  3, ..., 10, 11, 12])
+Coordinates:
+  * time     (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'month'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2a309a11-032f-421d-a589-d0a3343b8af3' class='xr-array-in' type='checkbox' checked><label for='section-2a309a11-032f-421d-a589-d0a3343b8af3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 ... 11 12 1 2 3 4 5 6 7 8 9 10 11 12</span></div><div class='xr-array-data'><pre>array([ 1,  2,  3, ..., 10, 11, 12])</pre></div></div></li><li class='xr-section-item'><input id='section-2a3f6928-3e08-4d17-a633-1ba797e235a7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2a3f6928-3e08-4d17-a633-1ba797e235a7' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:00:00 ... 2014-12-...</div><input id='attrs-3da7b6aa-5114-482b-b16c-048387c6080b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3da7b6aa-5114-482b-b16c-048387c6080b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-527ab759-689a-414b-ad1c-c381e44c8d78' class='xr-var-data-in' type='checkbox'><label for='data-527ab759-689a-414b-ad1c-c381e44c8d78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0, has_year_zero=True),
+       ...,
+       cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0, has_year_zero=True),
+       cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0, has_year_zero=True)],
+      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f2836d4-b0f0-4792-ae7a-3ee1851d9ec1' class='xr-section-summary-in' type='checkbox'  ><label for='section-0f2836d4-b0f0-4792-ae7a-3ee1851d9ec1' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3e48fa5b-d994-4bc9-901a-87d20abe4dca' class='xr-index-data-in' type='checkbox'/><label for='index-3e48fa5b-d994-4bc9-901a-87d20abe4dca' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-15 12:00:00, 1850-02-14 00:00:00, 1850-03-15 12:00:00,
+             1850-04-15 00:00:00, 1850-05-15 12:00:00, 1850-06-15 00:00:00,
+             1850-07-15 12:00:00, 1850-08-15 12:00:00, 1850-09-15 00:00:00,
+             1850-10-15 12:00:00,
+             ...
+             2014-03-15 12:00:00, 2014-04-15 00:00:00, 2014-05-15 12:00:00,
+             2014-06-15 00:00:00, 2014-07-15 12:00:00, 2014-08-15 12:00:00,
+             2014-09-15 00:00:00, 2014-10-15 12:00:00, 2014-11-15 00:00:00,
+             2014-12-15 12:00:00],
+            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5d4e7c82-90a2-4824-a835-c93c553f5c5d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5d4e7c82-90a2-4824-a835-c93c553f5c5d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+</div>
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+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss_JA</span> <span class="o">=</span> <span class="n">dss</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">month</span><span class="o">.</span><span class="n">isin</span><span class="p">([</span><span class="mi">7</span><span class="p">,</span><span class="mi">8</span><span class="p">]))</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="s1">&#39;time&#39;</span><span class="p">)</span>
+</pre></div>
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+ */
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+:root {
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+  --xr-border-color: var(--jp-border-color2, #e0e0e0);
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+html[theme=dark],
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+  --xr-border-color: #1F1F1F;
+  --xr-disabled-color: #515151;
+  --xr-background-color: #111111;
+  --xr-background-color-row-even: #111111;
+  --xr-background-color-row-odd: #313131;
+}
+
+.xr-wrap {
+  display: block !important;
+  min-width: 300px;
+  max-width: 700px;
+}
+
+.xr-text-repr-fallback {
+  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */
+  display: none;
+}
+
+.xr-header {
+  padding-top: 6px;
+  padding-bottom: 6px;
+  margin-bottom: 4px;
+  border-bottom: solid 1px var(--xr-border-color);
+}
+
+.xr-header > div,
+.xr-header > ul {
+  display: inline;
+  margin-top: 0;
+  margin-bottom: 0;
+}
+
+.xr-obj-type,
+.xr-array-name {
+  margin-left: 2px;
+  margin-right: 10px;
+}
+
+.xr-obj-type {
+  color: var(--xr-font-color2);
+}
+
+.xr-sections {
+  padding-left: 0 !important;
+  display: grid;
+  grid-template-columns: 150px auto auto 1fr 20px 20px;
+}
+
+.xr-section-item {
+  display: contents;
+}
+
+.xr-section-item input {
+  display: none;
+}
+
+.xr-section-item input + label {
+  color: var(--xr-disabled-color);
+}
+
+.xr-section-item input:enabled + label {
+  cursor: pointer;
+  color: var(--xr-font-color2);
+}
+
+.xr-section-item input:enabled + label:hover {
+  color: var(--xr-font-color0);
+}
+
+.xr-section-summary {
+  grid-column: 1;
+  color: var(--xr-font-color2);
+  font-weight: 500;
+}
+
+.xr-section-summary > span {
+  display: inline-block;
+  padding-left: 0.5em;
+}
+
+.xr-section-summary-in:disabled + label {
+  color: var(--xr-font-color2);
+}
+
+.xr-section-summary-in + label:before {
+  display: inline-block;
+  content: '►';
+  font-size: 11px;
+  width: 15px;
+  text-align: center;
+}
+
+.xr-section-summary-in:disabled + label:before {
+  color: var(--xr-disabled-color);
+}
+
+.xr-section-summary-in:checked + label:before {
+  content: '▼';
+}
+
+.xr-section-summary-in:checked + label > span {
+  display: none;
+}
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+.xr-section-summary,
+.xr-section-inline-details {
+  padding-top: 4px;
+  padding-bottom: 4px;
+}
+
+.xr-section-inline-details {
+  grid-column: 2 / -1;
+}
+
+.xr-section-details {
+  display: none;
+  grid-column: 1 / -1;
+  margin-bottom: 5px;
+}
+
+.xr-section-summary-in:checked ~ .xr-section-details {
+  display: contents;
+}
+
+.xr-array-wrap {
+  grid-column: 1 / -1;
+  display: grid;
+  grid-template-columns: 20px auto;
+}
+
+.xr-array-wrap > label {
+  grid-column: 1;
+  vertical-align: top;
+}
+
+.xr-preview {
+  color: var(--xr-font-color3);
+}
+
+.xr-array-preview,
+.xr-array-data {
+  padding: 0 5px !important;
+  grid-column: 2;
+}
+
+.xr-array-data,
+.xr-array-in:checked ~ .xr-array-preview {
+  display: none;
+}
+
+.xr-array-in:checked ~ .xr-array-data,
+.xr-array-preview {
+  display: inline-block;
+}
+
+.xr-dim-list {
+  display: inline-block !important;
+  list-style: none;
+  padding: 0 !important;
+  margin: 0;
+}
+
+.xr-dim-list li {
+  display: inline-block;
+  padding: 0;
+  margin: 0;
+}
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+  content: '(';
+}
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+  content: ')';
+}
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+  content: ',';
+  padding-right: 5px;
+}
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+  font-weight: bold;
+}
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+.xr-var-item {
+  display: contents;
+}
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+.xr-var-item > div,
+.xr-var-item label,
+.xr-var-item > .xr-var-name span {
+  background-color: var(--xr-background-color-row-even);
+  margin-bottom: 0;
+}
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+  padding-right: 5px;
+}
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+.xr-var-list > li:nth-child(odd) > label,
+.xr-var-list > li:nth-child(odd) > .xr-var-name span {
+  background-color: var(--xr-background-color-row-odd);
+}
+
+.xr-var-name {
+  grid-column: 1;
+}
+
+.xr-var-dims {
+  grid-column: 2;
+}
+
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+  grid-column: 3;
+  text-align: right;
+  color: var(--xr-font-color2);
+}
+
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+  grid-column: 4;
+}
+
+.xr-index-preview {
+  grid-column: 2 / 5;
+  color: var(--xr-font-color2);
+}
+
+.xr-var-name,
+.xr-var-dims,
+.xr-var-dtype,
+.xr-preview,
+.xr-attrs dt {
+  white-space: nowrap;
+  overflow: hidden;
+  text-overflow: ellipsis;
+  padding-right: 10px;
+}
+
+.xr-var-name:hover,
+.xr-var-dims:hover,
+.xr-var-dtype:hover,
+.xr-attrs dt:hover {
+  overflow: visible;
+  width: auto;
+  z-index: 1;
+}
+
+.xr-var-attrs,
+.xr-var-data,
+.xr-index-data {
+  display: none;
+  background-color: var(--xr-background-color) !important;
+  padding-bottom: 5px !important;
+}
+
+.xr-var-attrs-in:checked ~ .xr-var-attrs,
+.xr-var-data-in:checked ~ .xr-var-data,
+.xr-index-data-in:checked ~ .xr-index-data {
+  display: block;
+}
+
+.xr-var-data > table {
+  float: right;
+}
+
+.xr-var-name span,
+.xr-var-data,
+.xr-index-name div,
+.xr-index-data,
+.xr-attrs {
+  padding-left: 25px !important;
+}
+
+.xr-attrs,
+.xr-var-attrs,
+.xr-var-data,
+.xr-index-data {
+  grid-column: 1 / -1;
+}
+
+dl.xr-attrs {
+  padding: 0;
+  margin: 0;
+  display: grid;
+  grid-template-columns: 125px auto;
+}
+
+.xr-attrs dt,
+.xr-attrs dd {
+  padding: 0;
+  margin: 0;
+  float: left;
+  padding-right: 10px;
+  width: auto;
+}
+
+.xr-attrs dt {
+  font-weight: normal;
+  grid-column: 1;
+}
+
+.xr-attrs dt:hover span {
+  display: inline-block;
+  background: var(--xr-background-color);
+  padding-right: 10px;
+}
+
+.xr-attrs dd {
+  grid-column: 2;
+  white-space: pre-wrap;
+  word-break: break-all;
+}
+
+.xr-icon-database,
+.xr-icon-file-text2,
+.xr-no-icon {
+  display: inline-block;
+  vertical-align: middle;
+  width: 1em;
+  height: 1.5em !important;
+  stroke-width: 0;
+  stroke: currentColor;
+  fill: currentColor;
+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 8MB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, lat: 192, lon: 288,
+                     lev: 32, nbnd: 2)
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+  * lon             (lon) float64 2kB -180.0 -178.8 -177.5 ... 176.2 177.5 178.8
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6
+    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+Dimensions without coordinates: nbnd
+Data variables:
+    areacella       (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+    a               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    b               (lev) float64 256B dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;
+    mmrso4          (member_id, dcpp_init_year, lev, lat, lon) float32 7MB dask.array&lt;chunksize=(1, 1, 32, 192, 288), meta=np.ndarray&gt;
+    p0              float32 4B nan
+    ps              (lat, lon) float32 221kB dask.array&lt;chunksize=(192, 288), meta=np.ndarray&gt;
+    hurs            (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;
+    T_C             (member_id, dcpp_init_year, lat, lon) float32 221kB dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6ab30d99-93fd-4a8d-b514-649f48821b91' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6ab30d99-93fd-4a8d-b514-649f48821b91' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span>nbnd</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b49dabfd-500b-4dda-be36-4f781a1b63b5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b49dabfd-500b-4dda-be36-4f781a1b63b5' class='xr-section-summary' >Coordinates: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-33674f01-9e3e-4510-83bd-5ad3122bf446' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33674f01-9e3e-4510-83bd-5ad3122bf446' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46fe1050-0dcb-4247-8918-b40600bdab39' class='xr-var-data-in' type='checkbox'><label for='data-46fe1050-0dcb-4247-8918-b40600bdab39' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
+       -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
+       -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
+        62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
+        68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -178.8 ... 177.5 178.8</div><input id='attrs-eaeb27f9-120a-4444-a916-687dee503e8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eaeb27f9-120a-4444-a916-687dee503e8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20c24ddb-3ffa-4a96-8aa0-a8533cad96a1' class='xr-var-data-in' type='checkbox'><label for='data-20c24ddb-3ffa-4a96-8aa0-a8533cad96a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array([-180.  , -178.75, -177.5 , ...,  176.25,  177.5 ,  178.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-5a480531-0240-4ea9-808b-b3a416e2dd79' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5a480531-0240-4ea9-808b-b3a416e2dd79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e94ea6be-fe52-4a24-9383-823e5b3ae83e' class='xr-var-data-in' type='checkbox'><label for='data-e94ea6be-fe52-4a24-9383-823e5b3ae83e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5abde633-e641-4220-a919-375f20c5ae30' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5abde633-e641-4220-a919-375f20c5ae30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-871d6ac5-16ff-4612-a23c-09cc01904708' class='xr-var-data-in' type='checkbox'><label for='data-871d6ac5-16ff-4612-a23c-09cc01904708' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-2f97f747-3b6a-4625-a797-86d347b84e83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f97f747-3b6a-4625-a797-86d347b84e83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-919ef6ea-69c9-4994-bd47-8369e7553277' class='xr-var-data-in' type='checkbox'><label for='data-919ef6ea-69c9-4994-bd47-8369e7553277' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,
+        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,
+       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,
+       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,
+       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,
+       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,
+       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-3adcf97c-29ea-48d6-93fd-a5e279d254a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3adcf97c-29ea-48d6-93fd-a5e279d254a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0343f0ee-7db1-4fa8-8049-a7f25a1c7245' class='xr-var-data-in' type='checkbox'><label for='data-0343f0ee-7db1-4fa8-8049-a7f25a1c7245' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 14 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-4bc0a916-5aaf-411e-8f92-a8042b2c31ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bc0a916-5aaf-411e-8f92-a8042b2c31ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb1a9a7f-dd5e-4b10-afad-c864cb72e5ec' class='xr-var-data-in' type='checkbox'><label for='data-bb1a9a7f-dd5e-4b10-afad-c864cb72e5ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-9a29220f-77bd-4220-8ba2-1047392e3d3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a29220f-77bd-4220-8ba2-1047392e3d3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2b8d808-8f39-40b9-bb33-16abcf1cc146' class='xr-var-data-in' type='checkbox'><label for='data-a2b8d808-8f39-40b9-bb33-16abcf1cc146' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-6ecfb1a7-833b-4f7b-9cdf-3909919d44f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ecfb1a7-833b-4f7b-9cdf-3909919d44f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bad563a1-53a4-4fd5-bb5d-02820b4f2ea5' class='xr-var-data-in' type='checkbox'><label for='data-bad563a1-53a4-4fd5-bb5d-02820b4f2ea5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-aa8ecb86-e1af-4454-85e5-68a3633c6511' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aa8ecb86-e1af-4454-85e5-68a3633c6511' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-ef150ac5-573a-40c8-bd6a-2634ebf685d1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ef150ac5-573a-40c8-bd6a-2634ebf685d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66eaf47f-e45d-4591-b2fc-ee3b8bc3e2f1' class='xr-var-data-in' type='checkbox'><label for='data-66eaf47f-e45d-4591-b2fc-ee3b8bc3e2f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 192, 288) </td>
+                        <td> (1, 1, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 9 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="374" height="144" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="25" x2="25" y2="25" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="25" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="25" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,25.412616514582485 0.0,25.412616514582485" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="45.412617" font-size="1.0rem" font-weight="100" text-anchor="middle" >1</text>
+  <text x="45.412617" y="12.706308" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,45.412617,12.706308)">1</text>
+
+
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+                        <td> 256 B </td>
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+                        <td> (32,) </td>
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+                    <tr>
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+    <tr>
+        <td>
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+                        <th> Array </th>
+                        <th> Chunk </th>
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+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
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+                    
+                    <tr>
+                        <th> Shape </th>
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+                        <td> (192, 288) </td>
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+                        <th> Chunk </th>
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+                        <td> 216.00 kiB </td>
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+                    
+                    <tr>
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+                        <td> (1, 1, 192, 288) </td>
+                        <td> (1, 1, 192, 288) </td>
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+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 10 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
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+                        <th> Data type </th>
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+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-11a637df-ec17-4c79-9034-0b27214101c9' class='xr-index-data-in' type='checkbox'/><label for='index-11a637df-ec17-4c79-9034-0b27214101c9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -180.0, -178.75,  -177.5, -176.25,  -175.0, -173.75,  -172.5, -171.25,
+        -170.0, -168.75,
+       ...
+         167.5,  168.75,   170.0,  171.25,   172.5,  173.75,   175.0,  176.25,
+         177.5,  178.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-14644386-645b-432a-bcab-0a3a1945e5d7' class='xr-index-data-in' type='checkbox'/><label for='index-14644386-645b-432a-bcab-0a3a1945e5d7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0cc5da31-f29a-4f4c-b685-5dfa5a4fb211' class='xr-index-data-in' type='checkbox'/><label for='index-0cc5da31-f29a-4f4c-b685-5dfa5a4fb211' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ddf25b1e-7433-42c4-ad0e-223c9f08fe04' class='xr-index-data-in' type='checkbox'/><label for='index-ddf25b1e-7433-42c4-ad0e-223c9f08fe04' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,
+       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,
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+       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,
+       -379.10090386867523,   -445.992574095726,  -524.6871747076511,
+        -609.7786948084831,  -691.3894303143024,   -763.404481112957,
+        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,
+         -912.644546944648,  -936.1983984708786,   -957.485479535535,
+         -976.325407391414,   -992.556095123291],
+      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-41449b54-fe2f-4e0d-9fca-9e6f7586284c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-41449b54-fe2f-4e0d-9fca-9e6f7586284c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss_season</span> <span class="o">=</span> <span class="n">dss</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;time.season&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">keep_attrs</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss_season</span>
+</pre></div>
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+}
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+}
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+.xr-no-icon {
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+  stroke-width: 0;
+  stroke: currentColor;
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+}
+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 33MB
+Dimensions:         (season: 4, member_id: 1, dcpp_init_year: 1, lev: 32,
+                     lat: 192, lon: 288, nbnd: 2)
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+  * lon             (lon) float64 2kB -180.0 -178.8 -177.5 ... 176.2 177.5 178.8
+    lon_bnds        (lon, nbnd) float64 5kB dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+    a_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+    b_bnds          (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * lev             (lev) float64 256B -3.643 -7.595 -14.36 ... -976.3 -992.6
+    lev_bnds        (lev, nbnd) float64 512B dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;
+  * season          (season) object 32B &#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;
+Dimensions without coordinates: nbnd
+Data variables:
+    mmrso4          (season, member_id, dcpp_init_year, lev, lat, lon) float32 28MB dask.array&lt;chunksize=(4, 1, 1, 32, 192, 288), meta=np.ndarray&gt;
+    ps              (season, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 192, 288), meta=np.ndarray&gt;
+    hurs            (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;
+    tas             (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;
+    T_C             (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;
+    areacella       (season, member_id, dcpp_init_year, lat, lon) float32 885kB dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;
+    a               (season, lev) float64 1kB dask.array&lt;chunksize=(4, 32), meta=np.ndarray&gt;
+    b               (season, lev) float64 1kB dask.array&lt;chunksize=(4, 32), meta=np.ndarray&gt;
+    p0              (season) float32 16B 1e+05 1e+05 1e+05 1e+05
+Attributes: (12/60)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:variable_id:     areacella
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5ff0d995-95bf-42b1-a6bd-b81b0b926176' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5ff0d995-95bf-42b1-a6bd-b81b0b926176' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>season</span>: 4</li><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>lev</span>: 32</li><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li><li><span>nbnd</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a669e3fc-7e94-425e-9750-22339f68faaa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a669e3fc-7e94-425e-9750-22339f68faaa' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.06 -88.12 ... 89.06 90.0</div><input id='attrs-67aa772d-3b21-4ee7-bf03-a6b854483a24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67aa772d-3b21-4ee7-bf03-a6b854483a24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9504ae63-bb8a-4835-9633-0cd567bb24bb' class='xr-var-data-in' type='checkbox'><label for='data-9504ae63-bb8a-4835-9633-0cd567bb24bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
+       -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
+       -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
+       -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
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+       -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
+       -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
+       -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
+       -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
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+       -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
+       -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
+       -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
+       -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
+       -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
+        -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
+         0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
+         6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
+        11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
+        17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
+        23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
+        28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
+        34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
+        40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
+        45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
+        51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
+        57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
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+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -178.8 ... 177.5 178.8</div><input id='attrs-679ccd82-84bc-409f-8157-f954622bdc9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-679ccd82-84bc-409f-8157-f954622bdc9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86ee9e78-b931-4b76-b8e3-fc28643445b3' class='xr-var-data-in' type='checkbox'><label for='data-86ee9e78-b931-4b76-b8e3-fc28643445b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array([-180.  , -178.75, -177.5 , ...,  176.25,  177.5 ,  178.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(288, 2), meta=np.ndarray&gt;</div><input id='attrs-d21f7fb7-d74b-46d5-9cbc-bf9650c98958' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d21f7fb7-d74b-46d5-9cbc-bf9650c98958' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78c9847a-b205-4fec-b66f-36d4f0008a8e' class='xr-var-data-in' type='checkbox'><label for='data-78c9847a-b205-4fec-b66f-36d4f0008a8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4.50 kiB </td>
+                        <td> 4.50 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (288, 2) </td>
+                        <td> (288, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 14 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">288</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-24595160-8f93-4f2b-97ec-cda7a99914c0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24595160-8f93-4f2b-97ec-cda7a99914c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-358bcf22-f5b6-4060-82c1-0eaa229b3aad' class='xr-var-data-in' type='checkbox'><label for='data-358bcf22-f5b6-4060-82c1-0eaa229b3aad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-326f7d5d-372a-48f8-a8a4-9d55a797bf8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-326f7d5d-372a-48f8-a8a4-9d55a797bf8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05f703db-f19e-4574-901b-18b6eff27690' class='xr-var-data-in' type='checkbox'><label for='data-05f703db-f19e-4574-901b-18b6eff27690' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-6c953831-4148-4495-8aba-88de59c30ca0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c953831-4148-4495-8aba-88de59c30ca0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a4f3514-dd5a-4098-b102-1182e7860e38' class='xr-var-data-in' type='checkbox'><label for='data-1a4f3514-dd5a-4098-b102-1182e7860e38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-9cbea943-163c-4145-93dc-1b440f80db1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cbea943-163c-4145-93dc-1b440f80db1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1718c8d3-689f-4948-a94d-b91bee022f3e' class='xr-var-data-in' type='checkbox'><label for='data-1718c8d3-689f-4948-a94d-b91bee022f3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.643 -7.595 ... -976.3 -992.6</div><input id='attrs-d729580e-4513-4ff4-834c-22bef5b44e9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d729580e-4513-4ff4-834c-22bef5b44e9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b86b27b-f5e9-47a1-bdeb-b34e7dff51ef' class='xr-var-data-in' type='checkbox'><label for='data-6b86b27b-f5e9-47a1-bdeb-b34e7dff51ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([  -3.643466,   -7.59482 ,  -14.356632,  -24.61222 ,  -35.92325 ,
+        -43.19375 ,  -51.677499,  -61.520498,  -73.750958,  -87.82123 ,
+       -103.317127, -121.547241, -142.994039, -168.22508 , -197.908087,
+       -232.828619, -273.910817, -322.241902, -379.100904, -445.992574,
+       -524.687175, -609.778695, -691.38943 , -763.404481, -820.858369,
+       -859.534767, -887.020249, -912.644547, -936.198398, -957.48548 ,
+       -976.325407, -992.556095])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 2), meta=np.ndarray&gt;</div><input id='attrs-bad7011a-cf4e-4b48-aeaa-45f4c81a5b39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bad7011a-cf4e-4b48-aeaa-45f4c81a5b39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7122bbb3-cfd6-46ca-b58b-4e63d64aec3e' class='xr-var-data-in' type='checkbox'><label for='data-7122bbb3-cfd6-46ca-b58b-4e63d64aec3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 512 B </td>
+                        <td> 512 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (32, 2) </td>
+                        <td> (32, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 2 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="85" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="35" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="35" y1="0" x2="35" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 35.85954734920875,0.0 35.85954734920875,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="17.929774" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="55.859547" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,55.859547,60.000000)">32</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>season</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</div><input id='attrs-1bc04582-f52e-413c-9eee-777bef806aae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1bc04582-f52e-413c-9eee-777bef806aae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f709ec84-86d4-4be2-8a7d-1fe32ba0d348' class='xr-var-data-in' type='checkbox'><label for='data-f709ec84-86d4-4be2-8a7d-1fe32ba0d348' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b9074222-9e80-4b6a-9b87-30c5d9da6f9e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b9074222-9e80-4b6a-9b87-30c5d9da6f9e' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(season, member_id, dcpp_init_year, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1, 1, 32, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-4dde5401-d947-41ba-a253-23b03fa55ef2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dde5401-d947-41ba-a253-23b03fa55ef2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25cda548-382b-41ff-99dc-46b9c2d6d562' class='xr-var-data-in' type='checkbox'><label for='data-25cda548-382b-41ff-99dc-46b9c2d6d562' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>
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+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 864.00 kiB </td>
+                        <td> 864.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (4, 1, 1, 192, 288) </td>
+                        <td> (4, 1, 1, 192, 288) </td>
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+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 12 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
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+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
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+                        <td> 864.00 kiB </td>
+                        <td> 864.00 kiB </td>
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+                    
+                    <tr>
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+                        <td> (4, 1, 1, 192, 288) </td>
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+                        <td colspan="2"> 1 chunks in 13 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(season, member_id, dcpp_init_year, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 1, 1, 192, 288), meta=np.ndarray&gt;</div><input id='attrs-88a7c5b5-a0f7-4c18-abac-d9edf6af93de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88a7c5b5-a0f7-4c18-abac-d9edf6af93de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9bd87d9-c7f3-4082-a953-6b0ea4673e67' class='xr-var-data-in' type='checkbox'><label for='data-d9bd87d9-c7f3-4082-a953-6b0ea4673e67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 864.00 kiB </td>
+                        <td> 864.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (4, 1, 1, 192, 288) </td>
+                        <td> (4, 1, 1, 192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 5 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
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+    <tr>
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+                        <th> Array </th>
+                        <th> Chunk </th>
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+                        <td> 1.00 kiB </td>
+                        <td> 1.00 kiB </td>
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+                        <td> (4, 32) </td>
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+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
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+  <line x1="0" y1="39" x2="120" y2="39" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="39" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="39" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,39.793935054828374 0.0,39.793935054828374" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="59.793935" font-size="1.0rem" font-weight="100" text-anchor="middle" >32</text>
+  <text x="140.000000" y="19.896968" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,19.896968)">4</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>(season, lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 32), meta=np.ndarray&gt;</div><input id='attrs-d5efbafa-7f51-4358-b014-6e22e8e458b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5efbafa-7f51-4358-b014-6e22e8e458b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85ae5e22-0ed0-48d7-9415-e4bedb143727' class='xr-var-data-in' type='checkbox'><label for='data-85ae5e22-0ed0-48d7-9415-e4bedb143727' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 1.00 kiB </td>
+                        <td> 1.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (4, 32) </td>
+                        <td> (4, 32) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="89" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="39" x2="120" y2="39" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="39" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="39" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,39.793935054828374 0.0,39.793935054828374" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="59.793935" font-size="1.0rem" font-weight="100" text-anchor="middle" >32</text>
+  <text x="140.000000" y="19.896968" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,19.896968)">4</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1e+05 1e+05 1e+05 1e+05</div><input id='attrs-d5a332a2-2c48-45fe-98f6-0345628f322e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5a332a2-2c48-45fe-98f6-0345628f322e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eea7dba5-97ed-416c-817a-1870aee3b861' class='xr-var-data-in' type='checkbox'><label for='data-eea7dba5-97ed-416c-817a-1870aee3b861' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>array([100000., 100000., 100000., 100000.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5bbc8f0a-93a8-4172-89e5-c518dad58609' class='xr-section-summary-in' type='checkbox'  ><label for='section-5bbc8f0a-93a8-4172-89e5-c518dad58609' class='xr-section-summary' >Indexes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cf216927-486b-4029-80e0-ee3a3cc7a722' class='xr-index-data-in' type='checkbox'/><label for='index-cf216927-486b-4029-80e0-ee3a3cc7a722' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,
+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-82f9ed0f-6ef1-4c9c-92d8-11892eee777a' class='xr-index-data-in' type='checkbox'/><label for='index-82f9ed0f-6ef1-4c9c-92d8-11892eee777a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -180.0, -178.75,  -177.5, -176.25,  -175.0, -173.75,  -172.5, -171.25,
+        -170.0, -168.75,
+       ...
+         167.5,  168.75,   170.0,  171.25,   172.5,  173.75,   175.0,  176.25,
+         177.5,  178.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ba55cccf-2b75-4000-be73-8d2cbbf44ce0' class='xr-index-data-in' type='checkbox'/><label for='index-ba55cccf-2b75-4000-be73-8d2cbbf44ce0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f17db395-c967-44a2-9a7e-323f25a27dff' class='xr-index-data-in' type='checkbox'/><label for='index-f17db395-c967-44a2-9a7e-323f25a27dff' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-625f8b56-9dc8-43e3-bbb1-186468e6ccfe' class='xr-index-data-in' type='checkbox'/><label for='index-625f8b56-9dc8-43e3-bbb1-186468e6ccfe' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  -3.64346569404006,  -7.594819646328688, -14.356632251292467,
+       -24.612220004200935,  -35.92325001955032,   -43.1937500834465,
+        -51.67749896645546,  -61.52049824595451,  -73.75095784664154,
+        -87.82123029232025, -103.31712663173676, -121.54724076390266,
+       -142.99403876066208, -168.22507977485657,  -197.9080867022276,
+       -232.82861895859241,  -273.9108167588711,  -322.2419023513794,
+       -379.10090386867523,   -445.992574095726,  -524.6871747076511,
+        -609.7786948084831,  -691.3894303143024,   -763.404481112957,
+        -820.8583686500788,  -859.5347665250301,  -887.0202489197254,
+         -912.644546944648,  -936.1983984708786,   -957.485479535535,
+         -976.325407391414,   -992.556095123291],
+      dtype=&#x27;float64&#x27;, name=&#x27;lev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>season</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-eed6bbcb-db72-452c-ab4c-a301a6904771' class='xr-index-data-in' type='checkbox'/><label for='index-eed6bbcb-db72-452c-ab4c-a301a6904771' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=&#x27;object&#x27;, name=&#x27;season&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2ee5b3f0-ef63-466b-b5ac-4a47f9908646' class='xr-section-summary-in' type='checkbox'  ><label for='section-2ee5b3f0-ef63-466b-b5ac-4a47f9908646' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss_season</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">col</span><span class="o">=</span><span class="s1">&#39;season&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f39e8560790&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/943dafe510e20fe627b644d9345043f7855f7bb112201bd7673574af476c72af.png" src="../../../_images/943dafe510e20fe627b644d9345043f7855f7bb112201bd7673574af476c72af.png" />
+</div>
+</div>
+</section>
+<section id="controle-the-plot-visuals">
+<h2>Controle the plot visuals:<a class="headerlink" href="#controle-the-plot-visuals" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss_season</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">col</span><span class="o">=</span><span class="s1">&#39;season&#39;</span><span class="p">,</span>
+                       <span class="n">cmap</span> <span class="o">=</span> <span class="s1">&#39;coolwarm&#39;</span><span class="p">,</span><span class="c1">#ax=ax,</span>
+                       <span class="n">xlim</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">100</span><span class="p">,</span><span class="mi">100</span><span class="p">],</span>
+                       <span class="n">cbar_kwargs</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;label&#39;</span><span class="p">:</span><span class="s1">&#39;Temperature [$^\circ$C]&#39;</span><span class="p">}</span>
+                      <span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f37d5e02fd0&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/84f6d1d82e31574bcbafe235f29e27704d39499e89dead3ca4a8b44076e36ca7.png" src="../../../_images/84f6d1d82e31574bcbafe235f29e27704d39499e89dead3ca4a8b44076e36ca7.png" />
+</div>
+</div>
+</section>
+</section>
+<section id="plotting-with-cartopy">
+<h1>5. Plotting with cartopy<a class="headerlink" href="#plotting-with-cartopy" title="Link to this heading">#</a></h1>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">cartopy</span> <span class="k">as</span> <span class="nn">cy</span>
+<span class="kn">import</span> <span class="nn">cartopy.crs</span> <span class="k">as</span> <span class="nn">ccrs</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">da_plt</span> <span class="o">=</span> <span class="n">dss</span><span class="p">[</span><span class="s1">&#39;mmrso4&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">lev</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="s1">&#39;time&#39;</span><span class="p">,</span> <span class="n">keep_attrs</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span><span class="c1">#(&#39;member_id&#39;)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;mmrso4&#x27; (lat: 192, lon: 288)&gt; Size: 221kB
+dask.array&lt;getitem, shape=(192, 288), dtype=float32, chunksize=(192, 288), chunktype=numpy.ndarray&gt;
+Coordinates:
+  * lat             (lat) float64 2kB -90.0 -89.06 -88.12 ... 88.12 89.06 90.0
+  * lon             (lon) float64 2kB -180.0 -178.8 -177.5 ... 176.2 177.5 178.8
+    member_id       &lt;U8 32B &#x27;r1i1p1f1&#x27;
+    dcpp_init_year  float64 8B nan
+    lev             float64 8B -992.6
+Attributes: (12/19)
+    cell_measures:  area: areacella
+    cell_methods:   area: time: mean
+    comment:        Dry mass of sulfate (SO4) in aerosol particles as a fract...
+    description:    Dry mass of sulfate (SO4) in aerosol particles as a fract...
+    frequency:      mon
+    id:             mmrso4
+    ...             ...
+    time_label:     time-mean
+    time_title:     Temporal mean
+    title:          Aerosol Sulfate Mass Mixing Ratio
+    type:           real
+    units:          kg kg-1
+    variable_id:    mmrso4</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'mmrso4'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>lon</span>: 288</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-24680508-0ef3-4c9b-9ab5-c73ed099d6b5' class='xr-array-in' type='checkbox' checked><label for='section-24680508-0ef3-4c9b-9ab5-c73ed099d6b5' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(192, 288), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
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+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 216.00 kiB </td>
+                        <td> 216.00 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (192, 288) </td>
+                        <td> (192, 288) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 11 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+        73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
+        79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
+        85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -178.8 ... 177.5 178.8</div><input id='attrs-ea99162c-8811-425b-a90c-d78a4bffd88c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea99162c-8811-425b-a90c-d78a4bffd88c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c2fbfba-5abd-4911-9045-9aafd61eff2f' class='xr-var-data-in' type='checkbox'><label for='data-3c2fbfba-5abd-4911-9045-9aafd61eff2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array([-180.  , -178.75, -177.5 , ...,  176.25,  177.5 ,  178.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>member_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U8</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-c2d7c383-1a01-4d7b-96e8-a97422c34b6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2d7c383-1a01-4d7b-96e8-a97422c34b6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e75f2550-e7ff-4210-aec9-51ae4820a056' class='xr-var-data-in' type='checkbox'><label for='data-e75f2550-e7ff-4210-aec9-51ae4820a056' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;r1i1p1f1&#x27;, dtype=&#x27;&lt;U8&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dcpp_init_year</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-28bb3e63-23a1-4149-9f8a-79036f11e98f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28bb3e63-23a1-4149-9f8a-79036f11e98f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3995dd75-f4e2-4f71-824a-49536ec56e85' class='xr-var-data-in' type='checkbox'><label for='data-3995dd75-f4e2-4f71-824a-49536ec56e85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-992.6</div><input id='attrs-2a7e9fd3-5b1c-40d6-b663-47f0c9c44a90' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a7e9fd3-5b1c-40d6-b663-47f0c9c44a90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-495cfdf8-4eb1-41c5-873e-61215c1603d6' class='xr-var-data-in' type='checkbox'><label for='data-495cfdf8-4eb1-41c5-873e-61215c1603d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array(-992.55609512)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f93ad7ac-adbf-4fdb-9aba-ca06533c979f' class='xr-section-summary-in' type='checkbox'  ><label for='section-f93ad7ac-adbf-4fdb-9aba-ca06533c979f' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9e951233-7748-475b-9b83-0d60894bae96' class='xr-index-data-in' type='checkbox'/><label for='index-9e951233-7748-475b-9b83-0d60894bae96' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.05759162303664,  -88.1151832460733,
+       -87.17277486910994,  -86.2303664921466, -85.28795811518324,
+        -84.3455497382199, -83.40314136125654, -82.46073298429319,
+       -81.51832460732984,
+       ...
+        81.51832460732984,   82.4607329842932,  83.40314136125653,
+        84.34554973821989,  85.28795811518324,   86.2303664921466,
+        87.17277486910996,  88.11518324607329,  89.05759162303664,
+                     90.0],
+      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-028e3a8a-67f5-4e80-abab-f3212be3396f' class='xr-index-data-in' type='checkbox'/><label for='index-028e3a8a-67f5-4e80-abab-f3212be3396f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -180.0, -178.75,  -177.5, -176.25,  -175.0, -173.75,  -172.5, -171.25,
+        -170.0, -168.75,
+       ...
+         167.5,  168.75,   170.0,  171.25,   172.5,  173.75,   175.0,  176.25,
+         177.5,  178.75],
+      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=288))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-08ca749c-6994-41a8-8efc-6a6ff4bf6cc3' class='xr-section-summary-in' type='checkbox'  ><label for='section-08ca749c-6994-41a8-8efc-6a6ff4bf6cc3' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">matplotlib.colors</span> <span class="kn">import</span> <span class="n">LogNorm</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">f</span><span class="p">,</span><span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="n">dpi</span><span class="o">=</span><span class="mi">150</span><span class="p">,</span><span class="n">subplot_kw</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;projection&#39;</span><span class="p">:</span><span class="n">ccrs</span><span class="o">.</span><span class="n">Robinson</span><span class="p">()})</span>
+
+
+<span class="n">da_plt</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">pcolormesh</span><span class="p">(</span>
+    <span class="n">cmap</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="s1">&#39;Reds&#39;</span><span class="p">),</span>
+    <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span>
+    <span class="n">norm</span> <span class="o">=</span> <span class="n">LogNorm</span><span class="p">(),</span>
+    <span class="n">cbar_kwargs</span><span class="o">=</span><span class="p">{</span>
+        <span class="c1">#&#39;label&#39;:&#39;Wind Speed [m/s]&#39;, </span>
+        <span class="s1">&#39;orientation&#39;</span><span class="p">:</span><span class="s1">&#39;horizontal&#39;</span><span class="p">,</span>
+        <span class="s1">&#39;shrink&#39;</span><span class="p">:</span><span class="mf">.8</span>
+    <span class="p">},</span>
+    <span class="n">transform</span><span class="o">=</span><span class="n">ccrs</span><span class="o">.</span><span class="n">PlateCarree</span><span class="p">(),</span> 
+    <span class="c1">#x=&#39;lon&#39;,y=&#39;lat&#39;,</span>
+    <span class="n">levels</span> <span class="o">=</span> <span class="mi">6</span>
+<span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;ilev:-1; Mean over Time&#39;</span><span class="p">)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">coastlines</span><span class="p">()</span>
+
+<span class="n">gl</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">gridlines</span><span class="p">(</span><span class="n">draw_labels</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="c1">#gl.xlabels_top = False</span>
+<span class="c1">#gl.ylabels_right = False</span>
+<span class="c1">#gl.top_labels(False)</span>
+<span class="n">ax</span><span class="o">.</span><span class="n">add_feature</span><span class="p">(</span><span class="n">cy</span><span class="o">.</span><span class="n">feature</span><span class="o">.</span><span class="n">BORDERS</span><span class="p">);</span>
+<span class="n">f</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="../../../_images/5bc8f64ee196f79b76abf31871d20e190bc98c109705eeac81c98ef1991f792b.png" src="../../../_images/5bc8f64ee196f79b76abf31871d20e190bc98c109705eeac81c98ef1991f792b.png" />
+</div>
+</div>
+</section>
+<section id="global-average-weighted-means">
+<h1>6. Global average: weighted means!<a class="headerlink" href="#global-average-weighted-means" title="Link to this heading">#</a></h1>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">compute</span><span class="p">()</span>
+</pre></div>
+</div>
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+}
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;T_C&#x27; ()&gt; Size: 4B
+array(5.447856, dtype=float32)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'T_C'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-835850cc-d6ee-437b-931c-f62f71bce594' class='xr-array-in' type='checkbox' checked><label for='section-835850cc-d6ee-437b-931c-f62f71bce594' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>5.448</span></div><div class='xr-array-data'><pre>array(5.447856, dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-cdb24954-63dd-49e8-a5cd-80d447d9fd3d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cdb24954-63dd-49e8-a5cd-80d447d9fd3d' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-30fe78df-f740-4925-ae61-dc2bb459e1c5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-30fe78df-f740-4925-ae61-dc2bb459e1c5' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-501b8884-65c3-482b-a16e-5a3acc300f35' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-501b8884-65c3-482b-a16e-5a3acc300f35' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+</div>
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+</pre></div>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;T_C&#x27; ()&gt; Size: 4B
+array(14.715081, dtype=float32)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'T_C'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3d93790d-7462-4a42-a457-e0641a890e02' class='xr-array-in' type='checkbox' checked><label for='section-3d93790d-7462-4a42-a457-e0641a890e02' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>14.72</span></div><div class='xr-array-data'><pre>array(14.715081, dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-0d93f88c-a0e7-4767-8b76-d17f29223a07' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0d93f88c-a0e7-4767-8b76-d17f29223a07' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-113699b5-8179-4ae6-81ba-e4773bebff54' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-113699b5-8179-4ae6-81ba-e4773bebff54' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-ea8ce804-d144-40a6-9ba9-c2245f800c0a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ea8ce804-d144-40a6-9ba9-c2245f800c0a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">dss</span><span class="p">[</span><span class="s1">&#39;areacella&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f38041ade50&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/5aa913a04ffe0cc9a9e6c1b387d1250dc698d29cb2e23bf8eefdf7928e891319.png" src="../../../_images/5aa913a04ffe0cc9a9e6c1b387d1250dc698d29cb2e23bf8eefdf7928e891319.png" />
+</div>
+</div>
+</section>
+<section id="convert-to-pandas-do-some-random-fun-stuff">
+<h1>7. Convert to pandas &amp; do some random fun stuff:<a class="headerlink" href="#convert-to-pandas-do-some-random-fun-stuff" title="Link to this heading">#</a></h1>
+<p>Maybe we e.g. want to compare with a station, or just use some of the considerable functionalities available from pandas. It’s easy to convert back and forth between xarray and pandas:</p>
+<span style="color:green;font-weight:700;font-size:20px">
+A lot of these functions also exist in xarray!
+</span>
+<section id="pick-out-station">
+<h2>Pick out station:<a class="headerlink" href="#pick-out-station" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">lat_kristineberg</span> <span class="o">=</span> <span class="mf">58.24</span>
+<span class="n">lon_kristineberg</span> <span class="o">=</span> <span class="mf">11.44</span>
+<span class="c1"># pick out surface</span>
+<span class="n">ds_surf</span> <span class="o">=</span><span class="n">dss</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">lev</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
+<span class="n">ds_kristineberg</span> <span class="o">=</span> <span class="n">ds_surf</span><span class="o">.</span><span class="n">sel</span><span class="p">(</span><span class="n">lat</span><span class="o">=</span><span class="n">lat_kristineberg</span><span class="p">,</span> <span class="n">lon</span> <span class="o">=</span> <span class="n">lon_kristineberg</span><span class="p">,</span> <span class="n">method</span> <span class="o">=</span><span class="s1">&#39;nearest&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 11kB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, nbnd: 2, time: 240)
+Coordinates:
+    lat             float64 8B 57.96
+    lon             float64 8B 11.25
+    lon_bnds        (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+    a_bnds          (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;
+    b_bnds          (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;
+    lev             float64 8B -992.6
+    lev_bnds        (nbnd) float64 16B dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;
+  * time            (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12...
+    time_bnds       (time, nbnd) object 4kB dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;
+Dimensions without coordinates: nbnd
+Data variables:
+    areacella       (member_id, dcpp_init_year) float32 4B dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;
+    a               float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;
+    b               float64 8B dask.array&lt;chunksize=(), meta=np.ndarray&gt;
+    mmrso4          (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 10), meta=np.ndarray&gt;
+    p0              float32 4B ...
+    ps              (time) float32 960B dask.array&lt;chunksize=(10,), meta=np.ndarray&gt;
+    hurs            (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;
+    T_C             (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;
+Attributes: (12/60)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:variable_id:     areacella
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8a40df58-f854-4c4e-b647-2da8142b847d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8a40df58-f854-4c4e-b647-2da8142b847d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-898d1791-ace3-45e4-8ab5-7f9355e41f31' class='xr-section-summary-in' type='checkbox'  checked><label for='section-898d1791-ace3-45e4-8ab5-7f9355e41f31' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>57.96</div><input id='attrs-24f8af7e-84a1-4c04-89bc-51500e66b9e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24f8af7e-84a1-4c04-89bc-51500e66b9e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd5468a8-d299-458a-8a40-4ab4696eb5c6' class='xr-var-data-in' type='checkbox'><label for='data-cd5468a8-d299-458a-8a40-4ab4696eb5c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array(57.95811518)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>11.25</div><input id='attrs-61b747cf-4a4a-482a-9f42-9d20c0fcdb4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61b747cf-4a4a-482a-9f42-9d20c0fcdb4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86630b16-1a7b-47c6-84bc-90e6340af325' class='xr-var-data-in' type='checkbox'><label for='data-86630b16-1a7b-47c6-84bc-90e6340af325' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array(11.25)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-896cc5a6-5c6d-4e49-80d3-46af98a719e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-896cc5a6-5c6d-4e49-80d3-46af98a719e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a86f7966-82f1-4618-bac2-79345533ffa7' class='xr-var-data-in' type='checkbox'><label for='data-a86f7966-82f1-4618-bac2-79345533ffa7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>
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+                        <td> 16 B </td>
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+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-b3cb8ae8-7a03-4c45-82b9-2253b9a52e54' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b3cb8ae8-7a03-4c45-82b9-2253b9a52e54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a88556ee-4bcd-42d8-9337-20cff99f0a7d' class='xr-var-data-in' type='checkbox'><label for='data-a88556ee-4bcd-42d8-9337-20cff99f0a7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-32dbf347-6cde-4bd8-9bdc-82bd8714b951' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-32dbf347-6cde-4bd8-9bdc-82bd8714b951' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b315b82-7b17-4cd9-a859-2997e0d9567b' class='xr-var-data-in' type='checkbox'><label for='data-3b315b82-7b17-4cd9-a859-2997e0d9567b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>a_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-6cf0d2d4-b3aa-46fa-ade4-eb8eab8cbe6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6cf0d2d4-b3aa-46fa-ade4-eb8eab8cbe6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-657915ef-76d1-473f-b8dd-0a43e046c382' class='xr-var-data-in' type='checkbox'><label for='data-657915ef-76d1-473f-b8dd-0a43e046c382' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: a(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 16 B </td>
+                        <td> 16 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (2,) </td>
+                        <td> (2,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="110" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="60" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="60" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="80.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="140.000000" y="30.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,30.000000)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-d212a80a-99ad-48cf-a82a-8676aee0cef8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d212a80a-99ad-48cf-a82a-8676aee0cef8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-422bd8d8-2e18-4395-901d-26eefa1c5e44' class='xr-var-data-in' type='checkbox'><label for='data-422bd8d8-2e18-4395-901d-26eefa1c5e44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k+1/2)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 16 B </td>
+                        <td> 16 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (2,) </td>
+                        <td> (2,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="110" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="60" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="60" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="80.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="140.000000" y="30.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,30.000000)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-992.6</div><input id='attrs-96afb2ae-2d05-4f52-bee8-3726ddd58b87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96afb2ae-2d05-4f52-bee8-3726ddd58b87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adfe0c16-8929-4afa-81c0-74991782201d' class='xr-var-data-in' type='checkbox'><label for='data-adfe0c16-8929-4afa-81c0-74991782201d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array(-992.55609512)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(nbnd)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-5b5653c2-0b57-458c-9f2f-5b3b38c7d84a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b5653c2-0b57-458c-9f2f-5b3b38c7d84a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c6ec933-f55d-40c2-be67-a847ccb5496a' class='xr-var-data-in' type='checkbox'><label for='data-4c6ec933-f55d-40c2-be67-a847ccb5496a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>formula :</span></dt><dd>p = a*p0 + b*ps</dd><dt><span>formula_terms :</span></dt><dd>p0: p0 a: a_bnds b: b_bnds ps: ps</dd><dt><span>standard_name :</span></dt><dd>atmosphere_hybrid_sigma_pressure_coordinate</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 16 B </td>
+                        <td> 16 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (2,) </td>
+                        <td> (2,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="110" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="60" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="60" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="60" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="60.000000" y="80.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="140.000000" y="30.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(0,140.000000,30.000000)">1</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-15T12:00:00 ... 2009-12-...</div><input id='attrs-5db3fee9-eab1-4e9c-8026-72e8a744435e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5db3fee9-eab1-4e9c-8026-72e8a744435e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-254458b7-94bf-4fe4-b3d4-c03e4337374f' class='xr-var-data-in' type='checkbox'><label for='data-254458b7-94bf-4fe4-b3d4-c03e4337374f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,
+       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,
+       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 2), meta=np.ndarray&gt;</div><input id='attrs-19eaeb15-7cfc-4a72-9160-5f1c5839038d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-19eaeb15-7cfc-4a72-9160-5f1c5839038d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2be5e9e-a6bf-413e-8d97-d8428b755e44' class='xr-var-data-in' type='checkbox'><label for='data-c2be5e9e-a6bf-413e-8d97-d8428b755e44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 3.75 kiB </td>
+                        <td> 3.75 kiB </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (240, 2) </td>
+                        <td> (240, 2) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 7 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> object numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="75" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="25" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="25" y1="0" x2="25" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
+  <text x="12.706308" y="140.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" >2</text>
+  <text x="45.412617" y="60.000000" font-size="1.0rem" font-weight="100" text-anchor="middle" transform="rotate(-90,45.412617,60.000000)">240</text>
+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2a7b08af-9e78-451c-bc8c-993d99178271' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2a7b08af-9e78-451c-bc8c-993d99178271' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>areacella</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;</div><input id='attrs-3a9bd0ab-afa5-451b-a237-4969aa2b9465' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a9bd0ab-afa5-451b-a237-4969aa2b9465' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2ce18ef-ab5b-4b7f-9e62-7bcb4009f0a4' class='xr-var-data-in' type='checkbox'><label for='data-b2ce18ef-ab5b-4b7f-9e62-7bcb4009f0a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>comment :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report atmospheric variables and any other variable using that grid (e.g., soil moisture content). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>id :</span></dt><dd>areacella</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>mipTable :</span></dt><dd>fx</dd><dt><span>out_name :</span></dt><dd>areacella</dd><dt><span>prov :</span></dt><dd>fx ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>time_label :</span></dt><dd>None</dd><dt><span>time_title :</span></dt><dd>No temporal dimensions ... fixed field</dd><dt><span>title :</span></dt><dd>Grid-Cell Area for Atmospheric Grid Variables</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>variable_id :</span></dt><dd>areacella</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 4 B </td>
+                        <td> 4 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1) </td>
+                        <td> (1, 1) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 5 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="170" height="170" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="0" y1="0" x2="120" y2="0" style="stroke-width:2" />
+  <line x1="0" y1="120" x2="120" y2="120" style="stroke-width:2" />
+
+  <!-- Vertical lines -->
+  <line x1="0" y1="0" x2="0" y2="120" style="stroke-width:2" />
+  <line x1="120" y1="0" x2="120" y2="120" style="stroke-width:2" />
+
+  <!-- Colored Rectangle -->
+  <polygon points="0.0,0.0 120.0,0.0 120.0,120.0 0.0,120.0" style="fill:#ECB172A0;stroke-width:0"/>
+
+  <!-- Text -->
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+    <tr>
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+            <table style="border-collapse: collapse;">
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+                    <tr>
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+                    <tr>
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+                        <td> 8 B </td>
+                        <td> 8 B </td>
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+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> () </td>
+                        <td> () </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>b</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-a572d68b-d847-47a3-8a5e-e54f6a773064' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a572d68b-d847-47a3-8a5e-e54f6a773064' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79ec675e-ea47-4cf6-bb98-f93394e7f05c' class='xr-var-data-in' type='checkbox'><label for='data-79ec675e-ea47-4cf6-bb98-f93394e7f05c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>b_bnds</dd><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: b(k)</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 8 B </td>
+                        <td> 8 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> () </td>
+                        <td> () </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 1 chunks in 3 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float64 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10), meta=np.ndarray&gt;</div><input id='attrs-18fb0cbd-4181-4e9e-b0fd-eda83b99c5e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18fb0cbd-4181-4e9e-b0fd-eda83b99c5e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcd2584b-fd60-49d3-9e68-a69dd7b778a5' class='xr-var-data-in' type='checkbox'><label for='data-dcd2584b-fd60-49d3-9e68-a69dd7b778a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>
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+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 0.94 kiB </td>
+                        <td> 40 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240) </td>
+                        <td> (1, 1, 10) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 24 chunks in 7 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p0</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c4fa314d-cbf7-4f02-9ea8-4402b8fae7cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4fa314d-cbf7-4f02-9ea8-4402b8fae7cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7478526-9b21-438d-9f4b-ae0b04c460a2' class='xr-var-data-in' type='checkbox'><label for='data-c7478526-9b21-438d-9f4b-ae0b04c460a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate formula term: reference pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10,), meta=np.ndarray&gt;</div><input id='attrs-2c6f63ed-e4a9-4266-90a4-9be28a40ae58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c6f63ed-e4a9-4266-90a4-9be28a40ae58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22e5387e-fd16-43fb-9894-f3a454114b7f' class='xr-var-data-in' type='checkbox'><label for='data-22e5387e-fd16-43fb-9894-f3a454114b7f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 0.94 kiB </td>
+                        <td> 40 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (240,) </td>
+                        <td> (10,) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 24 chunks in 5 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
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+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-c3e70ba2-ce95-4c4c-b869-89b946252ab5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3e70ba2-ce95-4c4c-b869-89b946252ab5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89b56670-f8ac-4792-a7f4-2bbaabc8504d' class='xr-var-data-in' type='checkbox'><label for='data-89b56670-f8ac-4792-a7f4-2bbaabc8504d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 0.94 kiB </td>
+                        <td> 480 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240) </td>
+                        <td> (1, 1, 120) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 6 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
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+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-4f8450ed-612a-4133-8019-d767fbcfa48b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f8450ed-612a-4133-8019-d767fbcfa48b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9677c7b7-90a3-44bc-b999-8960083c0edb' class='xr-var-data-in' type='checkbox'><label for='data-9677c7b7-90a3-44bc-b999-8960083c0edb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 0.94 kiB </td>
+                        <td> 480 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240) </td>
+                        <td> (1, 1, 120) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 6 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T_C</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-def62cb6-9e4f-4d94-974c-816aa464f7d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-def62cb6-9e4f-4d94-974c-816aa464f7d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-377a82fd-8802-4343-9dbd-6d9b3ba3aee9' class='xr-var-data-in' type='checkbox'><label for='data-377a82fd-8802-4343-9dbd-6d9b3ba3aee9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\circ$C</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 0.94 kiB </td>
+                        <td> 480 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240) </td>
+                        <td> (1, 1, 120) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 7 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="194" height="90" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="10" y1="0" x2="24" y2="14" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6de52f87-c974-42bf-ad1c-c6bd3c686407' class='xr-section-summary-in' type='checkbox'  ><label for='section-6de52f87-c974-42bf-ad1c-c6bd3c686407' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2c3e41f6-80d2-4aa6-9f19-6ea1dd0818ca' class='xr-index-data-in' type='checkbox'/><label for='index-2c3e41f6-80d2-4aa6-9f19-6ea1dd0818ca' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-66fe8f5f-1582-4d47-9e04-daeaa7c1c7dd' class='xr-index-data-in' type='checkbox'/><label for='index-66fe8f5f-1582-4d47-9e04-daeaa7c1c7dd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-57278806-d180-400c-bb42-e8629745a701' class='xr-index-data-in' type='checkbox'/><label for='index-57278806-d180-400c-bb42-e8629745a701' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-15 12:00:00&#x27;, &#x27;1990-02-14 00:00:00&#x27;,
+               &#x27;1990-03-15 12:00:00&#x27;, &#x27;1990-04-15 00:00:00&#x27;,
+               &#x27;1990-05-15 12:00:00&#x27;, &#x27;1990-06-15 00:00:00&#x27;,
+               &#x27;1990-07-15 12:00:00&#x27;, &#x27;1990-08-15 12:00:00&#x27;,
+               &#x27;1990-09-15 00:00:00&#x27;, &#x27;1990-10-15 12:00:00&#x27;,
+               ...
+               &#x27;2009-03-15 12:00:00&#x27;, &#x27;2009-04-15 00:00:00&#x27;,
+               &#x27;2009-05-15 12:00:00&#x27;, &#x27;2009-06-15 00:00:00&#x27;,
+               &#x27;2009-07-15 12:00:00&#x27;, &#x27;2009-08-15 12:00:00&#x27;,
+               &#x27;2009-09-15 00:00:00&#x27;, &#x27;2009-10-15 12:00:00&#x27;,
+               &#x27;2009-11-15 00:00:00&#x27;, &#x27;2009-12-15 12:00:00&#x27;],
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-82c14247-cd87-4d1e-9e61-b2247c62979e' class='xr-section-summary-in' type='checkbox'  ><label for='section-82c14247-cd87-4d1e-9e61-b2247c62979e' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
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+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">vl</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;mmrso4&#39;</span><span class="p">,</span><span class="s1">&#39;hurs&#39;</span><span class="p">,</span><span class="s1">&#39;tas&#39;</span><span class="p">,</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span>
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+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds_kristineberg</span><span class="p">[</span><span class="n">vl</span><span class="p">]</span>
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+</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 6kB
+Dimensions:         (member_id: 1, dcpp_init_year: 1, time: 240)
+Coordinates:
+    lat             float64 8B 57.96
+    lon             float64 8B 11.25
+  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;
+  * dcpp_init_year  (dcpp_init_year) float64 8B nan
+    lev             float64 8B -992.6
+  * time            (time) datetime64[ns] 2kB 1990-01-15T12:00:00 ... 2009-12...
+Data variables:
+    mmrso4          (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 10), meta=np.ndarray&gt;
+    hurs            (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;
+    tas             (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;
+    T_C             (member_id, dcpp_init_year, time) float32 960B dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;
+Attributes: (12/60)
+    Conventions:                      CF-1.7 CMIP-6.2
+    activity_id:                      CMIP
+    branch_method:                    standard
+    branch_time_in_child:             674885.0
+    branch_time_in_parent:            219000.0
+    case_id:                          15
+    ...                               ...
+    intake_esm_attrs:variable_id:     areacella
+    intake_esm_attrs:grid_label:      gn
+    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCAR/CESM2/histor...
+    intake_esm_attrs:version:         20190308
+    intake_esm_attrs:_data_format_:   zarr
+    intake_esm_dataset_key:           CMIP.NCAR.CESM2.historical.fx.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4391e9e8-70a4-4160-879d-af13d6564b81' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4391e9e8-70a4-4160-879d-af13d6564b81' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 240</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7940780e-531f-4e9f-8898-e82ee01c54be' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7940780e-531f-4e9f-8898-e82ee01c54be' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>57.96</div><input id='attrs-bcc14ebb-82e4-4dbd-a2a0-8d46abb9fc45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bcc14ebb-82e4-4dbd-a2a0-8d46abb9fc45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da82df85-6d45-47b4-9ec4-efdc3bb9848b' class='xr-var-data-in' type='checkbox'><label for='data-da82df85-6d45-47b4-9ec4-efdc3bb9848b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>array(57.95811518)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>11.25</div><input id='attrs-9f87290c-e2d2-41a9-b7fe-58d451ccc4c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f87290c-e2d2-41a9-b7fe-58d451ccc4c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36ce72b3-70ed-44d5-90aa-abd0c9a5c094' class='xr-var-data-in' type='checkbox'><label for='data-36ce72b3-70ed-44d5-90aa-abd0c9a5c094' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\circ$ East</dd></dl></div><div class='xr-var-data'><pre>array(11.25)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-330e0ec3-e5d6-4b04-a403-23be9ef2b866' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-330e0ec3-e5d6-4b04-a403-23be9ef2b866' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cc0c25a-9be5-49f8-bd76-b88fb9d02ae3' class='xr-var-data-in' type='checkbox'><label for='data-9cc0c25a-9be5-49f8-bd76-b88fb9d02ae3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-d69bc926-2ba5-4d2d-ab45-2743a5dee307' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d69bc926-2ba5-4d2d-ab45-2743a5dee307' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-079f58d4-55e7-4907-a0a5-96fefd0a8c38' class='xr-var-data-in' type='checkbox'><label for='data-079f58d4-55e7-4907-a0a5-96fefd0a8c38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-992.6</div><input id='attrs-5669a45f-028f-4efb-836e-c09aa47926ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5669a45f-028f-4efb-836e-c09aa47926ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-289739db-014d-4ca0-b1eb-aedef19ac01d' class='xr-var-data-in' type='checkbox'><label for='data-289739db-014d-4ca0-b1eb-aedef19ac01d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>alevel</dd><dt><span>title :</span></dt><dd>atmospheric model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array(-992.55609512)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-15T12:00:00 ... 2009-12-...</div><input id='attrs-eaf7b075-577c-4316-b8a3-12df225c4180' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-eaf7b075-577c-4316-b8a3-12df225c4180' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e5a0022-a8cd-4096-a17b-f7b40c8ba2fb' class='xr-var-data-in' type='checkbox'><label for='data-4e5a0022-a8cd-4096-a17b-f7b40c8ba2fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-15T12:00:00.000000000&#x27;, &#x27;1990-02-14T00:00:00.000000000&#x27;,
+       &#x27;1990-03-15T12:00:00.000000000&#x27;, ..., &#x27;2009-10-15T12:00:00.000000000&#x27;,
+       &#x27;2009-11-15T00:00:00.000000000&#x27;, &#x27;2009-12-15T12:00:00.000000000&#x27;],
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-618ebcd8-56a9-4104-bae4-e0b06debf413' class='xr-section-summary-in' type='checkbox'  checked><label for='section-618ebcd8-56a9-4104-bae4-e0b06debf413' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>mmrso4</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 10), meta=np.ndarray&gt;</div><input id='attrs-f889b26a-26c5-493b-aea7-a4656bf99ed1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f889b26a-26c5-493b-aea7-a4656bf99ed1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e592787b-78f0-4fc3-b1fa-65fa8415b3d2' class='xr-var-data-in' type='checkbox'><label for='data-e592787b-78f0-4fc3-b1fa-65fa8415b3d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>description :</span></dt><dd>Dry mass of sulfate (SO4) in aerosol particles as a fraction of air mass.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>mmrso4</dd><dt><span>long_name :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>mmrso4</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>mass_fraction_of_sulfate_dry_aerosol_particles_in_air</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Aerosol Sulfate Mass Mixing Ratio</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>variable_id :</span></dt><dd>mmrso4</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 0.94 kiB </td>
+                        <td> 40 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240) </td>
+                        <td> (1, 1, 10) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 24 chunks in 7 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-58b8f75f-b5e6-41ae-ada6-03ab64fe6cdc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58b8f75f-b5e6-41ae-ada6-03ab64fe6cdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a375f94-a2b3-4e65-b753-a4f280ac9c29' class='xr-var-data-in' type='checkbox'><label for='data-1a375f94-a2b3-4e65-b753-a4f280ac9c29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>description :</span></dt><dd>This is the relative humidity with respect to liquid water for T&gt; 0 C, and with respect to ice for T&lt;0 C.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>hurs</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>hurs</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>variable_id :</span></dt><dd>hurs</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 0.94 kiB </td>
+                        <td> 480 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240) </td>
+                        <td> (1, 1, 120) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 6 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-4bbc3ab0-78bc-438f-b621-f4739c03cf4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bbc3ab0-78bc-438f-b621-f4739c03cf4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf1e51e6-b736-41e0-8af0-f0431359bdae' class='xr-var-data-in' type='checkbox'><label for='data-bf1e51e6-b736-41e0-8af0-f0431359bdae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>description :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>tas</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>mipTable :</span></dt><dd>Amon</dd><dt><span>out_name :</span></dt><dd>tas</dd><dt><span>prov :</span></dt><dd>Amon ((isd.003))</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>variable_id :</span></dt><dd>tas</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 0.94 kiB </td>
+                        <td> 480 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240) </td>
+                        <td> (1, 1, 120) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 6 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
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+</svg>
+        </td>
+    </tr>
+</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T_C</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 120), meta=np.ndarray&gt;</div><input id='attrs-6b0a2fbe-9b48-4d95-b8bc-5daaee32112a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b0a2fbe-9b48-4d95-b8bc-5daaee32112a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60555e4d-b034-474d-a48f-419ab29214d7' class='xr-var-data-in' type='checkbox'><label for='data-60555e4d-b034-474d-a48f-419ab29214d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>$^\circ$C</dd></dl></div><div class='xr-var-data'><table>
+    <tr>
+        <td>
+            <table style="border-collapse: collapse;">
+                <thead>
+                    <tr>
+                        <td> </td>
+                        <th> Array </th>
+                        <th> Chunk </th>
+                    </tr>
+                </thead>
+                <tbody>
+                    
+                    <tr>
+                        <th> Bytes </th>
+                        <td> 0.94 kiB </td>
+                        <td> 480 B </td>
+                    </tr>
+                    
+                    <tr>
+                        <th> Shape </th>
+                        <td> (1, 1, 240) </td>
+                        <td> (1, 1, 120) </td>
+                    </tr>
+                    <tr>
+                        <th> Dask graph </th>
+                        <td colspan="2"> 2 chunks in 7 graph layers </td>
+                    </tr>
+                    <tr>
+                        <th> Data type </th>
+                        <td colspan="2"> float32 numpy.ndarray </td>
+                    </tr>
+                </tbody>
+            </table>
+        </td>
+        <td>
+        <svg width="194" height="90" style="stroke:rgb(0,0,0);stroke-width:1" >
+
+  <!-- Horizontal lines -->
+  <line x1="10" y1="0" x2="24" y2="14" style="stroke-width:2" />
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+</svg>
+        </td>
+    </tr>
+</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c682c4e6-58bc-4eee-8a2c-865fe7fb7076' class='xr-section-summary-in' type='checkbox'  ><label for='section-c682c4e6-58bc-4eee-8a2c-865fe7fb7076' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dc39be7a-d750-4eb9-a280-02f5551f6353' class='xr-index-data-in' type='checkbox'/><label for='index-dc39be7a-d750-4eb9-a280-02f5551f6353' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-95e6e4f4-091f-4067-8e85-550413165a51' class='xr-index-data-in' type='checkbox'/><label for='index-95e6e4f4-091f-4067-8e85-550413165a51' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-18af2285-7351-4322-874d-e0819ae152f6' class='xr-index-data-in' type='checkbox'/><label for='index-18af2285-7351-4322-874d-e0819ae152f6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-15 12:00:00&#x27;, &#x27;1990-02-14 00:00:00&#x27;,
+               &#x27;1990-03-15 12:00:00&#x27;, &#x27;1990-04-15 00:00:00&#x27;,
+               &#x27;1990-05-15 12:00:00&#x27;, &#x27;1990-06-15 00:00:00&#x27;,
+               &#x27;1990-07-15 12:00:00&#x27;, &#x27;1990-08-15 12:00:00&#x27;,
+               &#x27;1990-09-15 00:00:00&#x27;, &#x27;1990-10-15 12:00:00&#x27;,
+               ...
+               &#x27;2009-03-15 12:00:00&#x27;, &#x27;2009-04-15 00:00:00&#x27;,
+               &#x27;2009-05-15 12:00:00&#x27;, &#x27;2009-06-15 00:00:00&#x27;,
+               &#x27;2009-07-15 12:00:00&#x27;, &#x27;2009-08-15 12:00:00&#x27;,
+               &#x27;2009-09-15 00:00:00&#x27;, &#x27;2009-10-15 12:00:00&#x27;,
+               &#x27;2009-11-15 00:00:00&#x27;, &#x27;2009-12-15 12:00:00&#x27;],
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b3b9c45-eafa-4274-a759-367fedd71f9f' class='xr-section-summary-in' type='checkbox'  ><label for='section-6b3b9c45-eafa-4274-a759-367fedd71f9f' class='xr-section-summary' >Attributes: <span>(60)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T21:43:39Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 0.9x1.25 finite volume grid (192x288 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos land</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>fx</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>variable_id :</span></dt><dd>areacella</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)
+</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/75033260-7bd2-46b9-9d98-3456f176d588</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;areacella&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCAR</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>CESM2</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>fx</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>areacella</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1i1p1f1/fx/areacella/gn/v20190308/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190308</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.fx.gn</dd></dl></div></li></ul></div></div></div></div>
+</div>
+<section id="resample">
+<h3>Resample:<a class="headerlink" href="#resample" title="Link to this heading">#</a></h3>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df_kristineberg</span> <span class="o">=</span> <span class="n">ds_kristineberg</span><span class="p">[</span><span class="n">vl</span><span class="p">]</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df_kristineberg</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>mmrso4</th>
+      <th>hurs</th>
+      <th>tas</th>
+      <th>T_C</th>
+      <th>lat</th>
+      <th>lon</th>
+      <th>member_id</th>
+      <th>dcpp_init_year</th>
+      <th>lev</th>
+    </tr>
+    <tr>
+      <th>time</th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+      <th></th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>1990-01-15 12:00:00</th>
+      <td>9.319389e-10</td>
+      <td>85.651199</td>
+      <td>277.036011</td>
+      <td>3.886017</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>1990-02-14 00:00:00</th>
+      <td>9.139207e-10</td>
+      <td>79.779701</td>
+      <td>273.601807</td>
+      <td>0.451813</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>1990-03-15 12:00:00</th>
+      <td>1.282672e-09</td>
+      <td>82.473785</td>
+      <td>277.405701</td>
+      <td>4.255707</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>1990-04-15 00:00:00</th>
+      <td>7.225737e-10</td>
+      <td>79.588730</td>
+      <td>280.137329</td>
+      <td>6.987335</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>1990-05-15 12:00:00</th>
+      <td>2.263646e-09</td>
+      <td>80.421875</td>
+      <td>283.043152</td>
+      <td>9.893158</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>...</th>
+      <td>...</td>
+      <td>...</td>
+      <td>...</td>
+      <td>...</td>
+      <td>...</td>
+      <td>...</td>
+      <td>...</td>
+      <td>...</td>
+      <td>...</td>
+    </tr>
+    <tr>
+      <th>2009-08-15 12:00:00</th>
+      <td>6.469142e-10</td>
+      <td>82.338539</td>
+      <td>290.292358</td>
+      <td>17.142365</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>2009-09-15 00:00:00</th>
+      <td>6.174767e-10</td>
+      <td>75.105225</td>
+      <td>288.502136</td>
+      <td>15.352142</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>2009-10-15 12:00:00</th>
+      <td>5.226203e-10</td>
+      <td>81.029533</td>
+      <td>284.518219</td>
+      <td>11.368225</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>2009-11-15 00:00:00</th>
+      <td>2.411485e-10</td>
+      <td>83.641380</td>
+      <td>278.707977</td>
+      <td>5.557983</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>2009-12-15 12:00:00</th>
+      <td>4.485378e-10</td>
+      <td>89.487213</td>
+      <td>277.537415</td>
+      <td>4.387421</td>
+      <td>57.958115</td>
+      <td>11.25</td>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>-992.556095</td>
+    </tr>
+  </tbody>
+</table>
+<p>240 rows × 9 columns</p>
+</div></div></div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df_yearly</span> <span class="o">=</span> <span class="n">df_kristineberg</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s1">&#39;YE&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">numeric_only</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="c1">#.plot()</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df_yearly</span><span class="p">[</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;Axes: xlabel=&#39;time&#39;&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/7e01c667bb94bef97ae5e059e9a3aeeb898abd7d9131e83d332fdea7d5f0f868.png" src="../../../_images/7e01c667bb94bef97ae5e059e9a3aeeb898abd7d9131e83d332fdea7d5f0f868.png" />
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df_kristineberg</span><span class="p">[</span><span class="s1">&#39;season&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df_kristineberg</span><span class="o">.</span><span class="n">to_xarray</span><span class="p">()[</span><span class="s1">&#39;time.season&#39;</span><span class="p">]</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;MAM&#39;</span><span class="p">,</span><span class="s1">&#39;JJA&#39;</span><span class="p">,</span><span class="s1">&#39;SON&#39;</span><span class="p">,</span><span class="s1">&#39;DJF&#39;</span><span class="p">]:</span>
+    <span class="n">df_kristineberg</span><span class="p">[</span><span class="n">df_kristineberg</span><span class="p">[</span><span class="s1">&#39;season&#39;</span><span class="p">]</span><span class="o">==</span><span class="n">s</span><span class="p">][</span><span class="s1">&#39;T_C&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">s</span><span class="p">)</span>
+    
+<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7f3565fe1890&gt;
+</pre></div>
+</div>
+<img alt="../../../_images/b5c7149f7b2750a83cd1f6f1d061ca06994d7be56de198f18b4446f32732e97c.png" src="../../../_images/b5c7149f7b2750a83cd1f6f1d061ca06994d7be56de198f18b4446f32732e97c.png" />
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">dss</span><span class="o">.</span><span class="n">isel</span><span class="p">(</span><span class="n">lev</span><span class="o">=-</span><span class="mi">1</span><span class="p">)[</span><span class="n">vl</span><span class="p">]</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df_ri</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>
+<span class="n">df_ri</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_html"><div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+
+    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+
+    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>member_id</th>
+      <th>dcpp_init_year</th>
+      <th>time</th>
+      <th>lat</th>
+      <th>lon</th>
+      <th>mmrso4</th>
+      <th>hurs</th>
+      <th>tas</th>
+      <th>T_C</th>
+      <th>lev</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>0</th>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>1990-01-15 12:00:00</td>
+      <td>-90.0</td>
+      <td>-180.00</td>
+      <td>2.049096e-11</td>
+      <td>98.689842</td>
+      <td>242.897797</td>
+      <td>-30.252197</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>1</th>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>1990-01-15 12:00:00</td>
+      <td>-90.0</td>
+      <td>-178.75</td>
+      <td>2.049095e-11</td>
+      <td>98.675537</td>
+      <td>242.903198</td>
+      <td>-30.246796</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>2</th>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>1990-01-15 12:00:00</td>
+      <td>-90.0</td>
+      <td>-177.50</td>
+      <td>2.049095e-11</td>
+      <td>98.675537</td>
+      <td>242.903198</td>
+      <td>-30.246796</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>3</th>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>1990-01-15 12:00:00</td>
+      <td>-90.0</td>
+      <td>-176.25</td>
+      <td>2.049095e-11</td>
+      <td>98.675537</td>
+      <td>242.903198</td>
+      <td>-30.246796</td>
+      <td>-992.556095</td>
+    </tr>
+    <tr>
+      <th>4</th>
+      <td>r1i1p1f1</td>
+      <td>NaN</td>
+      <td>1990-01-15 12:00:00</td>
+      <td>-90.0</td>
+      <td>-175.00</td>
+      <td>2.049095e-11</td>
+      <td>98.675537</td>
+      <td>242.903198</td>
+      <td>-30.246796</td>
+      <td>-992.556095</td>
+    </tr>
+  </tbody>
+</table>
+</div></div></div>
+</div>
+</section>
+<section id="lets-do-something-unnecesarily-complicated-d">
+<h3>lets do something unnecesarily complicated :D<a class="headerlink" href="#lets-do-something-unnecesarily-complicated-d" title="Link to this heading">#</a></h3>
+</section>
+</section>
+<section id="qcut-cut">
+<h2>qcut, cut<a class="headerlink" href="#qcut-cut" title="Link to this heading">#</a></h2>
+<p>qcut splits the data into quantile ranges</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df_ri</span><span class="p">[</span><span class="s1">&#39;hurs_cat&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">qcut</span><span class="p">(</span><span class="n">df_ri</span><span class="p">[</span><span class="s1">&#39;hurs&#39;</span><span class="p">],</span>
+                            <span class="n">q</span><span class="o">=</span><span class="p">[</span><span class="mf">0.05</span><span class="p">,</span><span class="mf">0.17</span><span class="p">,</span> <span class="mf">0.34</span><span class="p">,</span><span class="mf">0.66</span><span class="p">,</span> <span class="mf">0.83</span><span class="p">,</span><span class="mf">0.95</span><span class="p">],</span>
+                            <span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;very low&#39;</span><span class="p">,</span><span class="s1">&#39;low&#39;</span><span class="p">,</span><span class="s1">&#39;med&#39;</span><span class="p">,</span><span class="s1">&#39;high&#39;</span><span class="p">,</span><span class="s1">&#39;very high&#39;</span><span class="p">])</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Cut cuts into categories</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df_ri</span><span class="p">[</span><span class="s1">&#39;lat_cat&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">cut</span><span class="p">(</span><span class="n">df_ri</span><span class="p">[</span><span class="s1">&#39;lat&#39;</span><span class="p">],</span> <span class="p">[</span><span class="o">-</span><span class="mi">90</span><span class="p">,</span><span class="o">-</span><span class="mi">60</span><span class="p">,</span><span class="o">-</span><span class="mi">30</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">30</span><span class="p">,</span><span class="mi">60</span><span class="p">,</span><span class="mi">90</span><span class="p">],</span> 
+                          <span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;S polar&#39;</span><span class="p">,</span><span class="s1">&#39;S mid&#39;</span><span class="p">,</span><span class="s1">&#39;S tropics&#39;</span><span class="p">,</span> <span class="s1">&#39;N tropic&#39;</span><span class="p">,</span> <span class="s1">&#39;N mid&#39;</span><span class="p">,</span><span class="s1">&#39;N polar&#39;</span><span class="p">])</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df_ri</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;lat_cat&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_11040/3604578940.py:1: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.
+  df_ri.groupby(&#39;lat_cat&#39;).mean()
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">boxenplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s2">&quot;lat_cat&quot;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">&quot;hurs&quot;</span><span class="p">,</span>
+              <span class="n">color</span><span class="o">=</span><span class="s2">&quot;b&quot;</span><span class="p">,</span>
+              <span class="n">scale</span><span class="o">=</span><span class="s2">&quot;linear&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">df_ri</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">boxenplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s2">&quot;hurs_cat&quot;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">&quot;mmrso4&quot;</span><span class="p">,</span>
+              <span class="n">color</span><span class="o">=</span><span class="s2">&quot;b&quot;</span><span class="p">,</span>
+              <span class="n">scale</span><span class="o">=</span><span class="s2">&quot;linear&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">df_ri</span><span class="p">,</span>
+             <span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">displot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s2">&quot;mmrso4&quot;</span><span class="p">,</span>
+            <span class="n">hue</span><span class="o">=</span><span class="s1">&#39;lat_cat&#39;</span><span class="p">,</span>
+            <span class="n">log_scale</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
+            <span class="n">kind</span><span class="o">=</span><span class="s1">&#39;kde&#39;</span><span class="p">,</span>
+            <span class="n">data</span><span class="o">=</span><span class="n">df_ri</span><span class="p">,</span> 
+            <span class="n">multiple</span><span class="o">=</span><span class="s2">&quot;stack&quot;</span>
+           <span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="convert-back-to-xarray-if-we-need">
+<h2>Convert back to xarray if we need:<a class="headerlink" href="#convert-back-to-xarray-if-we-need" title="Link to this heading">#</a></h2>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds_new</span> <span class="o">=</span> <span class="n">df_ri</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s1">&#39;time&#39;</span><span class="p">,</span><span class="s1">&#39;lat&#39;</span><span class="p">,</span><span class="s1">&#39;lon&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">to_xarray</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds_new</span>
+</pre></div>
+</div>
+</div>
+</div>
+<section id="mask-by-category">
+<h3>mask by category<a class="headerlink" href="#mask-by-category" title="Link to this heading">#</a></h3>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ds_new</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">ds_new</span><span class="p">[</span><span class="s1">&#39;hurs_cat&#39;</span><span class="p">]</span><span class="o">==</span><span class="s1">&#39;very low&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">([</span><span class="s1">&#39;time&#39;</span><span class="p">,</span><span class="s1">&#39;lon&#39;</span><span class="p">])[</span><span class="s1">&#39;mmrso4&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="s1">&#39;very low&#39;</span><span class="p">)</span><span class="c1">#vmin = 0, vmax = 1.5e-8)</span>
+<span class="n">ds_new</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">ds_new</span><span class="p">[</span><span class="s1">&#39;hurs_cat&#39;</span><span class="p">]</span><span class="o">==</span><span class="s1">&#39;low&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">([</span><span class="s1">&#39;time&#39;</span><span class="p">,</span><span class="s1">&#39;lon&#39;</span><span class="p">])[</span><span class="s1">&#39;mmrso4&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="s1">&#39;low&#39;</span><span class="p">)</span><span class="c1">#vmin = 0, vmax = 1.5e-8)</span>
+
+<span class="n">ds_new</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">ds_new</span><span class="p">[</span><span class="s1">&#39;hurs_cat&#39;</span><span class="p">]</span><span class="o">==</span><span class="s1">&#39;high&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">([</span><span class="s1">&#39;time&#39;</span><span class="p">,</span><span class="s1">&#39;lon&#39;</span><span class="p">])[</span><span class="s1">&#39;mmrso4&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="s1">&#39;high&#39;</span><span class="p">)</span><span class="c1">#vmin = 0, vmax = 1.5e-8)</span>
+<span class="n">ds_new</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">ds_new</span><span class="p">[</span><span class="s1">&#39;hurs_cat&#39;</span><span class="p">]</span><span class="o">==</span><span class="s1">&#39;very high&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">([</span><span class="s1">&#39;time&#39;</span><span class="p">,</span><span class="s1">&#39;lon&#39;</span><span class="p">],</span> <span class="n">keep_attrs</span><span class="o">=</span><span class="kc">True</span><span class="p">)[</span><span class="s1">&#39;mmrso4&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="s1">&#39;very high&#39;</span><span class="p">)</span><span class="c1">#vmin = 0, vmax = 1.5e-8)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+</section>
+</section>
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+    <i class="fa-solid fa-list"></i> Contents
+  </div>
+  <nav class="bd-toc-nav page-toc">
+    <ul class="visible nav section-nav flex-column">
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#">Some tips with xarray and pandas</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#print-hey-world">print(‘Hey world’)</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#what-are-pandas-and-xarray">What are pandas and xarray?</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#pandas">Pandas</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#xarray">Xarray</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#read-in-cmip6-data-we-will-skip-this-next-part-but-you-can-check-it-later-to-read-data">1. Read in CMIP6 data: We will skip this next part, but you can check it later to read data:</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#import-python-packages">Import python packages</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#open-cmip6-online-catalog">Open CMIP6 online catalog</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#search-corresponding-data">Search corresponding data</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#create-dictionary-from-the-list-of-datasets-we-found">Create dictionary from the list of datasets we found</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#open-dataset">Open dataset</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#reading-in-the-data-from-file">1.1 Reading in the data from file:</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#opening-multiple-files">Opening multiple files:</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#check-how-your-dataset-looks">2. Check how your dataset looks</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#different-types-of-information-data">Different types of information/data:</a></li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#sometimes-we-want-to-do-some-nice-tweaks-before-we-start">3. Sometimes we want to do some nice tweaks before we start:</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#selecting-data-and-super-quick-plotting">Selecting data and super quick plotting:</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#see-here-for-nice-overview">See here for nice overview</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#slice-in-time-the-sel-method">Slice in time: the sel method</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#isel-sel-index-selecting">isel, sel: index selecting</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#calculates-variables-and-assign-attributes">3.2 Calculates variables and assign attributes!</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#convert-longitude">3.3 Convert longitude:</a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#the-easiest-interpolation-select-with-nearest-neighboor">4. The easiest interpolation: select with ‘nearest’ neighboor</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#super-quick-averaging-etc">Super quick averaging etc</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#mask-data-and-groupby-pick-out-seasons">Mask data and groupby: pick out seasons</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#controle-the-plot-visuals">Controle the plot visuals:</a></li>
+</ul>
+</li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#plotting-with-cartopy">5. Plotting with cartopy</a></li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#global-average-weighted-means">6. Global average: weighted means!</a></li>
+<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#convert-to-pandas-do-some-random-fun-stuff">7. Convert to pandas &amp; do some random fun stuff:</a><ul class="visible nav section-nav flex-column">
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#pick-out-station">Pick out station:</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#resample">Resample:</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#lets-do-something-unnecesarily-complicated-d">lets do something unnecesarily complicated :D</a></li>
+</ul>
+</li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#qcut-cut">qcut, cut</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#convert-back-to-xarray-if-we-need">Convert back to xarray if we need:</a><ul class="nav section-nav flex-column">
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#mask-by-category">mask by category</a></li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
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+<p class="component-author">
+By MetOs-UiO
+</p>
+
+  </div>
+  
+  <div class="footer-item">
+    
+
+  <p class="copyright">
+    
+      © Copyright 2024, MetOs, UiO.
+      <br/>
+    
+  </p>
+
+  </div>
+  
+  <div class="footer-item">
+    
+  </div>
+  
+  <div class="footer-item">
+    
+  </div>
+  
+</div>
+          </footer>
+        
+
+      </main>
+    </div>
+  </div>
+  
+  <!-- Scripts loaded after <body> so the DOM is not blocked -->
+  <script src="../_static/scripts/bootstrap.js?digest=8d27b9dea8ad943066ae"></script>
+<script src="../_static/scripts/pydata-sphinx-theme.js?digest=8d27b9dea8ad943066ae"></script>
+
+  <footer class="bd-footer">
+  </footer>
+  </body>
+</html>
\ No newline at end of file
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diff --git a/search/index.html b/search/index.html
new file mode 100644
index 0000000..6cf4617
--- /dev/null
+++ b/search/index.html
@@ -0,0 +1,464 @@
+
+<!DOCTYPE html>
+
+
+<html lang="en" data-content_root="../" >
+
+  <head>
+    <meta charset="utf-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><title>Search - eScience-2024  documentation</title>
+  
+  
+  
+  <script data-cfasync="false">
+    document.documentElement.dataset.mode = localStorage.getItem("mode") || "";
+    document.documentElement.dataset.theme = localStorage.getItem("theme") || "light";
+  </script>
+  
+  <!-- Loaded before other Sphinx assets -->
+  <link href="../_static/styles/theme.css?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+<link href="../_static/styles/bootstrap.css?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+<link href="../_static/styles/pydata-sphinx-theme.css?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+
+  
+  <link href="../_static/vendor/fontawesome/6.5.1/css/all.min.css?digest=8d27b9dea8ad943066ae" rel="stylesheet" />
+  <link rel="preload" as="font" type="font/woff2" crossorigin href="../_static/vendor/fontawesome/6.5.1/webfonts/fa-solid-900.woff2" />
+<link rel="preload" as="font" type="font/woff2" crossorigin href="../_static/vendor/fontawesome/6.5.1/webfonts/fa-brands-400.woff2" />
+<link rel="preload" as="font" type="font/woff2" crossorigin href="../_static/vendor/fontawesome/6.5.1/webfonts/fa-regular-400.woff2" />
+
+    <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=a746c00c" />
+    <link rel="stylesheet" type="text/css" href="../_static/styles/sphinx-book-theme.css?v=384b581d" />
+    <link rel="stylesheet" type="text/css" href="../_static/graphviz.css?v=fd3f3429" />
+    <link rel="stylesheet" type="text/css" href="../_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css" />
+    <link rel="stylesheet" type="text/css" href="../_static/copybutton.css?v=76b2166b" />
+    <link rel="stylesheet" type="text/css" href="../_static/togglebutton.css?v=13237357" />
+    <link rel="stylesheet" type="text/css" href="../_static/css/sphinx-toolbox.css" />
+    <link rel="stylesheet" type="text/css" href="../_static/tabs.css?v=a5c4661c" />
+    <link rel="stylesheet" type="text/css" href="../_static/sphinx_toolbox_installation.css" />
+    <link rel="stylesheet" type="text/css" href="../_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css?v=0a3b3ea7" />
+  
+  <!-- Pre-loaded scripts that we'll load fully later -->
+  <link rel="preload" as="script" href="../_static/scripts/bootstrap.js?digest=8d27b9dea8ad943066ae" />
+<link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=8d27b9dea8ad943066ae" />
+  <script src="../_static/vendor/fontawesome/6.5.1/js/all.min.js?digest=8d27b9dea8ad943066ae"></script>
+
+    <script src="../_static/documentation_options.js?v=55b5f74b"></script>
+    <script src="../_static/doctools.js?v=9a2dae69"></script>
+    <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
+    <script src="../_static/clipboard.min.js?v=a7894cd8"></script>
+    <script src="../_static/copybutton.js?v=f281be69"></script>
+    <script src="../_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
+    <script src="../_static/tabs.js?v=3030b3cb"></script>
+    <script>let toggleHintShow = 'Click to show';</script>
+    <script>let toggleHintHide = 'Click to hide';</script>
+    <script>let toggleOpenOnPrint = 'true';</script>
+    <script src="../_static/togglebutton.js?v=4a39c7ea"></script>
+    <script src="../_static/sphinx_toolbox_installation.js"></script>
+    <script src="../_static/design-tabs.js?v=36754332"></script>
+    <script>var togglebuttonSelector = '.toggle, .admonition.dropdown';</script>
+    <script>var togglebuttonSelector = '.toggle, .admonition.dropdown';</script>
+    <script>DOCUMENTATION_OPTIONS.pagename = 'search';</script>
+  <script src="../_static/searchtools.js"></script>
+  <script src="../_static/language_data.js"></script>
+  <script src="../searchindex.js"></script>
+    <link rel="icon" href="../_static/es-logo.ico"/>
+    <link rel="index" title="Index" href="../genindex/" />
+    <link rel="search" title="Search" href="#" />
+  <meta name="viewport" content="width=device-width, initial-scale=1"/>
+  <meta name="docsearch:language" content="en"/>
+  </head>
+  
+  
+  <body data-bs-spy="scroll" data-bs-target=".bd-toc-nav" data-offset="180" data-bs-root-margin="0px 0px -60%" data-default-mode="">
+
+  
+  
+  <a id="pst-skip-link" class="skip-link" href="#main-content">Skip to main content</a>
+  
+  <div id="pst-scroll-pixel-helper"></div>
+  
+  <button type="button" class="btn rounded-pill" id="pst-back-to-top">
+    <i class="fa-solid fa-arrow-up"></i>
+    Back to top
+  </button>
+
+  
+  <input type="checkbox"
+          class="sidebar-toggle"
+          name="__primary"
+          id="__primary"/>
+  <label class="overlay overlay-primary" for="__primary"></label>
+  
+  <input type="checkbox"
+          class="sidebar-toggle"
+          name="__secondary"
+          id="__secondary"/>
+  <label class="overlay overlay-secondary" for="__secondary"></label>
+  
+  <div class="search-button__wrapper">
+    <div class="search-button__overlay"></div>
+    <div class="search-button__search-container">
+<form class="bd-search d-flex align-items-center"
+      action="#"
+      method="get">
+  <i class="fa-solid fa-magnifying-glass"></i>
+  <input type="search"
+         class="form-control"
+         name="q"
+         id="search-input"
+         placeholder="Search..."
+         aria-label="Search..."
+         autocomplete="off"
+         autocorrect="off"
+         autocapitalize="off"
+         spellcheck="false"/>
+  <span class="search-button__kbd-shortcut"><kbd class="kbd-shortcut__modifier">Ctrl</kbd>+<kbd>K</kbd></span>
+</form></div>
+  </div>
+  
+    <header class="bd-header navbar navbar-expand-lg bd-navbar">
+    </header>
+  
+
+  <div class="bd-container">
+    <div class="bd-container__inner bd-page-width">
+      
+      
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+        
+      
+      <div class="bd-sidebar-primary bd-sidebar">
+        
+
+  
+  <div class="sidebar-header-items sidebar-primary__section">
+    
+    
+    
+    
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+    <div class="sidebar-primary-items__start sidebar-primary__section">
+        <div class="sidebar-primary-item">
+
+  
+
+<a class="navbar-brand logo" href="../">
+  
+  
+  
+  
+  
+    
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+      
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+    <img src="../_static/es-logo.png" class="logo__image only-light" alt="eScience-2024  documentation - Home"/>
+    <script>document.write(`<img src="../_static/es-logo.png" class="logo__image only-dark" alt="eScience-2024  documentation - Home"/>`);</script>
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+
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+ document.write(`
+   <button class="btn navbar-btn search-button-field search-button__button" title="Search" aria-label="Search" data-bs-placement="bottom" data-bs-toggle="tooltip">
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+    <span class="search-button__default-text">Search</span>
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+   </button>
+ `);
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+        <div class="sidebar-primary-item"><nav class="bd-links bd-docs-nav" aria-label="Main">
+    <div class="bd-toc-item navbar-nav active">
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+        <ul class="nav bd-sidenav bd-sidenav__home-link">
+            <li class="toctree-l1">
+                <a class="reference internal" href="../">
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+        <ul class="nav bd-sidenav">
+<li class="toctree-l1"><a class="reference internal" href="../feide/">Jupyterhub access</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/masked_and_weighted_average/">Using masks and computing weighted average</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../learning/notebooks/projections/">Using cartopy and projections for plotting</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="../git_integration/github-work/">Pull requests and Issues</a></li>
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diff --git a/searchindex.js b/searchindex.js
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@@ -0,0 +1 @@
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