era5_and_catchment_table.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e3eb1e67-6a0c-42ad-9091-eb531ca1df40",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 1. Catchments\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9a27178d-4488-4690-89fb-bbf37f5611f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' update: \\n    ...joined.shp files for catchments (after the joint operation in qgis \\n                  -> add glacier attributes into it (one-to-one join) \\n       + maybe needs foltering some super small polygons that are identified as catchments by qswat (filter by area) \\n    ..centroids.shp files for centroids (split column with coordinates) \\n    . \\n'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1. calculate catchment areasa in Qgis usuing Qswat model for catchment deliniation, \n",
    "#    build a table with catchment information and morphometrical (catchments + streams + glaciers) \n",
    "\n",
    "#   - take dem from jaxa (aw3d30m)\n",
    "#   - reproject to UTM (utm will allow the areas)\n",
    "#   - calcualte streams (same area threshold as for channels)\n",
    "#   - calculate catchments/watersheds (5km2 area)\n",
    "#   - zonal statistics bacse on elevetion \n",
    "#   - zonal statistics based on slope \n",
    "#   - merge streams info (length etc) with catchments atributes (LinkNO = PolygonID) \n",
    "#   - cantroid coordinates (UTM) \n",
    "#   - centroin coordinates (WGS) \n",
    "#   - glaciers of nepal (from Jakob): \n",
    "#      - join (to \"cut\" glacier polygon by cathcments) \n",
    "#      - calculate areas ofa this new polygons (-> the % of the glacier in the catchment) \n",
    "\n",
    "\n",
    "\n",
    "#  ----------------------------------\n",
    "#  issues here: \n",
    "#    the way catchments are calculated? \n",
    "#    what parameters do we need (same as others + everything we can think of) \n",
    "\n",
    "# way to solve/ideas: \n",
    "#   maybe instead of taking square tiles of DEM take specific valeys,\n",
    "#   that makes more physical/common sence (pysheds library?) \n",
    "    \n",
    "# (anything else?)\n",
    "\n",
    "\n",
    "\n",
    "#  ----------------------------------\n",
    "#  what happens after: \n",
    "#   - take only columns that you want ( TODO: inset list of columns you want) \n",
    "#   - plot relationship of that data \n",
    "\n",
    "\n",
    "#  ----------------------------------\n",
    "''' update: \n",
    "    ...joined.shp files for catchments (after the joint operation in qgis \n",
    "                  -> add glacier attributes into it (one-to-one join) \n",
    "       + maybe needs foltering some super small polygons that are identified as catchments by qswat (filter by area) \n",
    "    ..centroids.shp files for centroids (split column with coordinates) \n",
    "    . \n",
    "'''\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9276c8ed-bdcc-47c3-92f8-66770da707e6",
   "metadata": {},
   "source": [
    "## 2. Climate data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ead12a56-968f-443f-b9c2-f75889f1a423",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2. Take climate data and centroid coordinates of the catchments and fetch the data using coordinates,\n",
    "#    then append to the table \n",
    "#    explore the data \n",
    "\n",
    "#  issues here: scale! climate data needs to be downscaled somehow\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "18b3727e-a3a3-43e6-b38d-8741ab798fae",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import seaborn as sns\n",
    "import geopandas as gpd\n",
    "from shapely.geometry import Point\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e3edf38b-75cf-4186-b66d-64bd52c1b35a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#  names of variables: \n",
    "\n",
    "#  df                      - original cathcments table \n",
    "#  catchments              - df with only 'chosen' columns \n",
    "#  catchments              - df with only 'chosen' columns with new names (!!!)\n",
    "#  catchments_glacier      - only glacier parameters\n",
    "#  catchments_cath_streams - river and catchment parameters \n",
    "\n",
    "#  f - original netcdf\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fce1aaef-d422-47d1-8102-a4c957e77218",
   "metadata": {},
   "source": [
    "### get all catchment data to a pd dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0468ee49-9d8e-4d73-a982-b3446005e206",
   "metadata": {},
   "outputs": [],
   "source": [
    "# read table \n",
    "# df = pd.read_csv('glaciers_catchments_streams_intersection.csv')\n",
    "# plot shp. with cathments on top of era5 data: \n",
    "\n",
    "# catchment polygons\n",
    "catch_polygons = gpd.read_file('catchments/likely_correct/catchments_glaciers_joined_one2one.shp')\n",
    "# centroid points\n",
    "catch_points   = gpd.read_file('catchments/likely_correct/catchments_centroids.shp')\n",
    "# intersected glaciers \n",
    "catch_glaciers = gpd.read_file('catchments/likely_correct/glaciers_intersect_catchments.shp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "34f6a8f0-4d81-438f-ad96-ab371f2431cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# glaciers groupby \n",
    "catch_glaciers = catch_glaciers[['PolygonId', 'gl_area_km']]\n",
    "catch_glaciers['gl_area_m2'] = catch_glaciers.gl_area_km*(10**6)\n",
    "catch_glaciers_groupby = catch_glaciers.groupby('PolygonId').sum()\n",
    "\n",
    "# catchment centroid points add to polygons: \n",
    "catch_points = catch_points[['PolygonId', 'x_centr', 'y_centr']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "68daef7c-6cda-436f-a54b-879e6cc284f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f9c68eed850>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(catch_points.x_centr, catch_points.y_centr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c618ff02-c37b-416d-af5b-d06bca040c61",
   "metadata": {},
   "outputs": [],
   "source": [
    "# add stuff to cathment polygons\n",
    "\n",
    "''' merge tables: take 'smaller' table and add the 'bigger' table to it \n",
    "# (otherwise there will be a lot of nan vallues, .dropna - if there are any)'''\n",
    "# combined_table = catchments.merge(mean_points_df, on=['x_wgs', 'y_wgs'], how='left')\n",
    "\n",
    "df = catch_polygons.merge(catch_points, on = ['PolygonId'], how = 'left')\n",
    "df = df.merge(catch_glaciers_groupby, on = ['PolygonId'], how = 'left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "50730ff2-b1e1-44dc-bd11-851644988911",
   "metadata": {},
   "outputs": [],
   "source": [
    "# to dataframe \n",
    "\n",
    "df = pd.DataFrame(df) \n",
    "# df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4f3c19f4-332d-4bd5-91bb-f68902529022",
   "metadata": {},
   "outputs": [],
   "source": [
    "# what columns are you interested in?\n",
    "\n",
    "## ----- glacier parameters: \n",
    "\n",
    "# \"Elv_min\": \"elv_min_glacier\"\n",
    "# \"Elv_mean\": \"elv_mean_glacier\"\n",
    "# \"Elv_max\": \"elv_max_glacier\"\n",
    "# \"Slope_min\": \"min_slope_glacier\"\n",
    "# \"Slope_mean\": \"mean_slope_glacier\"\n",
    "# \"Slope_max\": \"max_slope_glacier\"\n",
    "# \"Aspect\": \"aspect_glacier\"\n",
    "# \"Area_SqKm\": \"area_glacier_km2\"\n",
    "# \"Thickness\": \"thickness\"\n",
    "\n",
    "## ---- catchments: \n",
    "\n",
    "# PolygonId: \"PolygonId\"\n",
    "# Area : \"catchment_area\"\n",
    "# X : \"x_utm\"\n",
    "# Y : \"y_utm\"\n",
    "# x_wgs : \"x_wgs\"\n",
    "# y_wgs : \"y_wgs\"\n",
    "# _mean_elev : \"mean_elevation\"\n",
    "# _median_el \" \"mean_elevation\"\n",
    "# _stdev_ele: \"std_elevation\"\n",
    "# _min_elev: \"min_elevation\"\n",
    "# _max_elev: \"max_elevation\"\n",
    "# _range_ele: \"range_elevation\"\n",
    "# _mean_slop: \"mean_slope\"\n",
    "# _median_sl: \"median_slope\"\n",
    "# _stdev_slo: \"std_slope\"\n",
    "# _min_slope: \"min_slope\"\n",
    "# _max_slope : \"max_slope\"\n",
    "# _range_slo : \"range_slope\"\n",
    "# _varianc_1 : \"variance_slope\"\n",
    "# area_glac_ : \"area_of_glacier\"\n",
    "\n",
    "\n",
    "## ----- streams: \n",
    "\n",
    "# strmOrder: \"stream_order\"\n",
    "# Length: \"stream_length\"\n",
    "# strmDrop: \"stream_drop\"\n",
    "# Slope: \"stream_slope\" \n",
    "# StraightL: \"stream_streightL\"\n",
    "\n",
    "# df.rename(columns={\"A\": \"a\", \"B\": \"c\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3b7db526-17bf-492b-98ae-e3cce078ae9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PolygonId', 'Area', 'Subbasin', 'X', 'Y', '_mean_elev', '_median_el',\n",
       "       '_stdev_ele', '_min_elev', '_max_elev', '_range_ele', '_variance_',\n",
       "       'LINKNO', 'DSLINKNO', 'USLINKNO1', 'USLINKNO2', 'DSNODEID', 'strmOrder',\n",
       "       'Length', 'Magnitude', 'DSContArea', 'strmDrop', 'Slope', 'StraightL',\n",
       "       'USContArea', 'WSNO', 'DOUTEND', 'DOUTSTART', 'DOUTMID', 'BasinNo',\n",
       "       '_mean_slop', '_median_sl', '_stdev_slo', '_min_slope', '_max_slope',\n",
       "       '_range_slo', '_varianc_1', 'ID', 'GLIMS_ID', 'Basin', 'Sub_Basin',\n",
       "       'Images', 'Longitude', 'Latitude', 'Class', 'Elv_min', 'Elv_mean',\n",
       "       'Elv_max', 'Slope_min', 'Slope_mean', 'Slope_max', 'Aspect',\n",
       "       'Area_SqKm', 'Thickness', 'Reserve', 'Year', 'Shape_area', 'Shape_len',\n",
       "       'x_centroid', 'y_centroid', '_count', '_sum', '_mean', '_median',\n",
       "       '_stdev', '_min', '_max', '_range', '_minority', '_majority',\n",
       "       '_variety', '_variance', 'geometry', 'x_centr', 'y_centr', 'gl_area_km',\n",
       "       'gl_area_m2'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# len(df)\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1254be98-0379-476f-b3cb-1730079ad168",
   "metadata": {},
   "outputs": [],
   "source": [
    "# take the columns you want, rename (to avoid confusuon, but be very carefull here!) \n",
    "\n",
    "catchments = df[['PolygonId', 'Area', 'X', 'Y', '_mean_elev', '_median_el', '_stdev_ele', \n",
    "                 '_min_elev', '_max_elev',\n",
    "                 '_range_ele', '_variance_', 'strmOrder', 'Length', 'strmDrop', 'Slope', '_varianc_1'  ,\n",
    "                 '_mean_slop', '_median_sl', '_stdev_slo', '_min_slope', '_max_slope', '_range_slo', \n",
    "                 'x_centr', 'y_centr', 'StraightL', \n",
    "                 'gl_area_m2', \n",
    "                 # 'gl_area_km'\n",
    "                ]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4c85e4fe-8bbe-45e8-bedb-c29388f5255f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PolygonId', 'Area', 'X', 'Y', '_mean_elev', '_median_el', '_stdev_ele',\n",
       "       '_min_elev', '_max_elev', '_range_ele', '_variance_', 'strmOrder',\n",
       "       'Length', 'strmDrop', 'Slope', '_varianc_1', '_mean_slop', '_median_sl',\n",
       "       '_stdev_slo', '_min_slope', '_max_slope', '_range_slo', 'x_centr',\n",
       "       'y_centr', 'StraightL', 'gl_area_m2'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check if its all correct\n",
    "# catchments.head()\n",
    "catchments.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ec70c64d-f53f-4afd-a07d-20d5717b70aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# raname columns so that it makes sense: \n",
    "\n",
    "\n",
    "catchments = catchments.rename(columns={\n",
    "                'PolygonId': 'PolygonId', \n",
    "                 'Area': 'catchment_area_m2', \n",
    "                 'X': 'x_utm', \n",
    "                 'Y': 'y_utm', \n",
    "                 '_mean_elev': 'mean_elevation',\n",
    "                 '_median_el': 'median_elevation',\n",
    "                 '_stdev_ele': 'std_elevation', \n",
    "                 '_min_elev': 'min_elevation', \n",
    "                 '_max_elev': 'max_elevation',\n",
    "                 '_range_ele': 'range_elevation', \n",
    "                 '_variance_': 'variance_elevation', \n",
    "                 'strmOrder': 'stream_order', \n",
    "                 'Length': 'stream_length', \n",
    "                 'strmDrop': 'stream_drop', \n",
    "                 'Slope': 'stream_slope', \n",
    "                 '_mean_slop': 'mean_slope', \n",
    "                 '_median_sl': 'median_slope', \n",
    "                 '_stdev_slo': 'std_slope', \n",
    "                 '_min_slope': 'min_elevation', \n",
    "                 '_max_slope': 'max_slope', \n",
    "                 '_range_slo': 'range_slope', \n",
    "                 '_varianc_1' : 'variance_slope',\n",
    "                 'x_centr': 'x_wgs', \n",
    "                 'y_centr': 'y_wgs', \n",
    "                 'StraightL': 'StraightL', \n",
    "                 'gl_area_m2': 'area_glacier_m2', \n",
    "                 # 'gl_area_km': 'area_glacier_km2'\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "df459ace-66f9-44a8-b788-aea073e80098",
   "metadata": {},
   "outputs": [],
   "source": [
    "catchments['glacier_percent'] = (catchments.catchment_area_m2 / catchments.area_glacier_m2)*100\n",
    "# catchments.glacier_percent.replace(0, np.nan, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "66553177-1f23-48f2-b72c-995ea88ca7cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# catchments\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c6474bfb-b9b6-46f9-8149-2ebb0f544f98",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max % of the glacier in the catchment:  50.298\n"
     ]
    }
   ],
   "source": [
    "print('max % of the glacier in the catchment: ', catchments.glacier_percent.max())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c18ee1d-99f2-4423-bf17-b7d9d5ac0356",
   "metadata": {},
   "source": [
    "## Correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bda7928d-903b-410e-af4e-d9ae554b8cbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "catchments_corr = catchments.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "39d5aa96-9ea1-42d6-96c7-ce5c872f2a5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'various parameters')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# catchments and streams \n",
    "\n",
    "plt.figure(figsize=(10, 10))\n",
    "\n",
    "# mask for the upper triangle\n",
    "mask = np.triu(np.ones_like(catchments_corr, dtype=bool))\n",
    "# color palette\n",
    "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
    "# heatmap \n",
    "sns.heatmap(catchments_corr, cmap=cmap, mask = mask)\n",
    "# sns.heatmap(catchments_corr, cmap=cmap)\n",
    "plt.title('various parameters', fontsize = 15)\n",
    "\n",
    "# plt.savefig('various_params_corr.png', dpi = 300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adcc5e8e-e204-43f2-93d9-a4d5b364f5a0",
   "metadata": {},
   "source": [
    "## Scatterplots (todo: many scatterplots with many parameters) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "07b69232-5bdf-410b-9347-b2ae349a3a9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='stream_length', ylabel='median_elevation'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 576x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "# sns.scatterplot(data = catchments, x = \"catchment_area_m2\", y = \"stream_length\")\n",
    "\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.scatterplot(data = catchments, x = \"stream_length\", y = \"median_elevation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c36b345d-48cd-4874-b0a5-7bb4641841ba",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "453d6b6d-8335-4280-93ef-6f0c7673e7de",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c4155a1-b0c3-4e88-96b3-a30ea924ef53",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1dd13d52-d3fa-4cff-b211-98be0eb75f9c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf1b1e33-c7ed-46cd-8935-33b5c232f1e0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0753cc9f-9d51-43ad-9e38-c90f8bc4282a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "d71c7035-3e73-4f0e-ae9d-bb5c52ed9b00",
   "metadata": {},
   "source": [
    "# Climate era5 data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "2608a424-0fc1-454e-b97a-5c36d231c171",
   "metadata": {},
   "outputs": [],
   "source": [
    "# f  - original era5\n",
    "# df - original era5 as dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c0c03ad2-3ecf-4d1c-9afd-092b571d8e78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' whats in there: \\n# 2m temperature, Forecast albedo, Snow depth, Surface latent heat flux, Total precipitation\\n\\n# 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, \\n2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 \\n# January, February, March, April, May, June, July, August, September, October, November, December (monthly)\\n\\n'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# open dataset\n",
    "f = xr.open_dataset('era5_monthly_averaged_reanalysis_1979_present.nc')\n",
    "\n",
    "''' whats in there: \n",
    "# 2m temperature, Forecast albedo, Snow depth, Surface latent heat flux, Total precipitation\n",
    "\n",
    "# 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, \n",
    "2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 \n",
    "# January, February, March, April, May, June, July, August, September, October, November, December (monthly)\n",
    "\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e6e1a31f-f170-4640-9da8-02d0549c836f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# f\n",
    "# f['tp']\n",
    "# print(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "2162f6bb-10f4-48e1-9c5b-ffe7397ca5c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(384, 9, 13)\n"
     ]
    }
   ],
   "source": [
    "# extract arrays from .nc file:\n",
    "\n",
    "lons = f.longitude \n",
    "lats = f.latitude\n",
    "time = f.time\n",
    "\n",
    "t2m  = f.t2m   # 2m temp in K\n",
    "fal  = f.fal   # forecasted albedo \n",
    "sd   = f.sd    # snow depth\n",
    "slhf = f.slhf  # surface latent heat flux\n",
    "tp   = f.tp    # total precip\n",
    "\n",
    "print(tp.shape) # shape: time, lat lon "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a847069f-a55c-42a1-ad14-3089cae9df13",
   "metadata": {},
   "outputs": [],
   "source": [
    "## convert netCDF to pandas data frame \n",
    "# convert to dataframe:\n",
    "# df = f.reset_coords(drop=True).to_dataframe()\n",
    "# df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c336a7f5-d063-470d-b814-c0ab353a131c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Frozen({'longitude': 13, 'latitude': 9, 'time': 384})"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# time.values\n",
    "# time\n",
    "f.dims # dimentions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89119a80-8cd6-459f-8cce-2f65b25bacd7",
   "metadata": {},
   "source": [
    "## plot era5 data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5f365d87-46a9-4d6e-9c88-84ff10b8a2c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape of the data: (384, 9, 13)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fde728e1650>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot an example \n",
    "print('shape of the data:', t2m.shape)\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "t2m[4,:,:].plot() # t2m[0,:,:] - 0 time step \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b7e9857-6e67-47b7-9014-33e6c426faf1",
   "metadata": {},
   "source": [
    "### plot catchments on top of era5 data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "92cc2498-2a51-4eca-860f-3a5ef2868a54",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot shp. with cathments on top of era5 data: \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a186eb23-c7e8-44cd-b47a-59705734bb61",
   "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>PolygonId</th>\n",
       "      <th>Area</th>\n",
       "      <th>Subbasin</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>_mean_elev</th>\n",
       "      <th>_median_el</th>\n",
       "      <th>_stdev_ele</th>\n",
       "      <th>_min_elev</th>\n",
       "      <th>_max_elev</th>\n",
       "      <th>...</th>\n",
       "      <th>_median</th>\n",
       "      <th>_stdev</th>\n",
       "      <th>_min</th>\n",
       "      <th>_max</th>\n",
       "      <th>_range</th>\n",
       "      <th>_minority</th>\n",
       "      <th>_majority</th>\n",
       "      <th>_variety</th>\n",
       "      <th>_variance</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>35</td>\n",
       "      <td>2082.39</td>\n",
       "      <td>None</td>\n",
       "      <td>328760</td>\n",
       "      <td>3139854</td>\n",
       "      <td>4262.080782</td>\n",
       "      <td>4279.0</td>\n",
       "      <td>567.428865</td>\n",
       "      <td>3028.0</td>\n",
       "      <td>5633.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4280.0</td>\n",
       "      <td>568.392970</td>\n",
       "      <td>3028.0</td>\n",
       "      <td>5630.0</td>\n",
       "      <td>2602.0</td>\n",
       "      <td>3028.0</td>\n",
       "      <td>4386.0</td>\n",
       "      <td>2521</td>\n",
       "      <td>323070.568314</td>\n",
       "      <td>POLYGON ((85.26332 28.35510, 85.26333 28.35484...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45</td>\n",
       "      <td>2025.14</td>\n",
       "      <td>None</td>\n",
       "      <td>330719</td>\n",
       "      <td>3134755</td>\n",
       "      <td>4182.969949</td>\n",
       "      <td>4178.0</td>\n",
       "      <td>576.714259</td>\n",
       "      <td>2733.0</td>\n",
       "      <td>5635.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4179.0</td>\n",
       "      <td>576.573312</td>\n",
       "      <td>2733.0</td>\n",
       "      <td>5635.0</td>\n",
       "      <td>2902.0</td>\n",
       "      <td>2733.0</td>\n",
       "      <td>4290.0</td>\n",
       "      <td>2701</td>\n",
       "      <td>332436.784113</td>\n",
       "      <td>POLYGON ((85.27338 28.30514, 85.27136 28.30511...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>223</td>\n",
       "      <td>2660.66</td>\n",
       "      <td>None</td>\n",
       "      <td>360687</td>\n",
       "      <td>3129518</td>\n",
       "      <td>5035.085857</td>\n",
       "      <td>4975.0</td>\n",
       "      <td>583.998144</td>\n",
       "      <td>3952.0</td>\n",
       "      <td>6620.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4977.0</td>\n",
       "      <td>583.656671</td>\n",
       "      <td>3952.0</td>\n",
       "      <td>6620.0</td>\n",
       "      <td>2668.0</td>\n",
       "      <td>3958.0</td>\n",
       "      <td>4475.0</td>\n",
       "      <td>2539</td>\n",
       "      <td>340655.109123</td>\n",
       "      <td>POLYGON ((85.61642 28.26023, 85.61584 28.26023...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>63</td>\n",
       "      <td>1239.68</td>\n",
       "      <td>None</td>\n",
       "      <td>364435</td>\n",
       "      <td>3131397</td>\n",
       "      <td>5389.377854</td>\n",
       "      <td>5344.0</td>\n",
       "      <td>352.609830</td>\n",
       "      <td>4569.0</td>\n",
       "      <td>6315.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5343.0</td>\n",
       "      <td>352.459732</td>\n",
       "      <td>4569.0</td>\n",
       "      <td>6315.0</td>\n",
       "      <td>1746.0</td>\n",
       "      <td>4569.0</td>\n",
       "      <td>5217.0</td>\n",
       "      <td>1655</td>\n",
       "      <td>124227.862933</td>\n",
       "      <td>POLYGON ((85.62013 28.28608, 85.61984 28.28608...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>81</td>\n",
       "      <td>1274.48</td>\n",
       "      <td>None</td>\n",
       "      <td>347053</td>\n",
       "      <td>3125258</td>\n",
       "      <td>4625.695439</td>\n",
       "      <td>4725.0</td>\n",
       "      <td>715.079257</td>\n",
       "      <td>2679.0</td>\n",
       "      <td>6482.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4726.0</td>\n",
       "      <td>715.406067</td>\n",
       "      <td>2679.0</td>\n",
       "      <td>6482.0</td>\n",
       "      <td>3803.0</td>\n",
       "      <td>2679.0</td>\n",
       "      <td>4626.0</td>\n",
       "      <td>3241</td>\n",
       "      <td>511805.840254</td>\n",
       "      <td>POLYGON ((85.44523 28.22210, 85.44524 28.22185...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 73 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   PolygonId     Area Subbasin       X        Y   _mean_elev  _median_el  \\\n",
       "0         35  2082.39     None  328760  3139854  4262.080782      4279.0   \n",
       "1         45  2025.14     None  330719  3134755  4182.969949      4178.0   \n",
       "2        223  2660.66     None  360687  3129518  5035.085857      4975.0   \n",
       "3         63  1239.68     None  364435  3131397  5389.377854      5344.0   \n",
       "4         81  1274.48     None  347053  3125258  4625.695439      4725.0   \n",
       "\n",
       "   _stdev_ele  _min_elev  _max_elev  ...  _median      _stdev    _min    _max  \\\n",
       "0  567.428865     3028.0     5633.0  ...   4280.0  568.392970  3028.0  5630.0   \n",
       "1  576.714259     2733.0     5635.0  ...   4179.0  576.573312  2733.0  5635.0   \n",
       "2  583.998144     3952.0     6620.0  ...   4977.0  583.656671  3952.0  6620.0   \n",
       "3  352.609830     4569.0     6315.0  ...   5343.0  352.459732  4569.0  6315.0   \n",
       "4  715.079257     2679.0     6482.0  ...   4726.0  715.406067  2679.0  6482.0   \n",
       "\n",
       "   _range  _minority  _majority  _variety      _variance  \\\n",
       "0  2602.0     3028.0     4386.0      2521  323070.568314   \n",
       "1  2902.0     2733.0     4290.0      2701  332436.784113   \n",
       "2  2668.0     3958.0     4475.0      2539  340655.109123   \n",
       "3  1746.0     4569.0     5217.0      1655  124227.862933   \n",
       "4  3803.0     2679.0     4626.0      3241  511805.840254   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((85.26332 28.35510, 85.26333 28.35484...  \n",
       "1  POLYGON ((85.27338 28.30514, 85.27136 28.30511...  \n",
       "2  POLYGON ((85.61642 28.26023, 85.61584 28.26023...  \n",
       "3  POLYGON ((85.62013 28.28608, 85.61984 28.28608...  \n",
       "4  POLYGON ((85.44523 28.22210, 85.44524 28.22185...  \n",
       "\n",
       "[5 rows x 73 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# len(catch_polygons)\n",
    "# len(catchments)\n",
    "# catchments\n",
    "catch_polygons.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5d992b13-7675-46a9-8f60-8215bc708f41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "catch_polygons.boundary.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "98d4a41b-b431-4de0-95e3-840777d2aad7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'time = 2002-11-01'}, xlabel='longitude [degrees_east]', ylabel='latitude [degrees_north]'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0I15nARcAS81sSXrsYyQDqovT1zcB3wYws1nAN939PHcvm9n7gVuAEPiWuy9L21wJ/MTM3g08RZInJiIiImNoX19xWAujOvBy9wUMnasFcM0Q168Hzhvw+rfAb4e4bhvwkhHqpoiIiEhNqHK9iIiI7LWkjte+veKwFvQNiYiIiNSIIl4iIiIyIqJdZhdJH0W8RERERGpEES8RERHZa45WNVZDES8RERGRGtHAS0RERKRGNNUoIiIiI0DlJKqhb0hERESkRhTxEhERkRERq5zEsBTxEhEREakRRbxERERkr7lDpHISw1LES0RERKRGFPESERGREaFVjcPTNyQiIiJSIwdOxKtUJti4fax7QXnL1rHuQj8bH+PuTEvzWHcBAO/qHusuVNi0KWPdBQCs7GPdBQAyxeJYd2HcifPj48e3h+Mnp2e8BFuCQjzWXRgTjmnLoCqMk/9MRURERPZ/4+NXJhEREdnnqY7X8BTxEhEREakRRbxERERkrzkox6sKiniJiIiI1IgiXiIiIjIiVMdrePqGRERERGpEAy8RERGRGtFUo4iIiOw9VwHVaijiJSIiIlIjiniJiIjIXnNUQLUainiJiIiI1IgiXiIiIjIilOM1PEW8RERERGpkVAdeZjbXzG43s+VmtszMLkmPn2Rm95rZEjNbaGanD9H2qPR836PdzC5Nz33SzNYNOHfeaH4OERER2b2+LYNq8diXjfZUYxm43N0Xm1kzsMjMbgU+D3zK3X+XDpo+D7xoYEN3fww4CcDMQmAd8PMBl3zR3b8wyv0XERERGTGjOvBy9w3AhvR5h5ktB2aTDIxb0ssmAOuHudVLgJXuvma0+ioiIiJ7Z1+PRtVCzZLrzWwecDJwH3ApcIuZfYFkuvPMYZq/BfjhTsfeb2Z/DywkiartGNEOi4iIiIywmiTXm1kTcCNwqbu3A+8DLnP3ucBlwHW7aZsDXgP8dMDhrwKHkUxFbgCu2kXbi9IcsoXFuGckPoqIiIgMwalNfte+HlUb9YGXmWVJBl03uPtN6eELgb7nPwWekVw/wCuBxe6+qe+Au29y98jdY+Abu2rv7te6+6nufmouqN/bjyIiIiKyV0Z7VaORRLOWu/vVA06tB16YPj8XWLGb27yVnaYZzWzmgJevBx7e+96KiIjI3oixmjz2ZaOd43UWcAGw1MyWpMc+BvwTcI2ZZYBe4CIAM5sFfNPdz0tfNwAvA96z030/b2YnkSTprx7ivIiIiMi4M9qrGhfALoempwxx/XrgvAGvu4EpQ1x3wUj1UUREREaAa1VjNVS5XkRERKRGNPASERERqRFtki0iIiJ7rW/LINk9RbxEREREakQRLxERERkRingNTxEvERERkRpRxEtERET2Wt+WQbJ7iniJiIiI1IgiXiIiIjIiXBGvYSniJSIiIvsVM5trZreb2XIzW2Zml6THTzKze81siZktNLPT0+PzzKwnPb7EzL42Wn1TxEtERERGxDjawLoMXO7ui82sGVhkZrcCnwc+5e6/M7Pz0tcvStusdPeTRrtjGniJiIjIfsXdNwAb0ucdZrYcmE1S57UlvWwCsL7WfdPAS0RERPaaj9NNss1sHnAycB9wKXCLmX2BJN3qzAGXzjezB4B24OPufudo9Ec5XiIiIrKvmZrmaPU9LhrqIjNrAm4ELnX3duB9wGXuPhe4DLguvXQDcLC7nwx8EPiBmbUMdc+9pYiXiIiIjIgarmrc6u6n7u4CM8uSDLpucPeb0sMXApekz38KfBPA3QtAIX2+yMxWAkcCC0e64wfMwCtqytN29ryx7gZh8ZCx7kKFRT7WXQAg7iiPdRcAyK1vG+suVEQTGsa6CwBknto81l0AIN7ROtZdGHcyh84d6y4AUJrSONZdqCg1j4//S4vHRzcOaGZmJNGs5e5+9YBT64EXAn8GzgVWpNdPA7a7e2RmhwJHAKtGo2/6z0NERERGwLiqXH8WcAGw1MyWpMc+BvwTcI2ZZYBeoG+K8gXAp82sDETAe919+2h0TAMvERER2a+4+wLYZW2LU4a4/kaSaclRp+R6ERERkRpRxEtERERGhLYMGp4iXiIiIiI1ooiXiIiI7DVnfBZQHW8U8RIRERGpEUW8REREZO95sm2Q7J4iXiIiIiI1ooiXiIiIjIh4l6WzpI8iXiIiIiI1ooiXiIiI7DVHdbyqoYiXiIiISI0o4iUiIiIjYFxtkj1ujWrEy8zmmtntZrbczJaZ2SXp8ZPM7F4zW2JmC83s9F20X21mS/uuG3B8spndamYr0j8njebnEBERERkJoz3VWAYud/djgDOAi83sWODzwKfc/STgE+nrXXmxu5/k7qcOOHYFcJu7HwHclr4WERGRMeRem8e+bFQHXu6+wd0Xp887gOXAbJIcvJb0sgnA+j289WuB69Pn1wOv2+vOioiIiIyymuV4mdk84GTgPuBS4BYz+wLJ4O/MXTRz4A9m5sDX3f3a9PgMd98AyeDOzKaPZt9FRERkeFrVOLyarGo0sybgRuBSd28H3gdc5u5zgcuA63bR9Cx3fy7wSpJpyhfs4ftelOaQLSwVuvbiE4iIiIjsvVEfeJlZlmTQdYO735QevhDoe/5TYMjkendfn/65Gfj5gOs2mdnM9P4zgc27aH+tu5/q7qdm840j8XFEREREnrXRXtVoJNGs5e5+9YBT64EXps/PBVYM0bbRzJr7ngMvBx5OT99MMngj/fOXI997ERERqVaS+G41eezLRjvH6yzgAmCpmS1Jj30M+CfgGjPLAL3ARQBmNgv4prufB8wAfp6M3cgAP3D336f3uBL4iZm9G3gKeOMofw4RERGRvTaqAy93XwC73DHzlCGuXw+clz5fBZy4i/tuA14yQt0UERGREaACqsPTlkEiIiIiNaItg0RERGRE7OvFTWtBAy+R/URvsZ3WjqfY3rGKmVNOBJwN2x5i5pQTaetci3vMxOaD6S20EcUFMKNcLtDcOJNCsR3DyOcmEHsZ95hMmCcotFKKe5mUm0UurB/0ftsL6yjGPWQtT1d5B7MajsGJWde9nIMbj2d7YR2xRzRmJ1EfNtMTddCYmQhAOS7SVtpMQEhrcQNN2SmU4h4m5+dQFzYB0Fnazo7iBvJBAx510RptoT5oYno4l5zV7fJ72Fx+CneIrcyk4CDqgoZnXNMWbWVjtIYp4UymhrOecT72mC5vozNupc4a6PUuJocz6Yk7cCBreZqCCc/670pEDlwaeInsJ1at/3Pl+YZtD/Y/37qETTseAWBG4Vh2dD4FwKTmQwDoLmwDYEfHmkHHAay7l0LUzaNtC5icn81xE1+CmfF4290U495B79/WegetpQ1AMmiq6H2Sclyko7yVbJCnIZxIW2kT+aCBhnQg1lVuBWB7IdnE4ugJZ3PflhsJLUMYZGmIG8kH9ZTiAu3xNgpxD402gbIVn/E9FL2XrriNicF0dsSbOTZ3RuVcwXtYWer/bjZHT7E5eooc9RTp2eV36+6sKi1lUjijcmx+5jjqg6ZdthE5EO3rKw5rQQMvkf1MQ34yTfUzaGqYQWvHGnLZpsrAq60rGdi4OxObDmFS8yEEQYYoKlYGXhMa5zJt4pGYBax67Dd0lLZS8l52FNazePuv6S63MSmXRImm181jUn42j7XdRTbIV/rQXW6lITMRM8Pd6ShtJfIS5gEexAAU4m7y3khoWeY2Poenu5ZV2j/atoBMkKMU9+Kx0+0Rh2VOZG35cWKP6PZ2ur190EAIoDNuo+TJgDBdET1I36ArjmM6fAf1QRMlL7DNNzApmEFgfWmvBjiTghmsKj005Pdc9AL1aOAlIntGAy+R/URgIY3105g7vb8e8UFTjqdcLpDLNFIsdxF7mWKpE3dnxdO38sKTP5RcmIU4LlOOetmyYzmzp50MwLbiWgILMTfMArpKrZgZscdMzE1nev2hABw36VwAtmxaDSSDqtMnnQ/A/Vt+TiHuBpwgyHBw0/E83PonANpLW6gPW5iQm8GE3Ay2FdayofvxyufJBQ0U424yhGyL1nNs7gzcnbt7bwYGR52WFe6pDLp2HpAVvZf7e2+pvO72ZMqwO+ogICAmYnP0NKfkX0Le6omJ6Irbeay0kKL3YgQ07jS1OCGc8qz/rkT2R86+X2OrFrSqUWQ/EXuEexJN2rB1KQ+t/Al3Lf0SC5ZeQ0wMJNGnXKaJ2MvEXuSeh78MwF1Lv1SJEHX0bKS32MZdS78EJJGjjOUq7wEwJT+bg5tOeEYfzpnxDtydUtzLHRu/C0Bv3EU2qMMIMIxcUM85M95RadMTtVeeT8nP4bhJ53JUy9kUox4iLxJY8vvh+vLKSn/yluRtLS7cBkAUlyl5AeeZg66t5fWsKD5A3hpwPE3+TSJaAQEZsjgx4Cwt3sWiwh95oHA7j5cW0VcNJyQkQzb9jp05mSP28G9HRCShiJfIfqRQ7ODupV9OBxJQLHUCUC53EwQ5SuUusplGDAOSyNVTm+4njsuYhYCRyzSy6LHv4u64R4ARBlkAMkEWx5lZf9Qu+xBYSBxHlCny5w3fpuxJHlY+TLbtWrz9N5Vrk4Gi0Vvu5P5tv+g/juPERB4zp/FYtnStApIpwiAIODp3Og8W/ly53jC6vRNw2uPtPC//Su4v3ELJC2yPNg0oJmj00EmWHDERWctjQB1NaWRrMMMICAktQ4930OMdNAeTWVtewWHZBvJWj4j006LG4WngJbIf2dq2YtCgK5dpJPaIbKaeQrEDAPeIuvxEiqUuiqVO1mxcQDnqxSwgm2mgo3szThkwGsL+6bUZdYezqfcJADrK25iQm/aM9+8pd+DESYTLAspxMugKLcspU17Nom2/IvIypbhQGeTkwwYWbL4hfZ4MzowkyhZYhi29ayr3v6fwK6aGs9karaPgSTJ8HJcJggyzM4extvw4kZd4uHgXJS+k9+pX8G4AShSpp3//VgPObXjzLr/XtaUVbIs34h4REgJJJC8fauAlIntGAy+R/UQUlytTge4RuWyS+3TU3FcwdcJR/GXJfxN7RKncDRhRXKwMtpI/6ymVezHrq8XjFONuAgvJkGNT7xMUoi5Cy1IXDL3pfHfUBiRRr3NmvIM4jrlryw+IPSIT5Dlnxjv404ZvJpE0S6Ye3Z3IywAc3nQ6T3T+lVxQT312Bq3FjZTiXjKepUgPWXKsLa9Ipv2ICclwT+E3PD//ag7JHsPacpIf1h4nKzWTa7LkLE9v3JVGsAJCspWp1b4B3IKeX5IhS0Rp0Gc6LHMST5YfTqdKqfxKPzc8egT+1kT2I65VjdXQwEtkPxEGGepyE+js3kQmU1eZPlyx9o88vOrnxF4msAxOjMdl+kYQBkyfeAw7OteQzdRzxrHv495lX8GJCTwYtFoRIPIS+cwza2NBEtmKvEzdgDILxbgH95g7Nn6XfNiQROCCeurCRp47+VX8ddtNhGke15NdDwzK/7p9w7eIPSLCyFs9vd5NTExEmRx1lClS8B42x09zUNBfBsNJEurzVocT0RN3UiKJgOWtoRIFi4kJCImJiL1MD73pNGfyv5CQh0t34Tg56shYhgZrIR/UU07vJyKyJzTwEtlPdPVsobNnM5BMM2YzjZWoThyXcBzMk6hPmCOOy+SyzeSyzTQ1HMSOzjXks03U5ZvJZpOB1fy6E5jb+Jz0Hkn0ald2FDayZPtvibxEnBY4DYKAXFBPIepiYPZH5EUKsXHn5u+RCxrIBLl00DY42nRI4wms7V6Ox2Vi4mQKkmwlN6uc3rLZJhHHyRSru1OkMOj9zAKy5AkIeH7+1dxT+HWajB+TIZdExLyn0iYmwklyzfrkrYGWcBIAR2SfSzZdcCAiAyjJa1gaeInsJ4rl7srzMMxjZrQ0zKQ+P5mN25dSKneTDevBAkrlLswCeottFIpttHWtJbAMzQ2DVwTOqJtfeR4EySJod2dN54PUhy1Mzs9m4dabKcbdOEk0LPIyxbiHOzd9H0jytfpyt86a9jbu2vIDynGRctwfMcoHTRSiTsperLQ7a9pbOLTlVNb1PIoR4OleJBnLclzuTNaUltPrybTpXYWbCQgJMCKS6daQEAfOrn8tq0pL2VBehRESBAGRl4kop3GtIgF1JIvh+1Y5QkyZDNlKvllzMJGJwTRmZQ4bwb81ETnQaOAlsp+Y3DKfhvwU5k4/jSDo/6fdVxYiCLKVQZe7E8dlIMb7cpeAju5NxHFUaRsMiOpEUZRGruCprqWV433HAMpeSgZA6dRhUlqiQMl7k+NBMCD3K0mof97UN5ALG/jj+q8P+jx3bfkR58x4BwEZurw9LYkBOCwr3g0kUage70wPR+nkYJL8nqOOBmvhrp5fVu7pfYMyC8FzxMRkLVfJ88qQwSwgTx293p1GxJLoWokiU8PZVf5tiMj+xsw+WMVlXe7+9d1dsNuBl5ndXMWbbHf3d1ZxnYiMIveY7t6tgwZdfcwCwrScRCaso1DqoD4/kXJcJAyyHDn3b1ix9o8A3LX0GrCAwEIebv0jJ01+BQBd0Y7B9yRIVzDWU4p7yYcNeLkjycHyEi8+6F3cuen7xJSTvDKMW9d9jTDIElqGwJIBUt/gbueomLtz56bv011uq6zUtAGlB0MyzMkeyeriMor0Vko71FszrfFmivRWtjXKWT15a2BO5jC2lNcl7S3D2flX81DxDopeIGNZil7A0qmSIH2vvmr2PXEHT5SWDNqCSEQG28+T6z8MfJXBi6V39l7g2Q+8gGOAf9zNeQO+PMw9xoXM9AJT3r96rLtBLoyGv6hGVrdNGusuALDtyfHRj9z2GcNfVCOZ7uGv2VnX75JaW2tf2lw5tvnPv6HcmAwcyp3tkIGoLiTbNIWywfx3fYQgk6M3jilf92dKrdvwqIyFIZnmiVjjZHqek0R5liz4EbmGpLzEqWdfPmQfHllyA22tawgzeR5vXIXnM+SYgJV6iOMyUblAFEeYGUGQIZdvYlm4mMOPeTWFzQXwmDvafoRnnFKxk8AyWJiBKJkWzFqebJjkj50x9S3ctfWHWCbDhGAGvXESeeuhGzygf/FAgIUhRQr05ErMaTgStj+QfKZ4AT1BJ7mgAXcnT4ayF8hYsqDg6AlnMzF3EI+13V3Jl3ukeC9HZ0+rDBzHzJr1Y/v+qdyO5uEvqpHstvHRF+stDX+R7Iu+5+6f3t0FZjb0ku8Bhqtc/2/u/pfdPP4MfGoPOi0io8TCDHUHzR10rP3RB/E4ZsrZf0OmsZkgl8cyYeX3tSCTY/UNX2bllz9dGXDh4FFM1NXJ5Gn9JROKhU4Kve24w+PLfj5kH4496e1kMnnc4alVt1Xyso56zt+RydQRhkkZBzMjm0vKWOzYtoJ7bv9MZXrSMAq9rckWRuVCMkizkIxlCSykEHXRU+7gL5uvr7zvKZNfw2mTX1t5nQ8byIeNnDTpleQG1Npa3bWEBVtuoBj14B6RCXKVumJRXKIY9xB7MjCc13AiU3MHkwvqOH7SucxtOLZyn0dL91dKYIhIP/faPMbIZ3d1wsxOA3D3jwx3k91GvNz9J8PdoJprRKQGzOjd+DRxdBpPXvcF3GOi7iT/aeudv8Mw4lKRuNALZmSaWlh57ZWUuzrBYygVaTjkCApbN4HHWBDw5OO/ZcUjN2EWEsflypZEbTtWseieL3HK8z9QefttWx6jp2cb5ahIVE4KpEZRgeNOfifNE2YzaepHWHjXVZRKvbhHzD7kHLo61rN1U7I5dpDJcuLJ/8iyJd8b8KGcfL4FK5QpRF2UvUjsETERxTipen9Q3eFAzJbCGkpxgXjAgOjh1j/xooMu5M7NP6AY9wy4q9MbdVGIVqcbecdYOqWYCxooxb083nkPa3qG2CA7ijACNgdPMzMz/5nnRWR/dZuZvczdB+VdmNnLgeuAuUM3G6yq5HozO5JkbvOQgW3c/dyquysio8rLyfTGmu/+X3rEsGyOIJMFjGLr9uRXRRucnpBpaKTc00VY30hh60YOf89HAdjw+5/RuXRxequIIAiBkFKxk2yukUJPK3ff/hlOft772PD0X9m25RGKhWTbnkymjiDIcMqZlxCGyRToqsd+nQxuPMIw1jzxBxqbZxEEIUEmz6w5z6OhaTrzjzyPR5f+mDgqkcnWUSx2kqeu0t+6sJmeqB3HibzI1uIatm5dQz5oJPZyWvE+iYyVKXDHpu9SjHsrOWRZ6ih6N4W4G0tLqtaHzZQoMq/hJOoyTZVNvAtRV6XdoO+amKnhrJH5ixPZTzj7fY7X14Hb08HXFgAzextJJOxvq71Jtasafwp8DfgGMH6SlESkYuo5r2Drnb+vTO/Nef2F1E2fxVM/+jqltu1YEOBxTKa5BQtC4mIRgoAgkyGsayDqSrYUWvn1z3HYez5KfvpMivlm4jhi0pQjOfyYV7Ho7msAiKIS7hHucP+Cq8nnWwjCDOAEYY55R/wN0w86kWJvG6vW3EnrthWVfubyzRQLHcQe09G+DiPZ9mf2IWcmn2P6MZz54k+w6O4vVtoUutor06OTcgdxYuPLuH9b/2pFgO5ya/rMeMGMC/jTxuuIPaIQ9WBmFKIuzpj6RpqySU7hnZtvSPejdJ4/7c2s7nqAnridnNdz8uRX8kjbXwA4edJ5ODHN2SnEccyyLX/AzGiNtzJNqxxFDhju/g0z6wX+lEa53kySTP9id19d7X2qHXiV3f2re95NEamVIJPFwkwl8tW16jHqps/i4Le8h7hcZtU3/xsLQpqPPJ6Ox5cSFZMVfzEQ5OoI6xuJeroAY+W1V+LuZElqgh35nNcNeq8wzOEepxGumEKhvbKaMo6KrHjk56xYdhP5ugmVpHSAlonzKJd6OGj2aWxct5ByqZtyuUAuP4FFd1/DaWnSfhAEnHb25ax76h6eXHELTpl80EBoWY6f9FLKcZF82FgZZAIU4mRFQmAhd26+gazVUfAk4T72iMBCFm//DWdPexsLt/8ScApxF7FH3LH5e4Rp/7cWngKSUhhmxpquh3jOxBdW+jUncyTrov6BpIikHNi/I164+/fSwdcDwFPAWe6+bU/uMVw5icnp01+Z2T8DP4f+fTLcffuedVlERsvm238FJEn2HpVpfeg+ppzxYgCCTAYLklV43U+tZNar38H6X/+AuLebIF+HRxFhQxONhx5Dx6NL8HKZuFykjFFfP5n7F1wFQLGQRMWCMEsclaCvzEOQAbN0K6IAT2uBOUmlfIAjn3M+Eyb150TNnf8C7l9wVVJfLL33Xbd9kly+f2VaOSqm7+OU4xLnzHg7APds/WnyvumgLsk983SqA3rLHUBITDndYzEpmlqIu7hzy/fTEhHWn6VrkLM6it5bee9i3E0uaGB7ce2g77mvYn2oMogiBxQzW0oyvDSgAZhCMvVogLv7CdXcZ7ifHIsGvAkkeV59HDh0TzotIqPHghCPI+b/w2Ws+ub/ALDy2is57KIrAJhw/Gm0Lb2fqLebdTd/j2zLJMoeJ2UmgKini7jQQ1jfkBxzTwZUAwRhjjgqEkUl8JggyBFmcmQydURRkRiIPSYMswRhjsACTjnzskrV+6EEYYYZs07h6Sf/DCQDsL7BV1wuEoRZwjgkG+RYsuMWuqO2SqTruZPPY3nbnXSWt1e29yl78rthSEg2yCf7QLrRG3cSe0Qx7iFreU6Z/Goe3HELZUoc03wOMxoOpRj3ct/WGylGSSJ+Ie4iYzniOK58hiAt0JoxDbxEdjaGKw5r4VUjcZPhVjXOBzCzOvcBvwqmx0aiAyIyMjyOaJhzKBaETH/xqysRsD5Tn/8S2pbeT7m7Ey+XKXW0EdY3kmlqwaMI3Jlw3Km4O82HH8vaX3yXTK9Xpv/iuEwQZNi2+VEeXfojLMwSBFnCMEt943S6OtbjnsHiMmBkMkktrEV3f5HTzr68spdi3wCmXOyuRNA2rV9EmJabAKirn8Lxp7yTpYu/Q2/3NqbEM9heWkdX1JrsxRh3E1qGB3b8DmDQHo+Ok7Ecp055DY+23UnJC0zJz2F9z+NEXsIImFY3nyWtv0828Cbmkfa/MK1uHvdtvRFIiquWvYhhRF6iO2rlga3JytCTwxck77N//x+MiOzE3deMxH2q/ZXtbuC5VRwTkTHUve5JJhx/Ks1HPIfNt/8Kj2NW/L9PEeTy/RfFSUI5cUTc3Uk4YVJSvwuYfMa5BEHA5tt/TdTVgUf9A66+HK4p04/m5OddzLIl361Ennq6NvO8F/wrmzc+xIplNxGEWU454wMsujfZrqhvqhLALOTUsy5l8X1fGdT3MMxSLvUSxyWKhU7uu/N/KlXjK+XkSTawBoi8TIbkc+WCeoiN2MvpascSS1v/SCnuJWN5thXXAk5ASD5sYHthHZGXyIX1lONkocAfN369UhQ1HzZw5pS3cO/WnxF7xKLtvyGwAMdZXExWPE4L5ozEX5nI/mU//oXEzH7t7ruNelVzzXA5XgcBs4F6MzuZ/inHFpL5TREZR4JM/96Kk045my1/+W1yPB149U0rhnX1EEdJpAvwOKn5teJ/P06mqWXQPQcmvfdpaJoGMChx/v4FVw2YJrSkLxYkNcJSfRGuu277NGEmSzbXxEmnv5fWHatY88SthJk6omIRjyPKxS6y+WYMaM5OY3sxqdR+wsSXs3j7r9Jcri7qMo2UvYR7jOMEBMTEFKKuZMNueslZUpk+JqI36qzknc3IHcaU/Bwear0VGzDoArhj83dJfuR55f9MBpaWKKMCqiIHmLOH2UrRgGN3cx4YPuL1N8A7gTnAVfQPvNqBjw3fRxGppbhUWfvC5FPOZtu9f+orrsPEk5/PjkV3EZeKhA2NlNt2gBkHveptbPz1D55xr7ChCe/opFjooKNtHc0TZtPb20ou1zIoZ2vi5MNp3f5E5XWx0MHzX/xxAE476zKiqMQ9t38mqR/mjntEEOaIygUaJx5ELt/E9INOoGXiPEqFDpYv/THlUrIa8biT/p66hiksvj3JWZuZP5JlbX8itCxF70nyt4CMZSmRbMQdUSIkQz5spLvcBjiBBZjlBhVRBTio4Qg29TxRGVCdM/3tbO55kmVtt6dXDP71/XlT30DnjrWsKz9BzvKIyEC2v9fxeu3wl1Ac7oLhcryuN7PvAW919xuq7ZmIjI2wYfBedXPOfxfrf/V93J2tC/7QfyKNdOHO2h99jUxTC5mmlkoiPsCqb/4PEUmy/EMLvzFotSFQ2c6ndfsTnHb25XS0reOhhd8AC1h09zWcfMbF9HRvZ/lDP+yPjJmRzTZRKveSyzXR29O/MLquroW6uhaCICSbbWD+ka8gl2tk0d1frPzGt6HwGGCEliUXJIVMT5r4CppzU9jcs5oHdvw2fZ+Ac6a/nTs2fR+AM6e9iUzQHw28Y9P3MTMaMxPZ0LOCmKQafRzHTK+fz0Otf6Tsyc/PjOUqA7NcUEd7vD2pC+aDB3Eisn9z97+MxH2G26sRT9Zpv2ck3kxERlfU3THodX7KVNydqLMj2WwayDS2EOTrmXbOKyvXeRwPGnR1rXmCqNBLNtdUmSrsmybsk8nkicoFioUOFt39/2ieMJtpB51ALpcMUu77y5U8suT7GJDNNXH0CW9h/hGvJAiz6SBu6GSQ5pakKOmKR37BA3/tLx94SMOJ9AXdJ+dnkwly5IJ6mnNTAJheP4/6sIX6sIWDG44HqOwL2Vd+ok9TJimiet/WnxFaFveYwDLctfWHPLTj1iRnDCMgJGO5QW2tMgzcj5NZRJ4tr9FjH1Ztcv2tZvYh4MdAV99B1fESGT+6n14FJCUk5v/jh4CAUkcb5Y5WPIoJDA5778fINDRVrgsbmoh6upn7posAiMtlnvzOF4k62/GoTCk2Mpl6orhELtfEzDmnM2feOcRxmScf/z0b1y3EggxR1Mv9C66q5ILdd0cyNVgudVNXP4UTT303mVwDcbnIuqcWgMeUy71E5QL3/uW/CcMMp5zxAYJMDrOwf5CXSRZPnz7lfP667SYAclaPEVCOS8Re5v6tv6QY93BUy5nJQIuQzYVVHMXzef7UNz5j0AXQFbVWnpsZRzSfwVPdD1GIutgWryUT5KgPWwgsICCsJPRvL6xnWjiHjvJ2clb/jPuKiAxn2IhX6l3AxcAdJLW9FgELh2tkZnPN7HYzW25my8zskvT4SWZ2r5ktMbOFZnZ6tW3Tc580s3Vp+yVmdl6Vn0NkvxXk+yu8PPnNL/DkNz7P6uuvIaxvwoKATGMLa77//yj39iabY3e2E3V3EjY0sPZn32Tl169kxf99gtKOrXgcJZGyqEwcl4ijEoXeVtas/BMdbWsJggyHHf0qznrJJwdVp1/2QDK1d8qZl5DNNZHNNXHKmR8gk0sS1u9b8AWKhQ5KxS7i9D368rkW3fsl4rjMvMNeUvkcUVSiXC5yx6bv0vdr7vOmnc/2wloiL1L2Im2lTZS9xPL2OynHJQpRF8W4h8XbfsP9235JIeqiEHVRivpLTmQsl+zlGCfTiYc0nYClPw77SlOcNe3NQN8qyuS9k9yv5LlyvEQOXGZWb2ZHPZu2VUW8+up5PQtl4HJ3X2xmzcAiM7sV+DzwKXf/XTpo+jzwomrauvsj6fkvuvsXnmW/RPY7ddNnUWzdRrmjDYByV7KCMchmCVomVRborfzKpwetXDQLkn0co7QKfRgS5OuIC70EYUAm2wh0VQqjPnj/NwAnXzeBo45/E6c8/wOsevz3bNu8jO6uTTz95J3MnX8OZkYclVm25AdMmnwY655aQBBkiKMi2VwT+boJ9HRvS6rgpyUr+lZQZnNJPlm53EO51AM4haibc2f8Y9ppyIUNRHGJwAJKcQ/5sJFMkCWKipgHtJe2EKZV8RMxj7ffy6belZTiApGXiT2iPky+izOnvoU7Nn+XmIhjJ7xoUE5YQKYS9epfYyQig/h+v0k2AGb2auALQA6Yb2YnAZ9299dU076qgZeZZYH3AS9ID/0Z+Lr7gKqFQ3D3DcCG9HmHmS0nKU/hJCUpACYA6/eg7SM7XysiidykaRzy1vcRxzGrvv5feBQx/x8/RBBkWPWtq4i6O4GkrMQRl37mGRXl+/ZoxJ2groGw4JgFPP/Fn2DLxqU8vuxnmPW3eWzpT57Rh43r/sqkqYdXpgtbtz1Oe+saonIvuXwzhx71t8yccxowoL5XWsoB4L47/juZbix2kgzwJlLu7SAfNrK8/Q6OaUl+DBnG2dPezr3bfko+zHDO9GQ7oTs330ApLhATEZKlOTOVrqiVu7b8sDIQCwa8X8kLPNn5ALPqjqIUF3CcB7f/nnNnvpvTJ7+ev27/eaUqPiSLM4FB+0SKyAHlk8DpJGMh3H2Jmc2rtnG1OV5fBbJAX8XDC9Jj/1jtG6WdOhm4D7gUuMXMvkAy3XnmHrTt834z+3uSKc/L3X1HtX0R2R8F2Rx1sw5h4x9uou3hJBMgbGyuFD499F2X0712Net+cT2WzREEAb1bNrLu59+p3KPc1VlJpg/rm4jKnURAZ8cGnnj0lwTpfo8NTTMpFbuwnX657eneThCEPLz4O+TyzcQek8s20dm5AY8jSsWuyqAL4LSzL+f+BVdhZtQ3Tqdt+8rkvTP1aVwpCdNNzB5ET5wM5Db0PFZpnw37o1J3br6Bc6a/nbw10h0nUb/Dmk6nvbSFttJmnJjQM5gFnDLp1bQWN/J0z1LcnZUdC1nZcT9OUgssJuLOzTfw3MlJFoPTX4usnP6+2R8BE5GKA+P3kbK7t9nOPwCrVG2O12nufqG7/yl9/ANw2rCtUmbWBNwIXOru7STRs8vcfS5wGXDdHrSFZNB3GHASSVTsql20vSjNIVtYbNXSb9m/dT75GFsX3ELX6scrxwxY84P+lYENc+YR5PLJNGAcDxp0AWQamwgbmgiyORrnH4G7Y0GWZQ9cj5nh7uTyzZRLyaCrsWkmx5z4NqBvCx1P9nFMf7ScdtblnHzG+8jnWwjDLJlsI8uX/oQH7vsaD9z3NR5b2p/4ftzJF5DJNhKEOTwuc9o5HyKXb8YsoDdK8sDaSpuZkp9badO3DVHy/s6fNn6L3rizcuyp7odoLW3AiTGMfNhILqhnadsfebrnYZozUynFyVRm0nsnF/TXhl68/bdJrluaO1aIulhTXg5QqSEmIgech83sbUBoZkeY2ZdIdvOpSrUDr8jMDut7YWaHQnW/7qXTlDcCN7j7TenhC4G+5z8lCdlV2xZ33+TuUVrq4hu7au/u17r7qe5+am6iViDJfm7A1Nek016Y5HGZUe5so3vd6kGXlrs7eewL/0q5s524VGTKGefS8pxTmH3+P3D4ez/GER/4JN1PrSRf14LHJeKoWKnbFcf9//S7OjfQ1DwzXc0YEwQZwjBHGGY47ezLK1OZfb8ZlkudbN/8COVSF+VSF21tT1WmJFc+9luCICCTyRPHJR7869fTRPxOeuJ0I28vUZdpIvIy5bjIhp7HOWf62ynHRXqjDkpxbxI9C1toyPTnsYWWIRPkee6kVw/6HjrK2yh7icjL5IJ6skEdmSBbGXz1ljvpidope5HIy0ReZke0mQaaabbJI/P3JrJfsRo9xtQHgOcABeAHQBvJTF5Vqv2V7cPA7Wa2iuQTHwL8w3CNLPlpex2w3N2vHnBqPfBCkvnRc4EVe9AWM5uZ5oABvB54uMrPIbLfaph7KPnps5h8ytkATD/nb1h57ZUAbPjNj5j9+gupmzaT3LSZFB9/mL4oj4UZtt37J6a/5HXUTZ1B97onWf/rH1UGS/UN07DA6O1tI45KWDrd6O6YGW07VvPo0p9QLnWDBZVCq/cvuIpMtoFpM5KaWrl8czLIsoBioYMgzBJm6ojjiN6eVrZtfgQzo1jsSuqHpW0Kve1kLEcpKpAN8/xp43U4TjkusqztdlZ2LiRK92g0jHJcJBPkOGvqWylTJBfUcefmpP7zou0387yp55MPG9hWWMuDO26pTCMWoh7qMo2Vz3VY02ksa+2rYJ9sFxRahgk+mW46KFMki1Y2ihxILNlb7GZ3fynwb8/mHtWuarzNzI4AjiIZeD3q7oVhmgGcRZIPttTMlqTHPgb8E3CNmWWAXuAiADObBXzT3c/bVVt3/y3w+XQVgQOrUYFXEYDKoKjPYRddkSTMxzFrf3ZdpYhqkM1iYYbc5GlEPck03vpffndQ2yCX5/Bj3sSkKZVgNxvW3s/a1XcAUCp2ksk28PDi7/QPlHLNeFzG0ryycqmbp578M9lsPZOmHsmUacfyxPJfAFAsdhL1thPHZTCjpzupCF/fkESS5h3+ctasuh33iMgdxymVewktkxQ9JQYCYo8BxwgwILQkgX5N9xLmNz0XgLOmvpXbNyUDtgVbfkBd0ERMRDaoAzfKXiCmjLtTjLtxdx5uvQ3HyViOshfxCHLZOoJ0omBHtInpmYNH4G9NZD+yn+d4uXtkZt1mNsHd257NPfYkSeEUYF7a5sQ03+O7u2vg7gvYdUzwlCGuXw+cN1xbd7+g+m6LHCAsgCCoRLkq3Cm1bgec7MQpWBCABYT1DRz89osJgoDV3/9/lDra8KgMUYxlk8HLwEEXwMw5pzFj1iksuvuLOE6ht40wTK6dPP1YOtuexixDy8R59HRvpdDbhsfJZtKHH/1q2tuepnnCwWzZ+GCanxVX+mgWEgQZonIRzFj9xB9w98qx0DIYAZGXyViejOXTPCsntCz5MAsY3eU2QsuwsmMhqzsfYnrdPLYX15EN6inG3YRk6Inace9foVg/YFoyFzRQjLuJ06nbkvcmXSROpxo3MTGYTkZ1vEQOVL0kQaFbGVxU/l+qaVxtOYnvkSSzL6E/t8uB3Q68RKR2up96gvZHFgMMqtNV7uqgMsrwmJZjT6X9kcXEUZmVX/scQSaJkoX1DcS9PZWfClGhwF1/+k/cYyZPOYJyuYfjnnshQZBh/pF/y2NLf0QQZslk6zn1rA8SBEGlPETbjlXUNUxNph+BlomH8Nc7v0Cp2EkQ5pLIXDogS1hST8yMMJOjWOiolJ/I5prJU8Y9Tqc/DfeYnNVRiLowCzh50nl0lVt5rH0BALFHBBYSeZHNvavIBMmCgkm5WXSVW4nipF8Zy6XbAyUV8VuyU1nf+zieruwMCIEQx6nP9O9V2RpvZqrPGtG/P5H9wn4e8Ur9Jn08K9VGvE4FjnUVrhEZtzKNzZQ704W/7hz2no/Ss/4p1v/6B9DozPm7d5OfMh2A7rWr6F69AswIsrm0aGoDdbMOobhtE3GpiMVxWsE+pqszSansK3D65OO/IZdvxh1OP+fySh/6ykOUil1pdfqkMGrrjicryf9xVKQ/QdYBqxRRJR68J+QpZ3yARfd+CUgLvRLQGyXnk42rk5DVw21/IrCQMMjhcZFMkGV2/bGs7VlG5GUag0mcOvm1BEHAwztuZ31PUiPMMHJWz/Omnc/Wnqd4sPWWJFfMAkKCpG+WRNmMgAnZaeworyO07DP2cBSRA4O7X7837atd1fgwcNDevJGIjK7c5Gk0HfGcymrGJ776Gdb9Kkkqx6wy6AIotbUmU5NpJCysb0wS6NevIS70YmGGTFMLLRMO5ujj38z8I19RaXvPn/+r8nzgoKvPaWdfThAm03BBmCOKShR72wiCEAsyBGGOMJMnzOQJwjz1jVPTjW+dOC5VNtGeMPlQgkyOk8/4AOW4QCHq4tiWF1beJ/aYukySW+YDds6tzzSTDeqY33QiuaCefNjI9LpDAVjd+SA7SuvJhfUEFpIN6uiJO7hl/VdYvOO3ab4YTMhOZ2r+YELLEHtEPmjAiWktbUpWdlKmM27d278ykf2LA261eYwhM3vSzFbt/Ki2fbURr6nAI2b2V5LlkwBUWx5fRGqj8ZAjsEyWnqdXEfWk02lNLRx20RWDrjNLEuzD+kbiYoFyVyeZxqY0+d4J83VMOeNcjiyfVGkThnU8tuxnROUCQZChrn7SkH0oF7vJZHLEQYhZQFQuYBbSPGEuHW1PUyx0kM01UY67CIIMpUIH+bpmCr1txHFEudTD9INO5LCjXwWQ5Hh5Mi25eMevqQ9biCmTt0a6olYyQZ7QQrrL7QQEZIM8BzccTy7sr8e1qnMRT3f3L34OLcOLZl7IXZt/SCFOfqQ5MaHlyIX1nDb1dQD8eeN3Km2m5g9OSkoUuil4D9PC/npiInJAOXXA8zrgjUDV9WWqHXh9cg86JCJjpNS2g1mvfBOdTz7Gul9+r7K9T++WDXQ9+RjFbVtoX/4AQb4uiYwFAWGYloeIY+a84Z2s/82P8Thi6z23cejJR9PbvYPHlt1IVO6lVOhM85+cE0/7pyH78OjDPwMgCMJ06vHqpPxDuVDZZsc9Jkj3VczXTcLMOOSwl7Fm5R8BZ/vWx5gfv4IgyBAEAY2ZSXSVdwBG5CWKcQ8FkoGlecCsxqN4qushABrDSRzSdAIAxai7sjKxz0F1h3NY02l0FLcRE5MLGihEXeTDRopxN+W4xO0bv00+aKCY1gULLUtbaTNNmcmElqHZJtEQNI30X5/IPu9ASEhy9207HfpfM1sAfKKa9tWWk/jL7s6b2T3u/vxq7iUioyesT6I8TfOPYv4/XM7TP/46AOt+nqQk9A184kIvc17/TupnHcy6m2+g84llAKz/1Q+xMKTclSzUuffPnwMDjyPCTF2aixWl1emHVi4nqwBnzO77pdAxoLd7O1NnHMeGp+8lk62nXC4QhlnKpU6mTD+GOfPOYdP6hZUcr758svsXXIV5mVzQQOzlJP/KMpUc3tgjNvY8kXx+y9IV9e8eZhbgHmEWMDk3m3lNJ7K9sJ613ctY0/0gSVK/UZdpBpxsUEcpTvrfG3cmWwh5sj1QHEfsKK5nok8hsoELA0TkQGJmzx3wMiCJgDXv4vJnGKk9L+pG6D4isheCXP8/xdyESTQddgydKx+lL4m96fCj6XjsYYJMhvpZB9O9bjWdKx8BMywIsSAkrG8EoNzRng5aQtydTKaOKdOPZePavxJHJe5fcBWnnHkJTz5+C9u3Plp533KpFwsC1q+5i7WrF5DNJn069sS3USp1sW3zMqJygZlzTmfrpqWYGUcf/2ZWPposEspk+3eZWHT3l4jjiBCn7AXAMQ9oykzmtKmv445N36fgXRTjbnJBQ5J/5RG3b/w2mSBHQEhMROQlthfXsX37OgAK6RZE+bBx0ObagYUYQVLfCycIQgILOW7Ci1nb/ShmRnvvRgIP2Fpex9TM7FH6mxTZRx0AES8Gb1NYBp4E3lRt45EaeB0YX7XIOGZhBo8H7+Q14yWvZcZLXlt5vfLaK7EwhCBg0x9/QeeqR8E9iYS5gyXRsLhYAIN83cRKBXuAQw57KZvWLyYq9dDTvY27//Sf5OtaBr1nJltHsdBRqdMVhhlOPPUi6homsXXLtkpEa8PT91TadLStpXVHkpva3DKXrs4N6XXpykfPkrF8Wty0SK91cefmG4jSrXzyQQMvmPEO7tj0PYpRsi9raFkCy4AXsXT1Y9bqKnW5AGbWHfmM7zEfNqTJ+kbsJULLMiF7EBMmHMRdW38IHhEBEYp6iRyg3u3ug5LpzWx+tY2rXdUoIuOcR2WC3K6LerYuvZ9yZztRVwfEcTLogmRT7LSivfeVkCj3DypOPuMDleeFnh1kc01YEOIeE0VFerq3M2HSoZxy5mXpno3JVj9BEJLJ1OPubFy/iM6ODaxYdlO68XZIEOYIwjy5fDOPLv0xvd3biOOIKTOOo7dnB3Eck8nWY0FIS2YqANkgWY3Yp+zJlGccx9y5+QbMgiRqZUZDZiLzGk/k7Glv48UHvYtzpr+dM6a9gXOmv53JuTnkw0Y29z5zIdL8xpMrz40kgvanTdclg65UUzCJuK/4q4iMO2Y218xuN7PlZrbMzC5Jj59kZvea2RIzW2hmpw9o81Eze8LMHjOzv9nN7X9W5bEhjVTEa8x3rBQRKO3YClCJNgVBhnJ3F2u+n9TCCrI54lJxUJvD3/uxpNq9O9Ne9Le0HHUCT3z1M3gUceoZlyYrD4vduEds2fQQxULfLhlJwdN83QTadqxi0d1fpK5hCocf/RomTT2C3p5WHlr4TaKoyNNP/oVN6x8gjoqYGZlsA6eng7S+oqsOFHrbeOKRn6e5WTHuMWe88N9oXLYeSKYDS3GJ0DOYBdSFjXSX23Hrj/Ql+V9OT9TGrIZjyASDf8yV4zLbi2vJWI4weOaPwGSD7CTi9cLpF/Lnzd8GvFKUdWIwHTNjQjBlr/6uRPZLY1zqYYAycLm7LzazZmBRWmn+88Cn3P13ZnZe+vpFZnYs8BaSza9nAX80syPdvfLDxcyOTs9PMLPzB7xXC3uQclVt5fpGoMfdYzM7Ejga+J2792XYagsfkXGg3NPFymv/m4Gz/31FVcOGJurnzGfO6y98Rru6GXPo3bSW3o1r2Xbv7ZVSFI8s+QHHPffv06k32LLxIcxCzJwwk0u3+emPQPV2b+OJR28G4PBjXo+ZUS4lex9GadJ9Nt+MkQy4pkw7ltPOvpw4LvPXO79AOa3HFYRZMpl6zIxFd3+RF0x4M8W4t5KbVYoL5MJ6wAjJ4u40Z6Zw3MSXkgkylU2x79n640oO1+Pt97Kpd2X/9+JFjm95aeV1FJcpe4GH224j8jKhZQdFucpeJGf1lanXhmDwFKuIjB/uvgHYkD7vMLPlwGySH459/3gnAOvT568FfpTuQ/2kmT0BnA7cM+C2RwGvAiYCrx5wvINkD+qqVBvxugM4x8wmAbcBC4E3A29PP9TDu2krIjXQu2Uj5Y5WguzQFdUtCJLcrSH0RcG6n36SuNADnhxr3bGKe/9yJblcYyU3y+MyBmSyDZVB1ylnXkbbjlU8sfyXlXs+suS7ZHKNydQkRhBmaJl4CL29bRR7WwHYtuURDj3qlQRBhjNeeEUl+nXyGR8gjos8+NdkVWYx7uW+rTeSDxuJvUxjOIlTp76GOzf/ACzJT2srbaJv78cTJr6Uh1r/CMCS7bfQG3VQ8sGfPRc2MKVuTuV1shl2gZiY2GMi7yHyEvmwkULURTjgx6VqeIkMzcZhxreZzQNOBu4DLgVuMbMvkKRbnZleNhu4d0CztemxCnf/JfBLM3u+uw8ckO2RanO8zN27gfOBL7n764Fjn+2bisjIK27dSFzopbhjG3G5jMdxsk9j0P/PvNS2neKOLc9oO+WMFwHQu2kt5c72ZGPrIMDTgqZxHCd5W2F/DtmESYdUni+6+4tMmnI4p519OYcd/ZpK2YpysYszXnhFJYesvXUNxd5WTj7j4krb+xdclU6N9mtvfZJMkMM9plwucM/mn1bueda0t3Pq1L7azU4mqMOJKcUF7tryI+7cfAP5oJFJuVnEHtNV3kFneTuFqAt35+jmc8iHjZWE+z4RSQC/byWkpT8eT5r4Cl5y0D8xKT+bxsxkjs2dwbRQqxlFxtjUNEer73HRUBeZWRNwI3Cpu7cD7wMuc/e5wGXAdX2XDtF8V8PIB8zsYjP7ipl9q+9RbcerHniZ2fNJIlx9G0OOVH6YiIyAhoMPB5KK9F4qYkG6JVAck2lqodzZTqm9lZVfu5IVX/4MnU8+1t92zqGUO9sxM4JcHsvkyDQlA60wk6dcSqb4Tnn++8nmmsjmmjj6+DcPev++aNXkqUdw6vP/hWyuiVy+mTiOOe3syzn40HMr1z5w75fJ5SdWXj++7KeD7hWGeR59+Gf09rZRKnbSE7fTEyXlLXbO2QotpCk7BbBKDa77t/+SLb1rKMU9FNINsQGOaDmdR9vvrFTCH6hvIFb2AhnLElhAPmzkwdZbWLDlB7SXNpMx/dgT2SWv4QO2uvupAx7X7twdM8uSDLpucPeb0sMXAn3Pf0oynQhJhGtgKHsO/dOQO/seyTaKfwP8Jb22YxfXPkO1A69LgY8CP3f3ZWZ2KHB7tW8iIqMv09hEtmUSYWMzYX0Dh110Rfq8kXJnO5mmlspqRfeITbf+PEmqB+K4jKXThrNfdwGZxiaCTJZsto4wyAL9m1ebWSXP6bSzL6exaWalDw8vTgq1BplcUlMrjln1+G8BmDHrZE4585LKtcVCK4ce+bcUC51s27yc+xdcRbncS7HQwaNLf0xX5waCIAMYAUnfSnGROzffQKHcP5gCOHPam8iH9WlifKIQd1L2YqVqfT5sADcKcRfluMAhDSfs9A0mnymZZuwfmPmAX3o7StsoRL2V6JuIjE+W/JC6Dlju7lcPOLUe6Nv09VxgRfr8ZuAtZpZPS0McAfx1F7c/3N3/HehKN8z+W+D4avu2J5Xr/5Im2ZPWr/iXat9kPJiU7ebvDlo01t2gIRg6x2YsdEytH/6iGnhk1viYttlSGD9bwKzv3vPE7Y7lPWSbG+hcvY3i9i5WXfcfZOoDyp0FMs0hh7zxKNb9ZmDF+eT5mhv+E2In05isejziXRlmvewVPPjxX1HMZYi7e3GDsLGBux66qpKWuvqtyZ8Nb30bOz6aRLuKbOWhyXfS8jfn0Ht/Ee8tsKF1CZseeoyZn/oAQS7HlLdexoZ/+2LS50uOJvrnZBBTbIGorQQh0BKCgUWNhGEAJYi7u4niiGJzlgX+ayhBlElqdt1W/DFRJol2BQ0NlDs7K58yc8YJlB5/lCLwxEGbiAsZ8JgV+eW0vfp46ucdSseDiyn+ISTuDggyyf6V1jKBmZd/lK2//zXFDesp7dhO1NHOXdlbaTrsaCaf/qJBG4/X2oTV46OcxYRH2oa/qEasvXv4i2rAt20f6y6MkbHfwHqAs0gW/i01syXpsY+RJMFfY2YZoBe4CCANKv0EeIRkReTFA1c07qTvB2mrmR0HbATmVduxalc1Pp9k5NgEHGxmJwLvcfd/rvaNRGR0da3ZTmFbJ5mGHL0b2imVusnPaMajGI9iVv9wIdmWZMXzmddfyOYFK3niGwuSxoER9ZaIekvcfeH1nHHdBWQachTbYoKGeuKeXsgkUaeorYOwZfAgdfbnLmddOvhq+8MCOv9yP0E+R9RbIMgneWEb/uNL1D/3OfQsXkbc0YXV5YjjmHBCstNG4/NOpHvRw8S9RaZ94AIyM6dVBmiTz305O26/FQAvlbBsdtD7e7lM0NhE3N2NWwDlMmSzBLk8PY8tJ+pMonU9He1YPl+J/G268ceYGVFXJ8QxQWMTk174Erbf+juizg5W/89nk4KzA4R1yS8spfYdYzrwEpFdc/cF7LrU1Sm7aPNZ4LNV3P7adLHhx0kiZU3Av1fbt2oTFv6XZC7z5rRzD5rZC6p9ExEZfYVtSZSnuL0bC4ywIQcxHHP5S3ns//5MpjFHcXsX2UnJdNz0sw9j+tmHEccxT9+0hKd+upggl/xIuPfd3wOg5VUvo/3XtxPU19H0gtPovON+AKL2TrZ+5xdMfMNLyTQng7CDPnExay/9L4giPFcgnNDMxDf8DU0vfh4b/u2LxB1ddN5+L+GE5qRQa3cva//5UxAYQUsTE1/3Uia+7qU7fyyAyqALwLJZspMmM/0Nb4ZMhtY7bmfSi19GmM8TF4us/twnky2QLCBsSKceLSBoaCDu6sQLBeb926d5+v++gBeLWD4PcQxBUBmExcVCMlXa3UXY3ILHUbKdUvocqGytJCID7Oez8GYWAO3uvoOk4sOhe3qPqivXu/vTOx3aVQhORMZA07ykoGe5s4AHRrm7SKmtmye+cRdxqVyZASjtGDwdEwQBh/zdcznnx//Ic//n9YPOtf/6drJzDgKg8477mfGx9wBGUJ+n8NhKNv3X1+la9DA9y59g46e/TJBNcrIAwpZmml78PIIgYOZnL8PjGAPyRxyCZdLf+dJcqYYTjhryM+UOPZioo4u4WGD2Re+vHC/t2E6Qy5NpaGTqK15FmEbVtv7uZqyunrClhXlXfIJDPngFh3zwCg79xGeom3sIQX0DYWMTQSaTDP6KBcrtbXgUQRwTl0p0LL6fTMuEynvNef8HK/lvAFPPfsWgvovIgcPdY+D9w164G9UOvJ42szMBN7OcmX0IWL43bywiI6tvGtFCwwtlvBwTFcqU2nvINNcl29+UIjLNuy6wXH/QBM68/kJO//JbAHB3ik8+TXlHO3GhyOYrryU3ZwZeKOHFEnFvgW3X/oQt//d9vFQmaG4kM20S4YRmovYOik88BSSDu7qjDiWY0ExhxRpmf+EjtLz0TOpPeQ7hhGYKq9YO2Z9o63aIY7xQYN21/y85luZvPf2V/x107eqrPkf7/fcRd3fhxSJbfvXzQecL657GMhnycw4GYO4HLseyOSzMVKYTg9xONdDMeOrqKysvD/ngFTQcnP6Cq4GXyDPVblXjWLrVzD6Ubks0ue9RbeNqpxrfC1xDUkxsLfAH4OLdthCRmpt0wmw2/ulxLAwI8xkwyE5qoLSjm9zkRoJsSJANh71PpilPpqWO7kc3J/lU5TLeW8AzIVFHF0FzI1FbB14oQuxYXQ7vLWDZDA2nHkf3woeJ2jrY/L/fqeRwNTz3OZQ2pjXESmUmnv9yuu5/iOKTa4m7hk6KnvYvF7Duss8RRzFWLBDk8oSNjUQd7ZDJEscxW37xM3pXrwJ3LJPBy2UyEyZSWPsUq6/6HAd/4PJBA6qD3vIOAMJ8nqCuDtyJi0WCXJ65l36EIK171nrf3Wz//a/xQi/kcsz9lw8lN0inGj0eH8ntIlJz70r/HDgOcqqcdqwq4uXuW9397e4+w92nu/s73H3bHnZUREbRzJcnNY0tY4R1WTJNeXKTGyuDrlJrsgKw1NZTaVMultmxdP0zCph2r2ule/U2LJckseePOpTGM06i6cVnMPPj7yNqS0vWhCFWn09yqpqSfKruhf0bWQwsu9C9eFml3YbPfBWAxtN2Lukw2MbPfBUyIUGaKD/9ze+AtJQF5RKr/+s/6Fq6JN14OyDT3EJ28hQyk6fi7sSdHaz+3CdZ+R9XEHV1PqMMRFjfgANxbw/uEU//7+cr5+oPnp+8VxAy8ewXEqTToz3r1iRv39W+276LHJAOgIiXu88f4lF1rle1qxqPBL4KzHD348zsBOA17v6ZZ9lvERlhE4+fxcTjZ7Ft0VOYGVPPOoxt9z0JQHF7F5mmOsqdvYQNOR644hf0bOgvA1DuKpKpz0JgleuzExuItvcSTmwm2t7KQR9+N0D/SsTYsWwmyY/qE8V4YMTtnXixhOWyhJMngscUV6+DKK4MvtZe9rlkZWNnN0FTA3F3L0FD/zTojhtvASCc0IyVk35t/vH3OeSDV7Dj7gW03fUX4u6ksKtlshxyyYdYk04LTnrBi+hYdD8dDy6GOPlJ7aUSQV09PU+tJj/nYDoXLyTq6Sbu7AAz4q7kXmuuvpI5l3yYjT/6LmFTEq2bcPrzK/3q3ZzUVExybEXkQGNmDcAHgYPd/SIzOwI4yt1/XU37an9yfIOkgGoJwN0fItnFW0TGmeM//komnTSHbGOOYy47Nykn4c6h734+HjuFLZ10rOzfNqjcWaDU1kPPxv4IjsdOYWsnU//l7yvH1n30KtpvuydZodjTi0dlZn3mUqa+p/9HQdzVTdye5GD15U1F21uZ+g9/l1SGDwPCpmQ1oGVC4o4uPIqIewqDBl0AvQ+vqDyfecE/4HFE1NHO6v/5LDtu/S0WJqsMw+YWDrnkQ2m/Y6KOdjbecD29T68hqE9r1ZklWyfFEZt++kOe/M+Ps+VXNxH39iZ5XmkULWxqwuOY1f/5ceJisn/lhOc9f1C/Jp1yNgCZ5gmIyABOUserFo+x9W2gSP8+j2uBqgNR1Q68Gtx95wquz9xzQ0TGBY9iNv7pMZZ/8U9YGIAbq751T/KD0Yy4twSe1PPKNOUJ6zJkGnOc/IXzk/blGAuM7d/8SRLFcidq76I1jUJ5sUTc3cvWb/yEzj/fx+zPXU5QXzdoKm/W/3ykkt+16X++Cbkslskw+/Mf5uCvfJLZ//MRLJtJtynKEpcH/0iZ8eF/rDzPTZuBpwOhvppcUUcHmQkTmf2P76tc13zKacnP/qj/XkE+R5DL0XzSKeRmzCTu7MDM8CjCS0UO+dDHOPQ//otD/+O/aDzhuURtbXi5TNzTzYQzz2HiWS9kkL7PqOR6kQPVYe7+efqDUT3sumbYM1Q78NpqZoeRzqya2d8BG/awoyJSA7nJDbQ/vrnyOshnyU6sJy6UyU9rItOQJTe5EQzuvuA7QDqGcFh82c8AqDuoBQssSawPA8wBH5wHFrY0UViVVJkprtvEzE9czKQ3vZJwQjNBQx1tv7iNumMOSwZtHV3EnV1JyYYBA6w5X/wYQUsThAHtv/7zTh9kcCbElJefl0S4mpoJ8nUEjY2U21rZ+vvfsObqK1lz9ZW033s3RrKt0dxLP5L8xApCZrzjXeTnHsKkc1+W3KOxieykKYTNLZXE+zVXX0nX0iWETY0E2SyZ5hYmnnHWM77fvuKrcbF3z/5iRGR/UTSzevrHRIcBVW9LU+2qxouBa4GjzWwd8CTJhtkiMs7UHzSBQ//+eWy49VFykxvIT2qgsK2Lng1tNMyeyBHvewF/fd8PASi2JqsJw/oscW8Jjx0L4ah/eTFTTjmY5Q/Usel/rsMNgro8ls8x+3OXU966g7Zf307vY6sB6Lj1Lqa88/ykOGo5Iu7upWfJI1g+lwza0t8FLZ9jw79fw+zPXf6MfucPP2TQ6yCTqeSDrbn6ykoUKmxsgnSwFHW00738YcLmZB+jIJcjKhYImpqTRPk08rX1l8mAsu8eQX09lsniHrPhhu9Q3LSxvx9zDqG4Kfm9sv3+e2k57YxB/Sru2JL+uZXGeUfu+V+QyH7MDoxA8H8AvwfmmtkNJNsTvbPaxsNGvMwsBN7n7i8FpgFHu/vZ7r7m2fVXREbbjBcdyaQTZ2NAcUdSyb6vKv2Kr97BmddfOOj6ZNAF8//+DM68/kKmnJLUuspMnli5xovJ9mTbvnMTpc3Joua6o+bh5SS5vufhx+l58FHqjp6fTCHm0xIOfZXp3/zKyirJuFhkx09/z5Yvfa9y//rjjhjUp+K6Tf2FVqGymrEvmT8uFolLSZ8sl2fu+y+j/tDDaDruxMqAy3J5MpOmEHV1EXW0E/ckA82oq5vSjh2Ut2+n96n+H2Uz3vg2Mi39+2T2rn1q8OIBID91RvrnQUN88yKyv3P3W4HzSQZbPwROdfc/V9t+2IFXuknkKenzLnfveFY9FZGamnLa4AjS7FcdV3nesXILZ15/IROOm5XU98pnsQBWf/8+Clv7N5h2d+qOmJckn5sRptsDdf/1oco1cWeyGrCvjISFIXP+99+oO2o+dUfNxzJJHlfnn+4jausgautgwyf+j+7Fyyiu6480DXzPwqqn6VnyCEFjPeGEZmb/4/uY/JKXEzQ09e/T6HFSZqKunrrZs9n6m18mxwNj0oteRv38Q2k8+hhmv+s9hI2NybRiQ2My1WlUBmdRdxcz3nIBh3zwCnIHzcTLJernH0p22jQAips27jT4svRzVjthIHIAOQDKSaReCLwEeDFwzp40rPYnxwNmdjPwU6Cr76C737QnbyYitdOYbiHUZ8KxM9nx4Dri3hJrf/Fgcs3Bk6mb2kTsTuuD67DAWHX9vYQNOaLuIm2dDRAYdUfNZ/Lfvw4LArZ9Z/A/+3BiCzszM3Lz5lBcvbaSEwVJontcKCbRKzMmv+uNdN25EAsCtt9wM14aes3O9tuSpP6Gww+vHIs6Oyls3kTd3IMHXTv99W8iLpUorEuq5m+9pX+Fd5DNkp0wkairi6C5BY8iglyWLTffSH7G4AhW4+FHU9i4jrb77hp0PCj2PVE5CZEDkZl9BTicJNoF8B4ze6m7V1VYvtqB12RgG3DugGMO7HbgZWZzge8CBwExcK27X2NmJwFfA+pIVkf+8xCrJjGzV5BUzA+Bb7r7lenxycCPgXnAauBN6YaVIpIyM/LTmils6WDe208jP7mRoy5+Icuv+iNNh00jrMtiYUCpoxcvRUlUK3ZajplJmAsptvbQtiwptjr5Ha/B0oHGlHeez7bv3ERm+hTKm7eRmzebpnNOZfv3fknQUE/dUfMBaH7R6bifRtd9DxJtayWclJRfiHYkeyNOePW5mBmFh1eQmTY5qfuVzUAYUnj8SZpeeDoNzzuR3mUrYHMvWFIgNeruIjNxEtnJU5JcrbRsxZSXnUfYlETkgmyWqa96PVt//XMsCLBMhoYjjiYzaRLt999H02HJAM7LZXqeWkPjMc+hvH0bmZYJeBQx+aWvADN2/OlWyh3t4DH18w4l6ukh7HFKbdupmzGrpn+fIjJuvBA4ztNl3GZ2PbC02sa2cyXnkWRmM4GZ7r7YzJqBRcDrgP8FvujuvzOz84CPuPuLdmobAo8DLyOpkXE/8FZ3f8TMPg9sd/crzewKYJK7/+vu+jL/+Cb/5E27r5JdCw1B1QsfRl1HVD/WXQDgkZ7ZY90FALYUmsa6CxXru58ZRRoLK9aMjzym7Ibc8BfVSHacFKyfsHp8bFk04ZG24S+qEWsfeuupWvNt28e6CwDc0v7tRe5+aq3eL3/wXJ/14Utr8l6r/+VDNf1sA5nZTcBlfbnuZnYIcKW7v7Wa9tVWrv+/IQ63AQvd/Ze7aufuG0jLTrh7h5ktJ9nv0YG+/2eZAKwfovnpwBPuvirtw4+A1wKPpH++KL3ueuDPwG4HXiIiIjK6DpBVjVOA5WbWN1N3GnBPmpKFu79md42rnWqsA44myfECeAOwDHi3mb3Y3S8d7gZmNg84GbgPuBS4xcy+QJLgf+YQTWYDTw94vRZ4Xvp8Rjqow903mNn0Kj+HiIiIyN74xN40rnbgdThwrruXAczsq8AfSKYBh53XNLMm4EbgUndvN7PPkITpbjSzNwHXAS/dudkQt9qjsbSZXQRcBDBl1viZqhAREdkvjf12PqPO3f8CYGYtDBhHuXtVc8zVLsuZDTQOeN0IzEpLTew2acnMsiSDrhsGrIK8kP7E/J+STCvubC0wd8DrOfRPSW5K88f68sg2MwR3v9bdT3X3U5snZ3fXTREREZFhmdlFZrYJeAhYSJK/vrDa9tVGvD4PLDGzP5NEol4A/JeZNQJ/3E3njCSatdzdrx5waj3JqoA/k6yUXPHM1twPHGFm84F1JJtyvy09dzPJ4O3K9M9d5pmJiIhIDYyfGluj7cPAc9x967NpXNXAy92vM7PfkkSmDPiYu/dFnz68m6ZnARcAS81sSXrsY8A/AdeYWQboJZ0ONLNZJGUjznP3spm9H7iFpJzEt9x9WXqPK4GfmNm7gaeAN1b1aUVERET2zkrgWS+hrXZVo5FUaD3U3T9tZgeb2elD1d4ayN0XsOsdu08Z4vr1wHkDXv8W+O0Q121L+yMiIiLjxYER8foocLeZ3ceAdCt3/5dqGlc71fgVkgKo5wKfBjpI8rZO26OuioiIiOzbvg78iWRx4R4X1Kt24PU8d3+umT0A4O47zEzLBEVERKTiAKnjVXb3Dz7bxtWuaiylleT7yuNP41mM8kRERET2cbenKxtnmtnkvke1jauNeP0f8HNgupl9Fvg74OPPorMiIiKyvzowIl59FRY+OuCYA4dW07jaVY03mNkikoR2A17n7sv3pJciIiIi+zp3n7837Xc78NopdLYZ+OHAc9VWaRURERHZH5hZA/BB4GB3v8jMjgCOcvdfV9N+uIjXIpLwmQEHAzvS5xNJ6mft1ahPRERE9iMHxlTjt0nGR337TK8l2YWnqoHXbpPr3X2+ux9KUsT01e4+1d2nAK+if8sfERERkQPFYe7+eaAE4O497Lpm6TNUu6rxtLSYKemb/I5kyx8RERERzGv3GGNFM6unv9LDYQyzb/VA1a5q3GpmHwe+n77RO4Bte9hRERERkX3dJ4HfA3PN7AaS7RH/odrG1Q683gr8B0lJCQfuSI+JiIiIJLzqGbd9lrv/Ia30cAbJFOMle7JhdrXlJLYDlzy7LoqIiIjsH8zsNnd/CfCbIY4Na7c5Xmb2ySo6MOw1IiIicgDwGj3GgJnVpWW2pprZpAFV6+cBs6q9z3ARr380s/bd9QN4C8l8p4iIiMj+6j3ApSSDrEX0r2RsB75c7U2GG3h9A2iu4ppxL0PM5LBzrLvB9LBjrLtQEWXGx1x8aONj288nghlj3YWKbBCNdRcAaDmi6oU6o6p8WLULsEff6tZJY90FADbMmTDWXQCgY/b4+D4AmtaPj+8k03PQWHch8fPav+U4WHE4atz9GuAaM/uAu3/p2d5ntwMvd//Us72xiIiIyP5mbwZdUP2qRhEREZHd248jXiNl/MTvRURERPZzGniJiIjI3jtAKtdb4h1m9on09cFmdnq17asaeJnZkWZ2m5k9nL4+Ia1kLyIiInIg+QrwfPoLyXewB6saq414fQP4KP0bQj5EUkZCREREJLEf1/Ea4HnufjHQC+DuO4BctY2rHXg1uPtfdzpWrvZNRERERPYTJTML6d8kexpQdV2kagdeW9Pdt/ve5O+ADXvYUREREZF93f+RVEmbbmafBRYA/1Vt42rLSVwMXAscbWbrgCeBd+xhR0VERGR/NvbTgKPKzAKSMdBHgJeQVK9/nbsvr/Ye1W6SvQp4qZk1AoG7j5/y6yIiIiI14O6xmV3l7s8HHn0299jtwMvMPriL430duPrZvKmIiIjsf8a61EON/MHM3gDc5O57/ImHi3j17dN4FHAacHP6+tXAHXv6ZiIiIiL7uA8CjUDZzHpJphvd3VuqaVzVXo1m9gfguX1TjGb2SeCne9FpERERkX2OuzcPf9WuVbuq8WCgOOB1EZi3N28sIiIisq8xs9uqObYr1a5q/B7wVzP7OcmahdcD3632TUREROQAsB/neJlZHdAATDWzSSRTjAAtwKxq71NVxMvdPwv8A7ADaAX+wd2HrVlhZnPN7HYzW25my8zskvT4j81sSfpYbWZLhmh71IBrlphZu5ldmp77pJmtG3DuvGo/sIiIiMiz8B5gEXA0sDh9vgj4JXuwZVBVES8zOxjYSlIwrHLM3Z8apmkZuNzdF5tZM7DIzG519zcPuM9VQNvODd39MeCk9JoQWDfw/YEvuvsXqum/iIiIjLJxsIH1aHL3a4BrzOwD7v6lZ3ufaqcaf0N/ALEemA88BjxnmE5uIK1w7+4dZrYcmA08AskO38CbgHOHef+XACvdfU2V/RUREREZDd8ys48DB7v7RWZ2BHCUu/+6msbVTjUe7+4npI8jgNNJSuRXzczmAScD9w04fA6wyd1XDNP8LcAPdzr2fjN7yMy+lc61ioiIyFg6MDbJ/hbJIsMz09drgc9U27jaVY2DuPtikrpeVTGzJuBG4FJ3bx9w6q08c0C1c9sc8BoGl6/4KnAYyVTkBuCqXbS9yMwWmtnCtu3a01tERET22mHu/nmgBODuPfQn2g+r2hyvgRXsA+C5wJYq22ZJBl03uPtNA45ngPOBU4a5xSuBxe6+qe/AwOdm9g1gyPCeu19LssckRxzfMPZjZBERkf3ZgfH/tEUzqyf9tGZ2GFCotnG1OV4Di4WVSXK+bhyuUZrDdR2wfIjthV4KPOrua4e5zTOiYmY2M80fg6S0xcPD9UVERERkBPwH8HtgrpndAJwFvLPaxtUOvB5x90GV6s3sjQxfvf4s4AJg6YCSER9z998yRN6Wmc0Cvunu56WvG4CXkSzhHOjzZnYSyWhz9RDnRUREpIaM/XtVYx93v9XMFgNnkHzsS9x9a7Xtqx14fZRnDrKGOrZz5xawi3lPd3/nEMfWA+cNeN0NTBniuguG7bGIiIjI6JgNhCTjqBeYGQPTqXZntwMvM3slyUBotpn934BTLSRTjiIiIiIHDDP7FnACsAyI08MO7P3AC1gPLCRZVbhowPEO4LI96qmIiIjs3w6AqUbgDHc/9tk23u3Ay90fBB40sxvcXREuEREROdDdY2bHuvsjz6bxcFONP3H3NwEPmD0zZc7dT3g2byoiIiL7mf18y6ABricZfG0kKSNhgFc7JhpuqvGS9M9XPfv+iYiIiOw3vkVasYH+HK+qDTfV2Fcr65/d/V8HnjOz/wb+9ZmtRERE5IB0YES8nnL3m59t42q3DHrZEMde+WzfVERERGQf9aiZ/cDM3mpm5/c9qm08XI7X+4B/Bg41s4cGnGoG7np2/RUREZH90oER8aonye16+YBjI1ZO4gfA74DPAVcMON7h7tv3oJMiIiIiNWFmc4HvAgeR5GFd6+7XmNmPgaPSyyYCre5+kpnNA5YDj6Xn7nX39w51b3f/h73p23A5Xm1AG8l+iZjZdKAOaDKzJnd/am/eXERERPYf42hVYxm43N0Xm1kzsMjMbnX3N/ddYGZXkYxx+qx095NGu2NV5XiZ2avNbAXwJPAXkv0RfzeK/RIRERF5Vtx9g7svTp93kESzZvedNzMD3sROe0bXQrXJ9Z8h2QzycXefD7wE5XiJiIjIQF6jxx5IpxFPBu4bcPgcYJO7rxhwbL6ZPWBmfzGzc/bsXapX7cCr5O7bgMDMAne/HThptDolIiIishtTzWzhgMdFQ11kZk3AjcCl7t4+4NRbGRzt2gAc7O4nAx8EfmBmLUPc72gze0l634HHX1Ftx4dLru/Tmr7JHcANZrYZbZItIiIifZ5FNGovbHX3U3d3gZllSQZdN7j7TQOOZ4DzgVP6jrl7gWSlIu6+yMxWAkeS7Ffd1+5fgItJpi2vM7NL3P2X6en/An5fTcerHXi9Fugl2Rj77cAE4NNVth0X6qzM0bmtY90NsuNore0el9sdJWFuw/AXHWCaw96x7gIAHfm6se4CAKGNl/9aYUZdx1h3AYAHwtnDX1QD7QeNj/9GADa0jo++WKHayaRR9vOx7sDYSXO4rgOWu/vVO51+KfCou68dcP00YLu7R2Z2KHAEsGqndv8EnOLunen05c/MbJ67X0OybVBVqhp4uXvXgJfXV3tzEREROXCMo1WNZ5Fu62NmS9JjH3P33wJv4ZlJ9S8APm1mZSAC3jtE2azQ3TsB3H21mb2IZPB1CCM18DKzDoYOHPZtCPmM+U8RERGRseTuC9jFYMjd3znEsRtJpiV3Z6OZneTuS9I2nWb2KpK9G4+vtm/D1fFqrvZGIiIiIvuxv2en/HZ3LwN/b2Zfr/Ym1eZ4iYiIiOze+JlqHHEDc8KGOFd1ia1xkgEoIiIisv9TxEtERERGxDhKrh+3FPESERERqRFFvERERGRkKOI1LEW8RERERGpEES8RERHZe7XdMmifpYiXiIiISI0o4iUiIiJ7zdiDfXMOYIp4iYiIiNSIIl4iIiIyMpTjNSxFvERERERqZFQjXmY2F/gucBAQA9e6+zVm9mPgqPSyiUCru580RPvVQAcQAWV3PzU9Phn4MTAPWA28yd13jOJHERERkWGocv3wRnuqsQxc7u6LzawZWGRmt7r7m/suMLOrgLbd3OPF7r51p2NXALe5+5VmdkX6+l9HuvMiIiIiI2lUpxrdfYO7L06fdwDLgdl9583MgDcBP9zDW78WuD59fj3wur3urIiIiOwdr9FjH1azHC8zmwecDNw34PA5wCZ3X7GLZg78wcwWmdlFA47PcPcNkAzugOmj0GURERGREVWTVY1m1gTcCFzq7u0DTr2V3Ue7znL39WY2HbjVzB519zv24H0vAi4CmDU7fBY9FxERERk5ox7xMrMsyaDrBne/acDxDHA+SZL8kNx9ffrnZuDnwOnpqU1mNjO9z0xg8y7aX+vup7r7qZMnawGniIjIqNJU47BGdTSS5nBdByx396t3Ov1S4FF3X7uLto1pQj5m1gi8HHg4PX0zcGH6/ELglyPddxEREZGRNtphoLOAC4BzzWxJ+jgvPfcWdppmNLNZZvbb9OUMYIGZPQj8FfiNu/8+PXcl8DIzWwG8LH0tIiIiY8WTchK1eOzLRjXHy90XsIutm9z9nUMcWw+clz5fBZy4i7bbgJeMWEdFREREakBbBomIiMjI2MejUbWgjHMRERGRGlHES0REREbEvp5/VQuKeImIiIjUiCJeIiIiMjIU8RqWIl4iIiIiNaKIl4iIiIwI5XgNTxEvERERkRpRxEtERET23n6wj2ItKOIlIiIiUiOKeImIiMjIUMRrWIp4iYiIiNSIBl4iIiIiNaKpRhEREdlrhspJVOOAGXhlDKYF4Vh3Y1wpEY91FwAoeWGsuwDAC+ufHOsuVHTUjY//VjeWm8e6CwD0enasu1AxMztprLsAwIx8+1h3AYANhQlj3YWKtoPqx7oLALQW68a6CwCsGesOyJAOmIGXiIiIjDJFvIalHC8RERGRGlHES0REREaEuUJew1HES0RERKRGFPESERGRvactg6qiiJeIiIhIjSjiJSIiIiNCdbyGp4iXiIiISI0o4iUiIiIjQxGvYSniJSIiIlIjiniJiIjIiFCO1/AU8RIRERGpEUW8REREZGQo4jUsRbxEREREakQDLxEREZEaGdWBl5nNNbPbzWy5mS0zs0vS4z82syXpY7WZLam2bXruk2a2bsA9zhvNzyEiIiLD8CS5vhaPfdlo53iVgcvdfbGZNQOLzOxWd39z3wVmdhXQtgdtH0nPf9HdvzDK/RcREREZMaM68HL3DcCG9HmHmS0HZgOPAJiZAW8Czt3TtiIiIjLO7OPRqFqoWY6Xmc0DTgbuG3D4HGCTu694Fm3fb2YPmdm3zGzSCHdXREREZMTVZOBlZk3AjcCl7t4+4NRbgR8+i7ZfBQ4DTiKJil21i7YXmdlCM1u4dVu8dx9CREREdslQjlc1Rn3gZWZZkoHTDe5+04DjGeB84Md72tbdN7l75O4x8A3g9KHau/u17n6qu586dYoWcIqIiMjYGtUcrzSH6zpgubtfvdPplwKPuvvaPW1rZjPTHDCA1wMPj2zPRUREZI/5Ph6OqoHRDgOdBVwAnDtE6Ye3sNM0o5nNMrPfVtH282a21MweAl4MXDbKn0NERERkr432qsYFJNO+Q5175xDH1gPnVdH2gpHrpYiIiIyEfT3/qhaU+CQiIiJSI9okW0RERPaeozpeVVDES0RERKRGFPESERGREWEqmTksRbxEREREakQRLxERERkZyvEaliJeIiIiIjWigZeIiIjsV8xsrpndbmbLzWyZmV2SHv/xgKLsq81syYA2HzWzJ8zsMTP7m9Hqm6YaRUREZESMowKqZeByd19sZs3AIjO71d3f3HeBmV0FtKXPjyXZUec5wCzgj2Z2pLtHI90xRbxERERkv+LuG9x9cfq8A1gOzO47n+4H/Sb6ty58LfAjdy+4+5PAE8Dpo9E3RbxERERk7znjcpNsM5sHnAzcN+DwOcAmd1+Rvp4N3Dvg/FoGDNRGkgZeIiIisq+ZamYLB7y+1t2v3fkiM2sCbgQudff2AafeSn+0C4beG3pURpEaeImIiMiIqGGO11Z3P3V3F5hZlmTQdYO73zTgeAY4HzhlwOVrgbkDXs8B1o9cd/spx0tERET2K2kO13XAcne/eqfTLwUedfe1A47dDLzFzPJmNh84AvjraPRNEa8aC4aMZo6N7DgZd88Ix7oHibyNn38OB1t2rLsAwKywY6y7AEDBx88+JEfnto51FwB4Ot881l0AoKOxfqy7ULGlPD6+k/HSjz+OxZuOnxSvs4ALgKUDSkZ8zN1/S7J6ceA0I+6+zMx+AjxCsiLy4tFY0QgaeImIiMh+xt0XMHTeFu7+zl0c/yzw2VHsFqCBl4iIiIwAY1zV8Rq3xsdck4iIiMgBQBEvERER2Xvu47KO13ijiJeIiIhIjSjiJSIiIiNCOV7DU8RLREREpEYU8RIREZGRoYjXsBTxEhEREakRDbxEREREakRTjSIiIjIilFw/PEW8RERERGpEES8RERHZew7ECnkNRxEvERERkRpRxEtERERGhgJewxrViJeZzTWz281suZktM7NL0uM/NrMl6WO1mS3ZRftXmNljZvaEmV0x4PhkM7vVzFakf04azc8hIiIiMhJGe6qxDFzu7scAZwAXm9mx7v5mdz/J3U8CbgRu2rmhmYXAl4FXAscCbzWzY9PTVwC3ufsRwG3paxERERlD5rV57MtGdeDl7hvcfXH6vANYDszuO29mBrwJ+OEQzU8HnnD3Ve5eBH4EvDY991rg+vT59cDrRuUDiIiIiIygmuV4mdk84GTgvgGHzwE2ufuKIZrMBp4e8Hot8Lz0+Qx33wDJ4M7Mpo98j0VERGSP+D4ejqqBmqxqNLMmkinFS929fcCptzJ0tAvAhji2R3+jZnaRmS00s4Vbt8V70lRERERkxI16xMvMsiSDrhvc/aYBxzPA+fD/27v3IEmr8o7j358g4WaQCqCAKIhsUl5WEElQhCIqlGIVGDFBowYh5YUI5qbE0mhZWiZEVErjpVgVLQ3hoiChCOWipYIgd1iWXYHyhskKgmgFL0Fw2Sd/vO+Y3tnu6WW7552Z7u+nqovu877n7fOeOTOcfc55z+HAAVnXAXv1fH4CcFf7/p4ku7fRrt2Be/tdoKpWACsADnjmNnbDJUmaR0t9/lUX5vupxgCfBm6rqg/NOvxC4PaqWjcg+/XAfkn2SbIN8Arg4vbYxcDx7fvjgf8Yb8klSZLGb76HGg8BXgM8v2f5iKPaY69g1jBjkj2SXApQVeuBk4GVNJPyz6+qte2ppwFHJPkOcET7WZIkLZTq8LWEzetQY1VdSf+5WlTVa/uk3QUc1fP5UuDSPuf9FHjB2AoqSZLUAVeulyRJIwsQn2ocyr0aJUmSOmLHS5IkqSMONUqSpPFwycyhjHhJkiR1xIiXJEkaCyfXD2fES5IkqSNGvCRJ0ugmYHHTLhjxkiRJ6ogRL0mSNAYFzvEayoiXJElSR4x4SZKksYgBr6GMeEmSJHXEiJckSRoP53gNNTUdr1Wrf3Pfznuu++GIl9kFuG8c5Zkg1snGrI9NWSebGkOd3D2WgiwStpFNjaNOnjSOgmi8pqbjVVW7jnqNJDdU1bPHUZ5JYZ1szPrYlHWyKetkY9bHppZknRTEvRqHco6XJElSR6Ym4iVJkuaZc7yGMuL1yKxY6AIsQtbJxqyPTVknm7JONmZ9bMo6mVApe6eSJGlEv7vjnvVHy0/q5Lu+evU7b1xyc+BaRrwkSZI6YscLSPK3SdYmWZPknCTb9hx7S5JKssuAvC9KckeS7yZ5W3elnl8j1smdSW5NsirJDd2Ven71q5Mk707yo/ZeVyU5akDeiWsnI9bH1LSRNv2U9ue/Nsn7B+SduDYCI9fJ1LSTJOf1/N7cmWTVgLwT2U6mydRPrk+yJ/Bm4KlV9UCS84FXAJ9NshdwBPBfA/JuBXysPWcdcH2Si6vq292Ufn6MUic9/riqJmZdnjnqBOCMqvrAHHknrp2MUh89pqKNJPkhcAywvKoeTLJbn7wT10ZgtDrpMRXtpKqO6znng8D9ffIu+nYSpy8NZcSrsTWwXZKtge2Bu9r0M4BTgUEt6Q+B71bV96vqIeBcmj8mk2BL62SSDaqTYSa1nWxpfUyyfnVyEnBaVT0IUFX39sk3qW0EtrxOJtnA350kAf4MOKdPvkluJ1Nj6jteVfUj4AM0EZy7gfur6rIkRwM/qqpb5si+J/DfPZ/XtWlL2oh1Ak2n7LIkNyZ5/TwXtxOD6qQ9fHKS1UnOSrJzn+wT105GrA+YrjayDDg0ybVJLk9yUJ/sE9dGYOQ6gelqJzMOBe6pqu/0yb7420lVN68lbOo7Xu3/GI4B9gH2AHZI8hfAO4B3DcveJ21ptwhGrhOAQ6rqWcCLgTclOWzeCtuRAXXyauATwL7A/jR/RD/YL3uftCXdTkasD5iuNrI1sDNwMPBW4Pw2qrFR9j6XXNJtBEauE5iudjLjlfSPdsGEtpNpM/UdL+CFwA+q6idV9RvgQuAEml+KW5LcCTwBuCnJ42flXQfs1fP5CUzGcMsodUJV3dX+917gSzTh8aWuX508t6ruqaqHq2oD8En63+sktpNR6mOq2gjNz//CalwHbKDZh6/XJLYRGK1Opq2d0A49vgw4b0Dexd1OiuYn2cVrCbPj1YR7D06yffsvrhfQ/EHYrar2rqq9aRr7s6rqx7PyXg/sl2SfJNvQTC6+uMvCz5MtrpMkOyR5zMx74EhgTbfFnxf96uS2JLv3nPMn9L/XSWwnW1wf09ZGgIuA5wMkWQZsw6abH09iG4ER6mQK2wk0nbLbq2rdgLyT2k6mytQ/1VhV1yb5InATsB64mTlWDE6yB/CpqjqqqtYnORlYCWwFnFVVa7so93wapU6AxwFfakcNtgb+vaq+PP+lnl9z1MmnkuxP82+9O4E3wOS3k1Hqg+lrIwWclWQN8BBwfFXVpLcRGK1OmL52Ak1HaqNhxqXUTkL5VONmcOV6SZI0sp122KMOfuobOvmuy25495JduX7qI16SJGlMDOYM5RwvSZKkjhjxkiRJ42HEaygjXpIkSR0x4iVJkkY3s46X5mTES5IkqSN2vKQOJfnlPFzz6CRva9+/NMlTt+Aa30iy2Y9mt+ffkWb/ztnH9m7XZ5oKSd7e8367JKuSPJRkk5XYpUmXqk5eS5kdL2mJq6qLq+q09uNLgUfc8dpCr6qqeV01O8lW83n9Mfltx6uqHqiq/VlM27hIWlTseEkLII3Tk6xJcmuS49r0w9to0heT3J7k7JnNg5Mc1aZdmeQjSS5p01+b5KNJngscDZzeRl327Y1kJdml3WdzJjJzbpLVSc4Dtusp25FJrk5yU5IvJNlxM+7nwCS3JLkaeFNP+lbtfV7fftfMSvaPSvLxJGuTXJLk0iQvb4/dmeRdSa4E/nRQedrvvDzJjUlWpt2uKMmbk3y7/b5z5yjzDknOast2c5Jj2vS9k3yz/b6b2nolye5Jrmjrdk2SQ5OcBsxEuc7erB++pKnm5HppYbwM2B94Js3mwNcnuaI9dgDwNJqoyVXAIUluAM4EDquqHyQ5Z/YFq+pbSS4GLqmqLwK0fbZ+TgL+t6qWJ1lOs30J7fDYPwIvrKpfJfkH4O+A9wy5n88Ap1TV5UlO70n/S+D+qjooye8AVyW5DDgQ2Bt4BrAbzV51Z/Xk+3VVPa8tz4Wzy5Pkn4F/BY6pqp+0Hdf3AScCbwP2qaoHkzx2jjK/A/haVZ3Ynnddkq8C9wJHVNWvk+xHs4XLs4E/B1ZW1fvaSNz2VfXNJCe3US5JS3wYsAt2vKSF8TzgnKp6GLgnyeXAQcDPgetmNslNsoqmg/JL4PtV9YM2/znA60f4/sOAjwBU1eokq9v0g2mGKq9qO23bAFfPdaEkOwGPrarL26TPAy9u3x8JLJ+JZgE7AfvR3P8XqmoD8OMkX5912fOGlOf3gacDX2nTtwLubvOsBs5OchHNZsyDHAkcneQt7edtgSfSdHg/mmbPyYeBZe3x62n2F3w0cFFVrZrj2pLUlx0vaWEMDEUBD/a8f5jm93Su8+eynv+fUrDtrGP9/mka4CtV9cpH8B0ZcK2ZY6dU1cqNEpOXDLnmr+YqT5JnAGur6jl98r6EpmN5NPDOJE+rqvUDynZsVd0x69rvBu6hiUY+Cvg1QFVdkeSw9vqfT3J6VX1uyH1IU6SMeG0G53hJC+MK4Lh2DtSuNB2F6+Y4/3bgyUn2bj8fN+C8XwCP6fl8J82wHsDLe9KvAF4FkOTpwPI2/Rqaoc2ntMe2T7KMOVTV/wD3J3lem/SqnsMrgZPaKBFJliXZAbgSOLad6/U44PABlx9UnjuAXZM8p01/dJKnJXkUsFdVfR04FXgsMGiO2krglOS3c+gOaNN3Au5uo3GvoYmmkeRJwL1V9Ung08Cz2vN/M3N/kjSMHS9pYXyJZkjsFuBrwKlV9eNBJ1fVA8BfAV9uJ53fA9zf59Rzgbe2k8X3BT5A0/H5Fs1cshmfAHZshxhPpe30VdVPgNcC57THrgH+YDPu5wTgY+3k+gd60j8FfBu4Kc0SE2fSRPAuANYBM2nX9rufQeWpqodoOpL/kuQWYBXwXJpO0r8luRW4GTij7Rj2817g0cDqtmzvbdM/Dhyf5BqaYcaZ6NvhwKokNwPHAh9u01e013ByvaZb0US8ungtYaklfgPStEiyY1X9so3QfAz4TlWdsUBl+Qbwlqq6YYRrzNzP79F0/A6Zq/O5lKR5evTZVXXfQpdF6spO2+1ez3nKiZ1818o1/3RjVW322oOLiREvael4XTvZfi3NcNiZC1iWnwGfTZ8FVB+BS9r7+Sbw3knodKVdQJUmkubmKZo+Gzp6LWFOrpeWiDa6tSARrtmq6mVjuMbhYyjKUElOAP56VvJVVfWmfuePoh0S3n/c15X0yCTZC/gc8HiartqKqvpwe+wU4GSah4/+s6pObefP3kYzfxTgmqp643yUzY6XpIlWVZ+hWWdM0jxbRNv5rAf+vqpuSvIY4MYkXwEeBxwDLG/X+tutJ8/3uliTz46XJEmaKFV1N+3aflX1iyS3AXsCrwNOq6oH22P3dl0253hJkqTxWIRPNbbDiAfQPD29DDg0ybVpthw7qOfUfdonwi9PcujY6mQWI16SJGmp2aXdSm3GiqpaMfukNHu7XgD8TVX9PMnWwM40u2IcBJyf5Mk00bEnVtVPkxwIXNQuvvzzcRfcjpckSRpdARs6m+N137DlJNqFjS8Azq6qC9vkdcCF1ayldV2SDcAu7ZqBM8OPNyb5Hk10bIuXzBnEoUZJkjRR2vUOPw3cVlUf6jl0EfD89pxlNPu/3pdk1yQzu1Q8mWZP2e/PR9mMeEmSpDFYVKvKH0Kz5det7dp6AG8HzqLZ7H4N8BBwfFVVuw/re5Ksp9kj941V9bP5KJgdL0mSNFGq6kogAw6/us/5F9AMS847hxolSZI6YsRLkiSNx+IZaly0jHhJkiR1xIiXJEkaDyNeQxnxkiRJ6ogRL0mSNLpuF1Bdsox4SZIkdcSIlyRJGoOC2rDQhVj0jHhJkiR1xIiXJEkaD59qHMqIlyRJUkeMeEmSpNH5VONmMeIlSZLUESNekiRpPJzjNZQRL0mSpI4Y8ZIkSeNhxGsoI16SJEkdseMlSZLUEYcaJUnSGJRDjZvBiJckSVJHjHhJkqTRFbDBTbKHMeIlSZLUESNekiRpPJzjNZQRL0mSpI4Y8ZIkSeNhxGsoI16SJEkdMeIlSZLGoGCDEa9hjHhJkiR1xIiXJEkaXUGV63gNY8RLkiSpI0a8JEnSeDjHaygjXpIkSR0x4iVJksbDdbyGMuIlSZLUETtekiRJHXGoUZIkja4KNricxDBGvCRJkjpixEuSJI2Hk+uHMuIlSZLUESNekiRpLMo5XkMZ8ZIkSeqIES9JkjQG5RyvzWDES5IkqSNGvCRJ0ugKN8neDEa8JEmSOmLES5IkjUf5VOMwRrwkSZI6YsRLkiSNrIByjtdQRrwkSZI6YsRLkiSNrso5XpvBiJckSVJH7HhJkiR1xKFGSZI0Fk6uH86IlyRJUkeMeEmSpPFwcv1QRrwkSZI6kirHYyVJ0miSfBnYpaOvu6+qXtTRd42VHS9JkqSOONQoSZLUETtekiRJHbHjJUmS1BE7XpIkSR2x4yVJktSR/wPord6ZepaMQAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 10))\n",
    "t2m[154,:,:].plot(ax=ax) \n",
    "catch_polygons.boundary.plot(ax=ax, alpha=.6, color='black')\n",
    "# plt.title('')\n",
    "\n",
    "# tutorial for this:\n",
    "# https://www.earthdatascience.org/workshops/gis-open-source-python/crop-raster-data-in-python/\n",
    "\n",
    "# plt.savefig('era5_catchments.png', dpi = 300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c16f8c4-a585-4e59-b34b-b95152278b3c",
   "metadata": {},
   "source": [
    "### Multiple in one fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7df05d32-b1dc-475b-bd8d-6f7df5eeb5ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x432 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot multiple: \n",
    "\n",
    "fig, axes = plt.subplots(1, 5, figsize = (25,6))\n",
    "t2m [305,:,:].plot(ax=axes[0])\n",
    "tp  [305,:,:].plot(ax=axes[1])\n",
    "fal [305,:,:].plot(ax=axes[2])\n",
    "sd  [305,:,:].plot(ax=axes[3])\n",
    "slhf[305,:,:].plot(ax=axes[4])\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e1e2e722-ca0b-4dc5-bd4b-cef16c76d276",
   "metadata": {},
   "outputs": [],
   "source": [
    "# f['tp'].plot()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0881082-16df-4b73-a194-3610f88226f7",
   "metadata": {},
   "source": [
    "## Calculate mean values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "430699dd-01ca-4b82-bd5e-c77f1f032a47",
   "metadata": {},
   "source": [
    "#### 1. just mean values over the entire time "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "13c4c749-434e-48d8-8eed-c62bb1541ebe",
   "metadata": {},
   "outputs": [],
   "source": [
    "# mean vallues + keep the coordinates\n",
    "fmeans = f.mean(dim='time', keep_attrs = True) \n",
    "# fmeans "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "aeed7c0e-d5c0-4831-9bbb-c883bbbbb7e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9, 13)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# extract arrays from .nc file:\n",
    "\n",
    "lons_mean = fmeans.longitude \n",
    "lats_mean = fmeans.latitude\n",
    "# time_mean = fmeans.time  # - no - since no time attribute anymore\n",
    "\n",
    "t2m_mean  = fmeans.t2m  # 2m temp in K\n",
    "fal_mean  = fmeans.fal  # forecasted albedo \n",
    "sd_mean   = fmeans.sd   # snow depth\n",
    "slhf_mean = fmeans.slhf # surface latent heat flux\n",
    "tp_mean   = fmeans.tp   # total precip\n",
    "\n",
    "tp_mean.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3dec7bb6-f497-4d8e-8237-3fe895da42f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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q6ntttVWStOW8e2npMoMlabKZwUuT+StJk21a83doYyAn2R94OPB14DjgjCRvpzOMxuMWKP4C4OOz1r0iye8B59L5hvdHPeo8GjgaYNvlO21N8yVJGlsjz+BVu2xN8yVJGkujzt/le5i/kqTBGEq3eZIdgU8Dx1XVLcDLgFdX1X7Aq4EPzVN2FfBs4FNdq98HPIjO4z3rgHf0KltVq6vq0Ko6dNXy7QZxKpKkRgEba9lAXmrPUsjglSt2GMSpSJIag8pgtWcp5O/yncxfSRqkab4Gbr3FSVbSCc6Tq+rUZvWLgJn3nwI2m0Cgy+HA+VV13cyKqrquqjZU1UbgAwuUlyS1ImwY0EvtMIMlaVKZv0uZ+StJk2p6r4Fb7UBOEjrfrK6pqnd2bboWeFLz/qnA5fMc5ihmPbqTZK+uxd8ALt761kqSNDnMYEmShs/8lSRNorbHQH488ELgoiQXNOteD/whcEKSFcAdNGM0Jdkb+GBVHdEsbw88A3jprOO+LckhdO4ev6rHdklSy2Ye39GSZQZL0oQyg5c081eSJtQ052+rHchVdTbMeV/2I3vsfy1wRNfybcB9euz3wkG1UZK0eOP46M20MIMlabKZwUuT+StJk21a83c6u80lSZIkSZIkSQtqewgLSdKEqsrUPr4jSdIomcGSJA3fNOevHciSpEXbMKXhKUnSqJnBkiQN37Tm73SetSRJkiRJkiRpQd6BLElalAI2TukEApIkjZIZLEnS8E1z/tqBLElapEzt4zuSJI2WGSxJ0vBNb/5O51lLkiRJkiRJkhbkHciSpEUpYGNN5+M7kiSNkhksSdLwTXP+2oEsSVq0DT7IIknSSJjBkiQN37Tm73SetSRJkiRJkiRpQd6BLElalCJT+/iOJEmjZAZLkjR805y/diBLkhZtow+ySJI0EmawJEnDN635O51nLUmSJEmSJElakHcgS5IWpQo2TOnjO5IkjZIZLEnS8E1z/tqBLElatGkd/0mSpFEzgyVJGr5pzV+HsJAkSZIkSZIk9TQ1dyBv2GEVNx+2b6t1LNuwT7vHv7taPT7ANjfd1Xody390W+t1bFzV7o92vndtq8cH2HDzLa3XsWxl+/8FLNt373Yr2GZlu8cH7tq5/Tpq5fh9i9mZgdbvIbWwu3dexjVP26m14//kZ+9u7dgzlt22Xet17Hbxrq3X8dN2f1Vhz2/u0m4FwA7f+XHrday4qf0Mrlt/0u7x72r/3wUbNrRexca717deR4ZQx6CZwerL+mXww21arWL1N5/Y6vEBlq3Y2OrxV6xs//+yvbe5ufU6/ufHe7Zexy8+5HutHv9Hd7b/+9b1N7f3O+mM29fs2Hodd93Z/vXjjmvbPf7yIZzDoE1z/k5NB7IkafA2MH6hL0nSJDCDJUkavmnN3+nsNpckSZIkSZIkLcg7kCVJi1JM7wQCkiSNkhksSdLwTXP+2oEsSVqk6R3/SZKk0TKDJUkavunN3+k8a0mSJEmSJEnSgrwDWZK0aBundAIBSZJGzQyWJGn4pjV/7UCWJC1KFWyY0vGfJEkaJTNYkqThm+b8dQgLSZIkSZIkSVJP3oEsSVq0aZ1AQJKkUTODJUkavmnN3+k8a0nSVivCxhrMayFJ9kvypSRrklyS5FXN+ocl+WqSi5L8a5Kdu8q8LskVSS5L8sst/lVIkjRUg8pgSZLUv2FeAy81diBLksbBeuA1VfXzwGOAY5McDHwQOL6qfhH4DPCnAM22FwAPAZ4FvDfJ8pG0XJIkSZKkMeYQFpKkRRvWDLRVtQ5Y17y/NckaYB/gwcBZzW5nAmcA/xs4Ejilqu4EvpvkCuAw4KtDabAkSS2b1lngJUkapWnNXzuQJUmLUjDIR2/2SHJu1/Lqqlrda8ck+wMPB74OXAw8G/gs8FvAfs1u+wBf6yq2tlknSdLYG3AGS5KkPkxz/tqBLElatAFOIHBDVR260E5JdgQ+DRxXVbck+X3gXUneCJwG3DWza4/iNajGSpI0atM6iY8kSaM0rflrB7IkaSwkWUmn8/jkqjoVoKq+DTyz2X4Q8CvN7mu5925kgH2Ba4fXWkmSJEmSJoMdyJKkxRni7LFJAnwIWFNV7+xav2dVXZ9kGfAG4MRm02nAx5K8E9gbOBD4xlAaK0lS28Z0BndJksbaFOdvq/ddJ9kvyZeSrElySZJXNesPSfK1JBckOTfJYXOUvyrJRTP7da3fPcmZSS5v/tytzfOQJG2u6EwgMIhXHx4PvBB4apMJFyQ5Ajgqyf8A36Zzh/E/AFTVJcAngUuBLwDHVtWGFv4aliwzWJIm16AyWINn/krS5BryNfCS0vYdyOuB11TV+Ul2As5LcibwNuDNVfX5pgPgbcCT5zjGU6rqhlnrjge+WFVvTXJ8s/zadk5BkjRqVXU2vcc1BjhhjjJ/BfxVa41a+sxgSZKGz/yVJE2cVjuQq2odsK55f2uSNcA+dDrtd25224UtH5fySO4N2w8DX8bwlKShm9bHd8aBGSxJk80MXprMX0mabNOav0MbAznJ/sDDga8DxwFnJHk7nWE0HjdHsQL+PUkB76+q1c36+zXBTFWtS7Jnm22XJG2umN7wHDdmsCRNFjN4PJi/kjRZpjl/Wx0DeUaSHYFPA8dV1S3Ay4BXV9V+wKvpTIzUy+Or6hHA4cCxSX5pC+s9uhlf6ty77/zpVpyBJEnjaSlk8IbbzGBJ0nRZEvn7E/NXkjQYrXcgJ1lJJzhPrqpTm9UvAmbefwroOYFAVV3b/Hk98Jmu/a5Lsldz/L2A6+cov7qqDq2qQ1dus8MgTkeS1GVjMwvt1r7UjqWSwcu3N4MladDM36VryeTvjuavJA3atF4Dt9qBnCR0vlldU1Xv7Np0LfCk5v1Tgct7lN2hmXSAJDsAzwQubjafRieAaf787OBbL0maTzGY4BzH8BwHZrAkTa5BZXA/kjwryWVJrmgmb5u9PUne1Wy/MMkjuradlOT6JBfPKrN7kjOTXN78udtW/6UsEeavJE2uab4GbnsM5McDLwQuSnJBs+71wB8CJyRZAdwBHA2QZG/gg1V1BHA/4DOd/GUF8LGq+kJzjLcCn0zyB8D3gd9q+TwkSRo3ZrAkaaskWQ68B3gGsBY4J8lpVXVp126HAwc2r0cD72v+BPhH4N3AR2Yd+njgi1X11qZT+ngmZ0I481eSNHFa7UCuqrOBubrVH9lj/2uBI5r3VwIPm+O4NwJPG1AzJUmLtHHO/+I1amawJE22IWXwYcAVTS6Q5BTgSKC7A/lI4CNVVcDXkuyaZK+qWldVZzUTyc12JPDk5v2HgS8zIR3I5q8kTbZpvQZu+w5kSdKkqumdgVaSpJEaXgbvA1zdtbyWe+8unm+ffYB18xz3flW1DqCq1iXZcwBtlSSpXVN8DWwHsiRJkiRNpz2SnNu1vLqqVnct97pKrlnL/ewjSZLGmB3IkqRFKab321dJkkZpgBl8Q1UdOs/2tcB+Xcv70pkMbkv3me26mWEukuwFXN9vgyVJGpVpvgZeNuoGSJLG17TOQCtJ0qgNKX/PAQ5MckCSVcALgNNm7XMa8HvpeAxw88zwFPM4DXhR8/5FwGf7P3NJkkZnWq+B7UCWJEmSJG2mqtYDrwDOANYAn6yqS5Ick+SYZrfTgSuBK4APAC+fKZ/k48BXgQcnWZvkD5pNbwWekeRy4BnNsiRJWqIcwkKStCjFeH5zKknSuBtmBlfV6XQ6ibvXndj1voBj5yh71BzrbwSeNsBmSpLUumm+BrYDWZK0aDWl4SlJ0qiZwZIkDd+05q9DWEiSJEmSJEmSevIOZEnSom1kOr99lSRp1MxgSZKGb1rz1w5kSdKiVDG14z9JkjRKZrAkScM3zfnrEBaSJEmSJEmSpJ7sQJYkLVpVBvKSJElbxvyVJGn4hnkNnORZSS5LckWS43tsf3KSm5Nc0LzeOPATbjiEhSRpkTK1j+9IkjRaZrAkScM3vPxNshx4D/AMYC1wTpLTqurSWbv+Z1X9atvt8Q5kSZIkSZIkSVo6DgOuqKorq+ou4BTgyFE1xjuQJUmL5uOvkiSNhhksSdLwDTB/90hybtfy6qpa3bW8D3B11/Ja4NE9jvPYJN8CrgX+pKouGVQDu9mBLElalGJ6Z6CVJGmUzGBJkoZvwPl7Q1UdOs/2XhXVrOXzgZ+pqp8kOQL4F+DAAbVvE1PTgbx8z7vY7RXfa7WObVesb/X4V928W6vHB7j6O7u3Xsc2N27feh0rb233+Huev227FQCrLvl+63VsvPmW1uvY8P1rWj1+rlne6vEBtt9159brYOXK9uuQRuTgPa/nv1/5960df2Xa/3Xm1ese2Xodn93lYa3Xsdf9f9zq8a/dYc9Wjw+w8173ab2O7W5o/3eulT/Z0Orxt7um5V+GgFx3Y+t1bLjxptbrwI5YTahtrv4pP/uac0bdjK2WbbZp9fjL9mj/GvjsX3xs63Wsumtj63Vc9IJ2M/ivn/ipVo8P8Fs73tx6HRc86o7W63jtlc9pvY4rz9+v1eNnffvX8nym/SpatBbo/hD2pXOX8T2q6pau96cneW+SParqhkE3Zmo6kCVJA1ZQs7//lCRJ7TODJUkavuHm7znAgUkOAK4BXgD8dvcOSe4PXFdVleQwOnPdtfINvx3IkqRF29jzqRpJktQ2M1iSpOEbVv5W1fokrwDOAJYDJ1XVJUmOabafCDwXeFmS9cDtwAuq2unitgNZkiRJkiRJkpaQqjodOH3WuhO73r8bePcw2jJvB3KS0/o4xk1V9eLBNEeSNC6K8Z4BPskf97HbT6vq/a03pgczWJI0l3HP4KXM/JUkzWWa83ehO5B/Hvhf82wP8J7BNUeSND4y7jPA/ynwPnrPbjvjGGAkHciYwZKkOY19Bi9l5q8kaQ7jmb9J3tXHbrdU1Rvm2rhQB/KfV9VXFmjEm/tohCRpAo35BD4fraq3zLdDkh2G1ZgezGBJ0pzGPIOXMvNXkjSnMc3fI4E3LrDP8cDiOpCr6pMLtaCffSRJWoL+aq4NSR5VVedU1Z8Ns0HdzGBJkobP/JUkTaC/raoPz7dDkt3m297XJHpJDqLzqO/PdJepqqf2U16SNJnGfPynLyZ5RlX9qHtlkmcCHwL2G02zNmUGS5J6GfMMXvLMX0lSL+OYv1X1d1u7T18dyMCngBOBDwAb+iwjSZpgVeMZnl3eD3yp6UT+IUCS36ZzZ/KvjLRlmzKDJUmbmIAMHgfmryRpE+Ocv0m2BX4VeCKwN3A7cDHwb1V1yULl++1AXl9V71t0KyVJWmKq6gNJ7gD+o7nr+Pl0Js17SlVdNdLGbcoMliRNnSS3LLQLsK6qDmqpCeavJGkiJHkT8GvAl4GvA9cD2wIHAW9tOpdfU1UXznWMeTuQk+zevP3XJC8HPgPcObO9qm7aivZLksbcOM5A262qPtp0In8T+D7w+Kq6ccTNAsxgSdL8xj2D+/Cdqnr4fDsk+eagKzV/JUnzGdP8Paeq3jTHtncm2RN4wHwHWOgO5POAovPtLnTGgJpRwAP7aKQkaUKN6Qy0ACS5iHszbnvgPnSGtAhQVfXQUbYPM1iSNI9xzuA+PWdA+2wp81eSNKdxzN+q+rcFtl9P567kOc3bgVxVB0BnnIyquqN7W3N7syRJ4+pXR92A+ZjBkqRpVlVXdi8n2ZlNJ7O7afY+A6rX/JUkTY0kq6vq6IX263cM5P8GHtHHOknSFBnXCQQAqup7o25Dn8xgSdJmxjmDt0SSlwJvoTPZz8x9X8O4E9j8lSRtZhzzt2t4ps02AUf0c4yFxkC+P7APsF2Sh3PvYzw703ncV5I0pYqMZXjOSPK5qpr3LuR+9mmLGSxJmsu4Z/AW+hPgIVV1wzAqM38lSXMZ4/z9IfA97s00uHe4pj37OcBCdyD/MvBiYF/gHV0V3QK8fgsaKknSUvOEJKfNsz3AwcNqTA9msCRJ8B3gtiHWZ/5KkibNlcDTqur7szckubqfAyw0BvKHk3wUOKqqTt7S1iXZD/gIcH9gI7C6qk5IcghwIrAtsB54eVV9o5+yzbY3AX9Ipwcd4PVVdfqWtk+StHXGcP6Abkf2sc9drbdiDmawJGk+Y57BW+J1wH8n+Tpw58zKqnplG5WZv5Kk+Yxp/v4dsBuwWQcy8LZ+DrDgGMhVtbEZd2qLw5NOML6mqs5PshNwXpIzm8a9uao+n+SIZvnJ/ZStqkub7X9bVW9fRJskSYNQ4zn+04yq+sqo27AQM1iS1NOYZ/AWej/wH8BFdDpVW2f+SpJ6GtP8rar3zLPt7/s5Rr+T6J2Z5E+ATwA/7arkpgUauA5Y17y/NckaOuNJFZ0xpAB2Aa7dgrKXzt5XkqQJZgZLkqbZ+qr64xHUa/5KktTotwP595s/j+1at0Uz3ybZH3g48HXgOOCMJG8HlgGP24KyM16R5PeAc+l8S/ujftsiSRqQMX1+Z8yYwZKkzU1PBn8pydHAv7LpEBbzduQOgPkrSdrc9OTvJpb1s1NVHdDjtSXBuSPwaeC4qroFeBnw6qraD3g18KEtKAvwPuBBwCF0vqF9xxxlj05ybpJz7/rx7f02V5LUp6oM5DVqSbZL8uBRt6OXScjgH964od/mSpL6NAn526ffphkHGTiveZ3bdqWTkL9339vfLkkakEm5Bt5SfXUgJ1mZ5JVJ/rl5vSLJyn7L0gm/k6vq1Gb1i4CZ958CDtuCslTVdVW1oao2Ah+Yq3xVra6qQ6vq0FW7btdPcyVJUybJrwEXAF9olg9JctpIG9VlEjL4vvdZ3k9zJUnazNZ25C7WJOTvSrbpp7mSpCnUTM7at746kOl82/lI4L3N65HNuoUaEzrfrK6pqnd2bboWeFLz/qnA5VtQliR7dS3+BnBxn+chSRqgqsG8RuxNdC7CfgxQVRcA+4+sNZszgyVJm5mA/J1XkkcMYp+tYP5KkjYzIdfAAM/ekp37HQP5UVX1sK7l/0jyrT7KPR54IXBRkguada8H/hA4IckK4A7gaIAkewMfrKoj5ipbVacDb0tyCJ2RR64CXtrneUiSBqQYzxloe1hfVTd3rtmWJDNYkrSJCcrg+fxDkicD853oh+iME9wG81eStIkJy98tOpF+O5A3JHlQVX0HIMkDgQUHNKyqs+dp0CN77H8tcMRCZavqhX22W5KkhVyc5LeB5UkOBF5JZ5zFpcIMliRNo13ojHc83wXuD1us3/yVJE2yzTJpPv12IP8pndlvr6QTaD8DvGQLGyZJmiQFTMa3r38E/Dmdmd0/BpwB/OVIW7QpM1iStKnJyeA5VdX+I26C+StJ2tQE5W8zpn7f+upArqovNndlPZhOeH67qpzSVZKm3LDGbkqyH/AR4P7ARmB1VZ3QPMp5IrAtsB54eVV9I8n+wBrgsuYQX6uqY3ocdzlwWlU9nU4n8pJjBkuSelki4ydOLPNXktTLtOZvv3cgQ+fW5v2bMg9LQlV9pJVWSZK0qfXAa6rq/CQ7AeclORN4G/Dmqvp8kiOa5Sc3Zb5TVYfMd9Cq2pDktiS7VNXNLbZ/a5nBkiQNn/krSRJ9diAn+SjwIOAC7h33qejcDSZJmlZD+va1qtYB65r3tyZZA+zTtGDnZrdd6MxwvqXuoDNZzZnAT7vqfOVWNXpAzGBJUk9TegfUsJi/kqSexjR/k/wccCT3XkdfS+dp3DX9lO/3DuRDgYOrpvVGbUnS5jLIGWj3SHJu1/Lqqlrds9bO8BQPB74OHAeckeTtwDLgcV27HpDkm8AtwBuq6j/nqPvfmtdSZQZLkmYZaAYveUn2oTMG8T3Xr1V1VsvVmr+SpFnGM3+TvBY4CjgF+Eazel/g40lOqaq3LnSMfjuQL6Yz7uS6xTRUkqQF3FBVhy60U5IdgU8Dx1XVLUn+Enh1VX06yfOADwFPp5NXD6iqG5M8EviXJA+pqltmH7OqPjzYUxk4M1iSNLWS/DXwfOBSNr0TuO0OZPNXkjQp/gB4SFXd3b0yyTuBS4CBdSDvAVya5Bt0ZqkHoKqe3X9bJUkTZ4j35CRZSafz+OSqOrVZ/SLgVc37TwEfBGgmubmzeX9eku8ABwHnMkuS79LjTKrqgYM+h0UygyVJm5ue+2J/HXjwCCawM38lSZsbz/zdCOwNfG/W+r2abQvqtwP5Tf23SZI0FYqhPb6TJHTuLl5TVe/s2nQt8CTgy8BTgcub/e8L3NRMkvdA4EDgyjkO333n87bAbwG7D/QEts6bRt0ASdISM8QMXgKuBFbS1Yk7JG8acn2SpKVufPP3OOCLSS4Hrm7WPQD4WeAV/Rygrw7kqvrKfNuTfLWqHtvPsSRJWoTHAy+kM9ndBc261wN/CJyQZAWdyfCObrb9EvCWJOvpPO56TFXd1OvAVXXjrFV/l+Rs4I2DPYXFMYMlSVPuNuCCJF9k0zuBW53s1vyVJE2KqvpCkoOAw+hMohdgLXBOVW2Yt3Cj3zuQF7LtgI4jSRonQ3p8p6rOphNyvTyyx/6fpjPcxYKSPKJrcRmdO5J32tI2jpAZLEnTaDwfoV2M05rXUmP+StI0GsP8TbJjVf0E+Fof+/Q0qA7kMfzrkyRtvbF8fGe2d3S9Xw98F3jeiNqyGGawJE2licjgBVXVh5OsojOXAcBlsycBGhHzV5Km0ljm72ebJ3k/C5xXVT8FaIZ7fAqd698PAP881wEG1YEsSdK4+oOq2mR85CQHjKoxkiTpXkmeDHwYuIrOVft+SV5UVWeNsFmSJI2NqnpakiOAlwKPT7I7cDdwGfBvwIuq6gfzHWNQHchj2f0uSdpKk3HvzT8Dj+ixbrOhMZYoM1iSptFkZHA/3gE8s6ouA2jGcPw4o89p81eSptGY5m9VnQ6cvtjyfXUgJ9kBuL2qNjaB/XPA57seHXrhYhsgSRpjYxqeAEl+DngIsEuS3+zatDNLaFxDM1iS1NMYZ/AWWjnTeQxQVf+TZGXblZq/kqSexjB/k9x/oTuMF9qn3zuQzwKemGQ34IvAucDzgd8BqKqL+zyOJGlSFFBjffPNg4FfBXYFfq1r/a3AH46iQXMwgyVJmxr/DN4S5yb5EPDRZvl3gPOGUK/5K0na1Pjm7+ls/tTtFu3Tbwdyquq2JH8A/H1VvS3JN/ssK0nSklNVn6UzmcBjq+qro27PPMxgSdI0exlwLPBKOsNGnAW8dwj1mr+SpEnxsCS3zLM9wHzb++9ATvJYOt+2/sEWll0SdlvxU55z//NbrWOn5be3evw77tv6k1p8a++fab2Oq2/brfU61t22U6vHv+Lg+7Z6fIBtrj1o4Z220qqbW6+C3a7Y0Orxdzz7ilaPD7D+uutbr2Nc1Rg+vtPDN5McS2c4i3uGrqiq3x9dkzYx9hl86fV78vB3/9Gom7FV1u8whEp22dh6FTd+/36tHn/DPncvvNNWummX9u/6yKp2swuAO5a3evjdz9u91eMD7HHhqtbrWL799q3XsfE+7f7eyLntHHZYGZzkWcAJwHLgg1X11lnb02w/ArgNeHFVnT9f2SSHACfSyd31wMur6hu96q+qO4F3Nq9hGvv8nRR1553tHv9H7V8UbXdW+3XUhvaz6+e/e/9Wj/+Bf/yNVo8P8I4D2h+p7rY92/9d5cAj278O/oXDrlx4p61wxH0vavX4AMe8dvDHHMdr4Kra6l88l/W533HA64DPVNUlSR4IfGlrK5ckjbka0Gu0PgrcH/hl4CvAvnSGsVgqjsMMliTNNoT8TbIceA9wOHAwcFSSg2ftdjhwYPM6GnhfH2XfBry5qg4B3tgsz677k82fFyW5cPZr4dZvteMwfyVJs03GNfAW6+sb1Kr6CvCVZiIBqupKOo8QSZI07n62qn4ryZFV9eEkHwPOGHWjZpjBkqQROgy4oskekpwCHAlc2rXPkcBHqqqAryXZNclewP7zlC06k9YC7AJc26PuVzV//upAz6hP5q8kSffq6w7kJI9Ncimwpll+WJJhjDslSVrKKoN5jdbMM/c/TvILdC5k9x9dczZlBkuSehpM/u6R5Nyu19GzatkHuLpreW2zrp995it7HPA3Sa4G3k7nTt9NT69qXfP25VX1ve4X8PI+/5YWzfyVJPU0GdfAW6zfISz+js6jvTcCVNW3gF9qqU2SpDGRGsxrxFY3M6y/ATiNzp1Rfz3aJm3i7zCDJUmzDCh/b6iqQ7teq2dX06Pq2ck91z7zlX0Z8Oqq2g94NfCheU71GT3WHT7P/oPyd5i/kqRZxv0auPlC9BXN62H9luu3A5mqunrWqiHMLiJJUnuSLANuqaofVdVZVfXAqtqzqt4/6rZ1M4MlSSOyFtiva3lfNh9uYq595iv7IuDU5v2n6AyVsYkkL0tyEfDgWeMffxcYxhjI5q8kaaIkeRVwMrBn8/qnJH3Ndt7vLLJXJ3kcUElW0Rn7ac1iGitJmhBjOvh/t6ramOQVwCdH3ZZ5mMGSpE0NL4PPAQ5McgBwDfAC4Ldn7XMa8IpmjONHAzdX1bokP5yn7LXAk4AvA08FLu9R98eAzwP/Fzi+a/2tVXXTAM5tIeavJGlT438N/AfAo6vqpwBJ/hr4KvD3CxXstwP5GOAEOmNWrQX+HTh2UU2VJE2I8Ry7qYczk/wJ8AngpzMrh3Rx2g8zWJI0y3AyuKrWN1+0ngEsB06qqkuSHNNsPxE4HTgCuAK4DXjJfGWbQ/8hcEKSFcAdwOyxl6mqm4GbgaMAkuwJbAvsmGTHqvp+S6c9w/yVJM0y9tfAYdOnaTbQe8ipzfTVgVxVNwC/s+XtkiRpyfv95s/ui8ICHjiCtmzGDJYkjVJVnU6nk7h73Yld74s5OlZ7lW3Wnw08sp/6k/wa8E5gb+B64Gfo3An8kP7OYHHMX0nSBPoH4OtJPtMs/zrzz0Nwj77GQE5yUJIvJrm4WX5okjcspqWSpAlSA3qNUFUd0OO1JDqPwQyWJM1hzPN3C/wl8Bjgf6rqAOBpwH+1Xan5K0nqaYyvgavqnXSeFLoJ+BHwkqr6u37K9juJ3geA1wF3NxVeSGcMK0nSNBvj8JyRZPskb0iyulk+MMmvjrZVmzCDJUmbG/P83QJ3V9WNwLIky6rqS8AhQ6jX/JUkbW4Mr4GT7D7zAq4C/gn4KPC9Zt2C+h0Defuq+kayybAY67eksZIkLVH/AJwHPK5ZXktnRvjPjaxFmzKDJUnT7MdJdgTOAk5Ocj3DyUHzV5I0Kc6j020d4AF07j4OsCvwfeCAhQ7Q7x3INyR5UFMZSZ4LrNvy9kqSJsoYfvvaw4Oq6m3ce4fR7fQ5kcCQmMGSpM2Nf/7260g6k/O9GvgC8B1gGE8Kmb+SpM2N4TVw1zCNZwC/VlV7VNV96OTpqf0co987kI8FVgM/l+Qa4Ls4oYAkTbeCMZ+BdsZdSbbj3gvEBwF3jrZJmzCDJUmbmpwM7scbq+q1wEbgwwBJ/hp4bcv1mr+SpE2Nf/4+qqqOmVmoqs8n+Yt+Ci7YgZxkOfCyqnp6kh2AZVV16+LbKknSkvJ/6NzRtF+Sk4HHAy8eaYsaZrAkSTyDzTuLD++xbmDMX0nShLqhmRD2n+h0h/8ucGM/BRfsQK6qDUke2bz/6da0UpI0WTI+j7/OqarOTHI+nRneA7yqqm4YcbMAM1iSNLdJyOD5JHkZ8HLggUku7Nq0E/BfbdZt/kqS5jLm+XsUnRuoPkOnA/msZt2C+h3C4ptJTqMzqdA9AVpVfY2TIUmaUOMdnt2eBDyBzhmtpBOoS4UZLEna3ORk8Fw+Bnwe+L/A8V3rb62qm4ZQv/krSdrcGOdvk5+vSrJjVf1kS8r2O4ne7nRuaX4q8GvNa8GJC5Lsl+RLSdYkuSTJq5r1hyT5WpILkpyb5LA5yj8ryWVJrkhyfNf63ZOcmeTy5s/d+jwPSZI2keS9wDHARcDFwEuTvGe0rdqEGSxJmkZVVVfRGYv41q4XSXYfQv3mryRpoiR5XJJLgUub5Yc118ML6usO5Kp6ySLbth54TVWdn2Qn4LwkZwJvA97cDNZ8RLP85O6CzbhT76Ez5tVa4Jwkp1XVpXS+gf5iVb21CdXjaX8SBUnSZHoS8AtVNTOJ3ofpdCYvCWawJGlKfYxOh+15dO736p61qIAHtlm5+StJmkB/C/wycBpAVX0ryS/1U7CvDuQk7+qx+mbg3Kr67FzlqmodsK55f2uSNcA+dAJ/52a3XYBrexQ/DLiiqq5s2nAKcCSdXvIjuTdsPwx8GcNTkoZuzMd/mnEZ8ADge83yfsCFc+8+XGawJKmXCcngOVXVrzZ/HjCK+s1fSVIv456/VXV10v2dLBv6KdfvGMjbAj9HZ/wngOcAlwB/kOQpVXXcQgdIsj/wcODrwHHAGUneTmcYjcf1KLIPcHXX8lrg0c37+zXBTFWtS7Jnn+chSdJs9wHWJPlGs/wo4KvNuIdU1bNH1rIOM1iSNNWS/Cb3zlXwn1X1L0Oo1vyVJE2aq5M8Dqgkq4BXAmv6KdhvB/LPAk+tqvUASd4H/DudR2sWfMw3yY7Ap4HjquqWJH8JvLqqPp3kecCHgKfPLtbjUFvUz5/kaOBogPvsvc2WFJUk9aN6/Vc9dt446gYsYOwzeMXODtMoSQM3GRm8oGZsxp8FPt6sOibJM6rq2JarHvv83Zbtt6SoJKkf452/xwAn0PnC8hrgDDpzDSyo3w7kfYAd6DyyQ/N+76rakOTO+QomWUknOE/umrH2RcCrmvefAj7Yo+haOo8Rz9iXex/zuS7JXs03r3sB1/equ6pWA6sB9v+FHcf8JnNJWmKKsZ6BdkZVfQUgyc505eKQZnjvx9hn8HZ77TcBPymStIRMSAb3aVRzFYx9/u6c3afnp0SShmHI+ZvkWXQ6fJcDH6yqt86x36OArwHPr6p/nut4VXUD8DuLacuyPvd7G3BBkn9I8o/AN4G3J9kB+H9zFUpnUI0PAWuq6p1dm66l84sAdGa1vbxH8XOAA5Mc0NxW/QKaQZ6bP1/UvH8RMOcYVJIkzSfJ0UmuozPu8bl0Jus5d7St2oQZLEmaZjNzFcwY1lwF5q8kaWS6JlY9HDgYOCrJwXPs99d07iZe6JgPTPKvSX6Y5Pokn03S16S0fd2BXFUfSnI6nUH9A7y+qma+Cf3TeYo+HnghcFGSC5p1rwf+EDghyQrgDppHbJLsTadH/YiqWp/kFXT+ApYDJ1XVJc0x3gp8MskfAN8Hfquf85AkDdhk3Nfyp8BDmm9jlxwzWJLU02RkcD9GMleB+StJ6ml4+TvfxKrd/ojOUy+P6uOYH6PTKf0bzfIL6AwR9eg5SzT66kBuvkV9GvDAqnpLkgckOayqvjFfuao6m97jOAE8ssf+1wJHdC2fDpzeY78bm/ZIkkZo3GegbXwHuG3UjZiLGSxJ6mVCMrgfI5mrwPyVJPUywPzdI0n3k6+rm2GIZsw3sWqnLck+dDqDn0p/Hcipqo92Lf9T88XlgvodA/m9wMamQW8BbqX/3m1Jkpay1wH/neTrwD1jGlbVK0fXpE2YwZKkqTUzV8EImL+SpDbdUFWHzrO9n4lV/w54bTM+/9wHSnZv3n4pyfHAKc2xng/8Wz+N7bcD+dFV9Ygk3wSoqh81YzJJkqbZZNz99H7gP+hMyLNxxG3pxQyWJG1uMjJ4TknOrqonJLmVTc82QFXVzi03wfyVJG1uePk738SqMw4FTmk6j/cAjkiyvqr+ZdZ+59Fp+Uwv80u7thXwFws1pt8O5LubQZlnZr69L0vzIluSNEyTcfG6vqr+eNSNmIcZLEna3GRk8Jyq6gnNnzuNqAnmryRpc8PL33smVgWuoTNe8W9v0pSqA2beNxO+fq5H5/Em+y1Wvx3I7wI+A+yZ5K+A5wJv2NrKJUlaAr6U5GjgX9l0CIubRtekTZjBkqSpleQxwCVVdWuzvCOdyW+/3nLV5q8kaWTmmlg1yTHN9hP7PVaS31ygrlMXOkZfHchVdXKS8+gM2h/g16tqTV+tlCRNpNTETOAz8y3u67rWFfDAEbRlM2awJGm2CcrgfrwPeETX8m091g2c+StJmm3Y+dtrYtW5Oo6r6sXzHOrX5qsG2LoO5K5BlgGuBz7evW0J3Z0lSRqFmnug/nExiMd52mAGS5LmNQEZ3KdU1T2X61W1MUm/T9JueWXmryRpPmOYv1X1kq09xkLB2z3I8gOAHzXvdwW+DyzJi25J0pBMwN1PSbYH/hh4QFUdneRA4MFV9bkRN80MliTNbQIyuE9XJnklnbuOAV4OXNlifeavJGluY56/SX4FeAiw7cy6qnrLQuWWzbexqg6oqgfSGW/j16pqj6q6D/Cr9HF7syRJY+AfgLuAxzXLa4G/HF1zOsxgSZIAOIZORl9DJ6MfDRzdVmXmryRpUiU5EXg+8Ed0vhz9LeBn+ik7bwdyl0c1424AUFWfB560he2UJE2YmTGgtvY1Yg+qqrcBdwNU1e10wnSpMIMlSZuZgPztS1VdX1UvqKo9q+p+VfXbVXX9EKo2fyVJmxnza+DHVdXvAT+qqjcDjwX266dgvx3INyR5Q5L9k/xMkj8HblxkYyVJk6IG9Bqtu5JsN9OSJA8C7hxtkzZhBkuSNjf++duXJAcl+WKSi5vlhyZ5wxCqNn8lSZsb72vg25s/b0uyN52bqPoamqnfDuSjgPsCn2le923WSZI07t4EfAHYL8nJwBeB1460RZsygyVJ0+wDwOu490mhC4EXDKFe81eSNGk+l2RX4G+A84Gr6Josdj59zV7bzDT7qkU2TpI0icbo8df5VNW/JzkPeAydoSteVVU3jLhZ9zCDJUmbmZAM7tP2VfWNZJPRpda3Xan5K0nazJjnb1X9RfP200k+B2xbVTf3U3beO5CTvGmhA/SzjyRpQo334zsAJPliVd1YVf9WVZ+rqhuSfHG0rTKDJUkLGPP83QI3NMNLzQw19VxgXVuVmb+SpHlNwDUwQFXd2W/nMSx8B/L/SnLLPNtD5/GhN/VboSRJS0GSbYHtgT2S7Ma9E+ftDOw9sobdywyWJAmOBVYDP5fkGuC7wO+0WJ/5K0nSLAt1IH8A2KmPfSRJ02gJfHO6FV4KHEens/g87u1AvgV4z4ja1M0MliTNbbwzuC9JlgMvq6qnJ9kBWFZVt7ZcrfkrSZrbFORvL/N2IFfVm4fVEEnS+Bnz8Z9OAE5I8kdV9fejbs9sZrAkaT7jnMH9qqoNSR7ZvP/pkOo0fyVJcxrn/G2Gb3zaQut66WsSvUmwMhu574r5nkTaersuu63V4y9fsbHV4wNsnH9Y7IHYJne3Xse2y9utY7eDbm/1+ADrf7b9z+KqH+3eeh3X7Ltzq8ff9X4PbvX4ALtceVfrdSy7u/1/33z5n9uvYwwtxc7jSbNxFdy274bWjr/i1uWtHXvG8jtbrwJWtf//wF33a7mOu7PwPltpxU/a/7wr7dexYr92+8JueuyqVo8PcPueO7Zexx4Xb9d6Hbffp+Xfuc5t9/BT4JtJTgM+BdzzD6eqTh1dk8ZEAmn35zvL2v9/vza09zsEwIZb276pfTiyvP3s2nDV1a0eP1dc2erxAXa/cJfW67jPbru2Xsf1Vx7Qeh237N/uz9Rbf6b9c4CzhlDH0jeI4RunpgNZkiRJkjR2dgduBJ7ata4AO5AlSerPVg/faAeyJGnxhvT4TpL9gI8A9wc2Aqur6oQkhwAnAtsC64GXV9U3mjKvA/4A2AC8sqrOGE5rJUkagjF+hHZLVNVLRt0GSZLuMYb5O4jhG/t6niXJQUm+mOTiZvmhSd6wmAolSVqE9cBrqurngccAxyY5GHgb8OaqOgR4Y7NMs+0FwEOAZwHvbSbi2Uw6fjfJG5vlByQ5rO0T6pcZLEmaZkkemORfk/wwyfVJPpuk9eeezV9J0gT6QZKdAJK8IcmpSR7RT8F+B0T6APA64G6AqrqQzoW5JGlaVWcCgUG8Fqyqal1Vnd+8vxVYA+zTaQUzA23vAlzbvD8SOKWq7qyq7wJXAHN1Cr8XeCxwVLN8K30+xjMkZrAkaVNDyt8l4mPAJ4G96Dx6+ynglCHUa/5KkjY1xGvglvzvqro1yROAXwY+DLyvn4L9diBvP/NIcJf1W9BASdIkqgG9OoP5n9v1OnquKpPsDzwc+DqdcZz+JsnVwNvpXOhBp3O5e5aPtc26Xh5dVccCdwBU1Y+A9mef6p8ZLEna3GDydxykqj5aVeub1z8xnNabv5KkzQ3uGngUZmYl/RXgfVX1Wfq89u13DOQbkjyI5hSTPBdYt6WtlCRpDjdU1aEL7ZRkR+DTwHFVdUuSvwReXVWfTvI84EPA07l3UoBuc8X03c3wFjMZd1864ywvFWawJGmafSnJ8XTuOi7g+cC/JdkdoKpuaqle81eSNGmuSfJ+OtfMf51kG/q8ubjfDuRjgdXAzyW5Bvgu8LuLaakkaYIM8ZvTJCvpdB6fXFUzM6+/CHhV8/5TwAeb92uB/bqK78u9w1vM9i7gM8CeSf4KeC6wlMY4NIMlSZsbnzuIt9bzmz9fOmv979P5W3hgS/Wav5KkzY13/j6PzhxBb6+qHyfZC/jTfgr21YFcVVcCT0+yA7CsGX9SkjTFwvDGbkoSOncXr6mqd3ZtuhZ4EvBl4KnA5c3604CPJXknnfESDwRmP4ZKkmV0Lgj/DHgandP69apa086ZbDkzWJI02zAzeNSqqvUJ8+ao1/yVJG1i3PO3qm4DTk2yZ5IHNKu/3U/ZeTuQk/zxHOtnKn5nr+2SJA3Y44EXAhcluaBZ93rgD4ETkqygM4bx0QBVdUmSTwKX0hmv8Niq2jD7oFW1Mck7quqx9Bmcw2IGS5I0fOavJGlSJXk28A46N1ldDzyAznXwQxYqu9AdyDs1fz4YeBSdO7oAfg04azGNlSRNkCF9+1pVZ9N7XGOAR85R5q+Av+rj8P+e5DnAqVW1lL5PNoMlSXNbSok1WcxfSdLcxjt//wJ4DPD/qurhSZ4CHNVPwXk7kKvqzQBJ/h14xMxjO0neRGesSUnStKrxfnynyx8DOwDrk9xBp6O6qmrnUTbKDJYkzWlyMnjJMX8lSXMa//y9u6puTLIsybKq+lKSv+6nYL+T6D0AuKtr+S5g/y1spCRJS05V7bTwXiNlBkuSpk6SR8y3varOb7kJ5q8kadL8OMmOdJ6oOTnJ9XSGfFxQvx3IHwW+keQzdG7W/g3gI4tpqSRpgoz3t68AJPliVT1toXUjZAZLkjY3ARm8gHfMs63oTJ7bJvNXkrS58c7fI4HbgVcDvwPsAryln4J9dSBX1V8l+TzwxGbVS6rqm4toqCRpkoxxeCbZFtge2CPJbtw7xvLOdCYVWBLMYElST2Ocwf2oqqeMuH7zV5K0ufHO3z2BdVV1B/DhJNsB9wNuXKhgXx3ISR4A3AB8pntdVX1/ce2VJGnkXgocR6ezuPsx2FuA94yiQb2YwZKkaZfkF4CDgW1n1lVVq3cDm7+SpAn0KeBxXcsbmnWPWqhgv0NY/Bv39rFvBxwAXAY8pP82SpImzThPIFBVJwAnJPmjqvr7UbdnHmawJGkz45zBWyLJ/wGeTKcD+XTgcOBs2h9OwvyVJG1mzPN3RVXdM75/Vd2VZFVfBfvZqap+sXu5mdDgpVvUREnS5Bnv8JxxUpI3AA+oqqOTHAg8uKo+N+qGgRksSZrDZGRwP54LPAz4ZlW9JMn9gA+2Xan5K0nqabzz94dJnl1VpwEkOZLO0zYLWraY2poZbxe8vTnJfkm+lGRNkkuSvKpZ/4kkFzSvq5Jc0KPsg7v2uSDJLUmOa7a9Kck1XduOWMx5SJIEnERnZvWZR3nWAn85uubMzwyWJA1TkmcluSzJFUmO77E9Sd7VbL+w6WhdsGySP2q2XZLkbfM04faq2gisT7IzcD3wwEGdX7/MX0nSBDgGeH2Sq5N8H3gtfX452u8YyH/ctbgMeATwwz6KrgdeU1XnJ9kJOC/JmVX1/K5jvwO4eXbBqroMOKTZZzlwDV3jTwF/W1Vv76f9kqQWFOP+7euMB1XV85McBVBVtyfJQoWGxQyWJG1mSBncZMB7gGfQ+YL1nCSnVdWlXbsdDhzYvB4NvA949HxlkzyFzkzwD62qO5PsOU8zzk2yK/AB4DzgJ8A3BnmevZi/kqTNjPk1cFV9B3hMkh2BVNWt/Zbtdwzknbrer6czHtSn+2jYOmBd8/7WJGuAfYBLofNtNfA84KkLHOppwHeq6nt9tleSNARjPv7TjLvSmX22AJI8CLhztE3ahBksSdrMkDL4MOCKqroSIMkpdDp+uzuQjwQ+UlUFfC3Jrkn2Avafp+zLgLdW1Z0AVXX9XA2oqpc3b09M8gVg56q6cIDnOBfzV5K0mXG+Bk5nGKj/D9i7qg5PcjDw2Kr60EJl++1AvrSqPjWr0t+iM1Nfv43cH3g48PWu1U8Erquqyxco/gLg47PWvSLJ7wHn0vmG90c96jwaOBrgvnuv7LepkqTp8n+ALwD7JTkZeDzw4pG2aFNjn8HLd9+136ZKkpaWfYCru5bX0rnLeKF99lmg7EHAE5P8FXAH8CdVdU6vBiT5YlU9DaCqrpq9rkVjn7/bsn2/TZUkTYd/BP4B+PNm+X+ATwALdiD3Owby6/pc11Nza/SngeOq6pauTUexeSjOLrsKeDabBvX7gAfRebxnHfCOXmWranVVHVpVh+6ye7995ZKkvtWAXiNUVWcCv0mn0/jjwKFV9eVRtmmWsc/g5Tvu2G9zJUn9Gkz+7pHk3K7X0bNq6TWk0+zknmuf+cquAHYDHgP8KfDJ2cNHJdk2ye5NG3dLsnvz2h/Yu8exB23s83dltu23uZKkfo33NfAeVfVJYCNAVa0HNvRTcN5e1SSHA0cA+yR5V9emnek8xrOgJCvpBOfJVXVq1/oVdC7YH7nAIQ4Hzq+q62ZWdL9P8gHgc/20RZI0WOP8+M4s+wDL6eTiLyWhO7NGwQyWJM1nQBl8Q1UdOs/2tcB+Xcv7Atf2uc+qecquBU5thr34RpKNwB5sOsbwS4Hj6HQWn9+1/hY6Yyu3wvyVJM1nzK+Bf5rkPtw7fONj6DEmfy8L3ZZ7LZ3HY55NZ8KCGbcCr17o4M23yB8C1lTVO2dtfjrw7apau8BhNvuGNslezdhSAL8BXLxQWyRJLRjv8AQgyUnAQ4FLaL6JpXNmI+1AxgyWJM1nOBl8DnBgkgPoTOj2AuC3Z+1zGp2hFU6hM0TFzVW1LskP5yn7L3TGAP5ykoPodDbf0H3QqjoBOCHJH1XV37dydr2Zv5KkuY33NfAf08ntByX5L+C+wHP7KThvB3JVfQv4VpKTm9uat9TjgRcCFyW5oFn3+qo6nR5jOiXZG/hgVR3RLG9PZ9bel8467tuSHELnY7uqx3ZJkvr1mKo6eNSNmM0MliSNWlWtT/IK4Aw6T+qcVFWXJDmm2X4icDqdO3avAG4DXjJf2ebQJwEnJbkYuAt4UXM3ci/vT/JK4Jea5S8D76+quwd7th3mryRpEiVZDjypeT2YzlBTl/WbpwsNYfHJqnoe8M1k85u0q+qh85WvqrPpPfYVVfXiHuuupfPLx8zybcB9euz3wvnqlSQNwRIYv3hAvprk4Kq6dOFdh8cMliTNaYgZ3HR8nj5r3Yld7ws4tt+yzfq7gN/tswnvBVY2f0Knc/Z9wP/qs/wWMX8lSXMa42vgqtqQ5Miq+ls6T99ukYWGsHhV8+evbnHLJEkTLcxxdTR+PkynE/kHwJ10TqsWukAcAjNYktTTBGXwnJKsaO4AflRVPaxr038k+VaLVZu/kqSeJiB//yvJu4FPAD+dWVlV589dpGOhISxmxlh6eVW9tntbkr8GXrt5KUmSxspJNI+acu8YyCNnBkuSptw3gEcAG5I8qKq+A5DkgfQ5Y/ximL+SpAn2uObPt3StKzrzEsxrWZ8VPKPHusP7LCtJmlQ1oNdofb+qTquq71bV92Zeo25UFzNYkrS58c/fhczc5PUnwJeSfDnJl4H/AF4zhPrNX0nS5sb4GriqntLjtWDnMSw8BvLLgJcDD0xyYdemnYD/WnyTJUmTYPORAcfSt5N8DPhXOkNYAFBVp46uSWawJGl+E5LB87lvkj9u3r+fzkR8PwW2BR4OfKmNSs1fSdJ8xjl/k+wC/B/unZj2K8BbqurmhcouNAbyx4DPA/8XOL5r/a1VddMi2ipJ0lKzHZ2O42d2rStgpB3ImMGSpOm2HNiRTYeb3LH5c6cW6zV/JUmT6iTgYuB5zfILgX8AfnOhgguNgXwzcDNwFECSPel847tjkh2r6vtb0WhJ0rgb429fZ1TVS0bdhl7MYEnSvCYggxewrqresvBug2X+SpLmNd75+6Cqek7X8puTXNBPwb7GQE7ya0kuB75L5/bmq+h8KytJmmZjPP7TuDCDJUk9TX7+jnSie/NXktTTeF8D357kCTMLSR4P3N5PwX4n0ftL4DHA/1TVAcDTcPwnSZKGwQyWJE2jp424fvNXkjRpjgHek+SqJFcB7wZe2k/BfjuQ766qG4FlSZZV1ZeAQxbTUknShKjOBAKDeGleZrAkaVNTkL9LYLxh81eStKkxvQZO8gCAqvpWVT0MeCjw0Kp6eFVdOH/pjoUm0Zvx4yQ7AmcBJye5Hli/mEZLkibIEr/4XEiSnwP2Ab5eVT/pWv+sqvrC6Fq2CTNYkrS5Mc/gMWD+SpI2N575+y/AIwCSfHrWOMh96fcO5CPpjInxauALwHeAX9vSyiRJWiqSvBL4LPBHwMVJjuza/P+NplU9mcGSJA2f+StJmhTd8wo8cDEH6OsO5Kr6adfihxdTkSRp8iz1x18X8IfAI6vqJ0n2B/45yf5VdQIjnrinmxksSeplzDN4yTN/JUm9jGn+1hzv+zZvB3KSW+c4cICqqp0XU6kkaUKMZ3jOWD4zbEVVXZXkyXQ6kX+GJdCBbAZLkuY13hm8ZJm/kqR5jWf+PizJLXSybLvmPWxBts3bgVxVO219GyVJWpJ+kOSQqroAoLkT+VeBk4BfHGnLMIMlSRoF81eSNGmqavnWHqPfSfQkSdrMmD6+M+P3mDUZTlWtB34vyftH0yRJkvoz5hksSdJYmtb8nZoO5O1yN7+46oejbsZW2TiEOpavWjeEWtq344o7Wj3+zeu3b/X4ACuzofU69tn+5tbr+PryB7R6/Jvvv22rxwe46aHbtF7HsrtXtl4HXx7w8YpxfXwHgKpaO8+2/xpmWybditvgPudv9Zfec1q2of0fxGXrF95na931g/Z/LVvf8n+Zt9+//c+i+p0Ceiusurn9UWyW/XDHVo+/cddWDw/ALk+4vvU6lj/57tbrOGC7ny6801Y470MtHHTMM1hDUgXV7lVktX/JQm1s+Yc9QwiWCVEbhvCBt2zDLbe2Xseyu+5qvY4dP9d+383OB7R7LV+r2v/d96pBH3CK89f/KSVJkiRJkiRJPU3NHciSpBZM6bevkiSNnBksSdLwTWn+2oEsSVqUML3jP0mSNEpmsCRJwzfN+esQFpIkSZIkSZKknrwDWZK0eFP67askSSNnBkuSNHxTmr92IEuSFi01pekpSdKImcGSJA3ftOavQ1hIkiRJkiRJknqyA1mStDg1wJckSeqf+StJ0vAN+Ro4ybOSXJbkiiTH99h+ZJILk1yQ5NwkT9i6E5ybQ1hIkhZtWmeglSRp1MxgSZKGb1j5m2Q58B7gGcBa4Jwkp1XVpV27fRE4raoqyUOBTwI/10Z7vANZkiRJkiRJkpaOw4ArqurKqroLOAU4snuHqvpJ1T2DMu9Ai88XeQeyJGnxvPtJkqTRMIMlSRq+weXvHknO7VpeXVWru5b3Aa7uWl4LPHr2QZL8BvB/gT2BXxlY62axA1mStGg+PitJ0miYwZIkDd8A8/eGqjp0vqp6rNus9qr6DPCZJL8E/AXw9AG1bxMOYSFJkiRJkiRJS8daYL+u5X2Ba+fauarOAh6UZI82GmMHsiRp8ZwFXpKk0TB/JUkavuFdA58DHJjkgCSrgBcAp3XvkORnk6R5/whgFXDjVp3fHBzCQpK0OOXjs5IkjYQZLEnS8A0xf6tqfZJXAGcAy4GTquqSJMc0208EngP8XpK7gduB53dNqjdQdiBLkhbPi1dJkkbDDJYkafiGmL9VdTpw+qx1J3a9/2vgr4fRFoewkCRJkiRJkiT11OodyEn2Az4C3B/YCKyuqhOSfAJ4cLPbrsCPq+qQHuWvAm4FNgDrZ2YnTLI78Algf+Aq4HlV9aMWT0WSNEvw8dmlzAyWpMllBi9d5q8kTa5pzt+2h7BYD7ymqs5PshNwXpIzq+r5MzskeQdw8zzHeEpV3TBr3fHAF6vqrUmOb5ZfO+jGS5IW0M7wSpvZ0ouxJPsDa4DLmm1fq6pjhtLYpcMMlqRJNqQM1hYzfyVpkk1p/rbagVxV64B1zftbk6wB9gEuBWhmCnwe8NQtPPSRwJOb9x8GvozhKUmTbDEXY9/pdWfPtDCDJUkaPvNXkjSJhjYGcnM32MOBr3etfiJwXVVdPkexAv49yXlJju5af78mmGcCes856jw6yblJzr3xpo1bfQ6SpE2lBvNaSFWtq6rzm/e30rm7eJ972nHvxdjH2znT8TbqDF5/x0+3+hwkSZsaRv5q64w6f+/mzq0+B0nSpoZ1DbzUtD2EBQBJdgQ+DRxXVbd0bTqK+S/2H19V1ybZEzgzyber6qx+662q1cBqgIc+dOUYfjyStIQVg5yBdo8k53Ytr27+D9/MFlyMHZDkm8AtwBuq6j8H1toxshQyeIf77mcGS9IgDTaD1YKlkL87Z3d/SiRpkKY4f1vvQE6ykk5wnlxVp3atXwH8JvDIucpW1bXNn9cn+QxwGHAWcF2SvapqXZK9gOvbPAdJUutumJkkZj5bcDG2DnhAVd2Y5JHAvyR5yKwyE88MliRp+MxfSdKkaXUIi+aR4g8Ba6rqnbM2Px34dlWtnaPsDs04lyTZAXgmcHGz+TTgRc37FwGfHXTbJUkLy8bBvPqqa+GLsU/MrKuqO6vqxub9ecB3gIMGd+ZLnxksSZNtWPmrLWP+StJkG+Y18FLS9hjIjwdeCDw1yQXN64hm2wuY9ehOkr2TnN4s3g84O8m3gG8A/1ZVX2i2vRV4RpLLgWc0y5KkYasBvRawpRdjSe6bZHnz/oHAgcCVizzLcWUGS9IkG0L+alHMX0maZEO6Bl5qWh3CoqrOBjLHthf3WHctcETz/krgYXOUvRF42sAaKkla6mYuxi5KckGz7vVVdTo9LsaAXwLekmQ9sAE4pqpuGlZjlwIzWJKk4TN/JUmTaCiT6EmSJtOwZo9dxMXYp+kMdyFJ0kQaxxncJUkad9Oav3YgS5IWp4Ca0vSUJGmUzGBJkoZvivO37TGQJUmSJEmSJEljyjuQJUmLNq2P70iSNGpmsCRJwzet+WsHsiRp8aY0PCVJGjkzWJKk4ZvS/HUIC0mSJEmSJElST96BLElalDC9j+9IkjRKZrAkScM3zflrB7IkaXGqpnYGWkmSRsoMliRp+KY4fx3CQpIkSZIkSZLUk3cgS5IWbVof35EkadTMYEmShm9a89c7kCVJi1cDekmSpC0zpPxN8qwklyW5IsnxPbYnybua7RcmecQWlP2TJJVkjy05dUmSRmZKr4HtQJYkSZIkbSbJcuA9wOHAwcBRSQ6etdvhwIHN62jgff2UTbIf8Azg+y2fhiRJ2kp2IEuSFi01mJckSdoyQ8rfw4ArqurKqroLOAU4ctY+RwIfqY6vAbsm2auPsn8L/BljeR+WJGlaTes1sGMgS5IWp4CNY5h8kiSNu8Fl8B5Jzu1aXl1Vq7uW9wGu7lpeCzx61jF67bPPfGWTPBu4pqq+lWTrzkCSpGGZ4mtgO5AlSZIkaTrdUFWHzrO9V+/u7CvnufbpuT7J9sCfA8/sr4mSJGnUpqYDeWWWsdfy7VqtYz0bWj3+MCzjjtbr2Hv777Zex00b2v3RvnHj9q0eH+COWtl6Hddus1vrdey97Y9bPf7aO9o/hxv33aH1On5857at19HKv7zp/PJVW2jZ3cUO161vr4Ih3LyW9e3/sC+/c3nrdaz8Sbu/q9zxw/Z/tbz9Pu1/4Cva/3WIavs0hvDv4oab28/H++9+S+t17LLq9tbraMVwMngtsF/X8r7AtX3us2qO9Q8CDgBm7j7eFzg/yWFV9YOBtn7KZdkylm3X7jUww7iDfGXL2TKMuwnXt/h7UKM2bmy9jlS7f1cb77iz1eMDZFn7P7N1113t1zGEn9v6zvfaPf6GMe1Dm9Jr4KnpQJYkDd44jt0kSdIkGFIGnwMcmOQA4BrgBcBvz9rnNOAVSU6hM0TFzVW1LskPe5WtqkuAPWcKJ7kKOLSqbmj9bCRJ2krTeg1sB7IkSZIkaTNVtT7JK4AzgOXASVV1SZJjmu0nAqcDRwBXALcBL5mv7AhOQ5IkbSU7kCVJi9fyY2ySJGkOQ8rgqjqdTidx97oTu94XcGy/ZXvss//Wt1KSpCGZ0mtgO5AlSYs2rY/vSJI0amawJEnDN635u2zUDZAkSZIkSZIkLU3egSxJWpxiameglSRppMxgSZKGb4rz1w5kSdKiBMiUjv8kSdIomcGSJA3fNOevHciSpMXbOOoGSJI0pcxgSZKGb0rz1zGQJUmSJEmSJEk9eQeyJGnRpvXxHUmSRs0MliRp+KY1f+1AliQtzhRPICBJ0kiZwZIkDd8U569DWEiSJEmSJEmSevIOZEnSIhVM6eM7kiSNlhksSdLwTW/+2oEsSVq0TGd2SpI0cmawJEnDN6356xAWkiRJkiRJkqSevANZkrR4U/r4jiRJI2cGS5I0fFOav3YgS5IWpyAbR90ISZKmkBksSdLwTXH+tjqERZL9knwpyZoklyR5VbP+E0kuaF5XJbmg37LNtjcluabrGEe0eR6SJI0bM1iSpOEzfyVJk6jtO5DXA6+pqvOT7AScl+TMqnr+zA5J3gHcvAVlL222/21Vvb3l9kuS5jOlj++MCTNYkiaZGbxUmb+SNMmmNH9b7UCuqnXAuub9rUnWAPsAlwIkCfA84KlbWlaStARMZ3aOBTNYkiacGbwkmb+SNOGmNH9bHcKiW5L9gYcDX+9a/UTguqq6fBFlX5HkwiQnJdltjnJHJzk3ybk/vHHDVrVfkqRxNeoMvvuun25V+yVJGkejzt+76o6tar8kSTOG0oGcZEfg08BxVXVL16ajgI8vouz7gAcBh9D5hvYdvcpW1eqqOrSqDr3vfZZv3UlIkjaTqoG81J6lkMErV+2wdSchSdqM+bu0LYX8XZVtt+4kJEmbmdZr4LbHQCbJSjrhd3JVndq1fgXwm8Ajt7RsVV3Xtc8HgM+10HRJ0kLGMPimiRksSRPMDF6yzF9JmmBTmr+t3oHcjO/0IWBNVb1z1uanA9+uqrVbWjbJXl2LvwFcPLhWS5I0/sxgSZKGz/yVJE2itoeweDzwQuCpSS5oXkc0217ArEd3kuyd5PQ+yr4tyUVJLgSeAry65fOQJM1WwMYBvdQGM1iSJtWgMlhtMH8laVJN8TVwq0NYVNXZQObY9uIe664Fjuij7AsH10pJ0mKE8Ry7aVqYwZI0uczgpcv8laTJNc35O5RJ9CRJkiRJkiRJ46f1SfQkSRNsSr99lSRp5MxgSZKGb0rz1w5kSdLiTWl4SpI0cmawJEnDN6X56xAWkiRJkiRJkqSevANZkrQ4MzPQSpKk4TKDJUkavinOXzuQJUmLNq0z0EqSNGpmsCRJwzet+esQFpIkSZIkSZKknrwDWZK0eFP67askSSNnBkuSNHxTmr/egSxJWqTqhOcgXpIkaQuYv5IkDd9wr4GTPCvJZUmuSHJ8j+2/k+TC5vXfSR428FNu2IEsSVrykuyX5EtJ1iS5JMmrmvWfSHJB87oqyQVdZV7XBO1lSX55ZI2XJEmSJGkLJFkOvAc4HDgYOCrJwbN2+y7wpKp6KPAXwOq22uMQFpKkxSmGeffSeuA1VXV+kp2A85KcWVXPn9khyTuAm5v3BwMvAB4C7A38vyQHVdWGYTVYkqTWDDeDJUkSDDt/DwOuqKorAZKcAhwJXHpPc6r+u2v/rwH7ttUYO5AlSYu3cTjVVNU6YF3z/tYka4B9aMIzSYDnAU9tihwJnFJVdwLfTXIFnQD+6nBaLElSy4aUwZIkqcvg8nePJOd2La+uqu47iPcBru5aXgs8ep7j/QHw+YG1bhY7kCVJS8FC4XmPJPsDDwe+3rX6icB1VXV5s7wPnW9gZ6xt1kmSJEmSNGo3VNWh82xPj3U9b39O8hQ6HchPGETDerEDWZK0aBnc4zsLhWenvmRH4NPAcVV1S9emo4CPd+/ao7jP+kqSJsYAM1iSJPVpiPm7Ftiva3lf4NrN2pM8FPggcHhV3dhWY+xAliQt3hAvXpOspNN5fHJVndq1fgXwm8Aju3bvK2wlSRpbdiBLkjR8w8vfc4ADkxwAXENnjp/f7t4hyQOAU4EXVtX/tNmYqelADmFl2j3dlRPw17nvipWt17GMZa3Xsc/ydo9/Z93VbgXAbfXT9utY1dqXU/e4epvtWj3+j3fYvtXjA/zg7l1br+O69Tu3XseXB33AAjYOJzybMY4/BKypqnfO2vx04NtVtbZr3WnAx5K8k84kegcC3xhKY7W5hFre66bwwaj2Y4Usa6/9MzYO4deIWtHueWz/g7tbPT7Aqlva/8AzhLFlN7b8WSxb3/IvQ8Cqs3ZovY6bt22/ji/tdf/W6xi4IWawxtiyZWT7dn8XH0pHyrKW/99f2f41MHe3n4/t/6YCbGw3ILNiGL8MTcb/nRvvuHPUTdhqy1YO4fMe9F/TEPO3qtYneQVwBrAcOKmqLklyTLP9ROCNwH2A93YumVnfz5O9izH+PZ6SpGnweOCFwEVJLmjWvb6qTqfzTWz38BU0wfpJOpPsrQeOraoNQ2yvJEmSJEmL1lzvnj5r3Yld7/8X8L+G0RY7kCVJi1RD+wa/qs5mjhsrqurFc6z/K+CvWmyWJEkjMrwMliRJM6Y3f+1AliQt3pSGpyRJI2cGS5I0fFOav0MYNVCSJEmSJEmSNI68A1mStHhT+u2rJEkjZwZLkjR8U5q/diBLkhbHGeAlSRoNM1iSpOGb4vx1CAtJkiRJkiRJUk/egSxJWqSC2jjqRkiSNIXMYEmShm9689cOZEnS4k3p+E+SJI2cGSxJ0vBNaf46hIUkSZIkSZIkqSfvQJYkLc4UTyAgSdJImcGSJA3fFOevHciSpMWb0sd3JEkaOTNYkqThm9L8dQgLSZIkSVJPSZ6V5LIkVyQ5vsf2JHlXs/3CJI9YqGySv0ny7Wb/zyTZdUinI0mSFsEOZEnS4lUN5iVJkrbMEPI3yXLgPcDhwMHAUUkOnrXb4cCBzeto4H19lD0T+IWqeijwP8DrtvavQ5KkoZjSa2CHsJAkLdJ4Bp8kSeNvaBl8GHBFVV0JkOQU4Ejg0q59jgQ+UlUFfC3Jrkn2Avafq2xV/XtX+a8Bz239TCRJ2mrTew3sHciSJEmSpF72Aa7uWl7brOtnn37KAvw+8PmtbqkkSWqNdyBLkhangI0bR90KSZKmz+AyeI8k53Ytr66q1V3LmaN2+thnwbJJ/hxYD5zcR1slSRqtKb4GbvUO5CT7JflSkjVJLknyqmb9J5Jc0LyuSnLBHOXnmnRh9yRnJrm8+XO3Ns9DkjSHKR3/aRyYwZI04QaTvzdU1aFdr9WzalkL7Ne1vC9wbZ/7zFs2yYuAXwV+pxn+YiKYv5I04ab0GrjtISzWA6+pqp8HHgMcm+Tgqnp+VR1SVYcAnwZOnV1wgUkXjge+WFUHAl9sliVJ0r3MYEnS1joHODDJAUlWAS8ATpu1z2nA76XjMcDNVbVuvrJJngW8Fnh2Vd02rJMZEvNXkjRxWu1Arqp1VXV+8/5WYA1d414lCfA84OM9it8zYUNV3QXMTLpA8+eHm/cfBn69lROQJM1vSr99HQdmsCRNuCHkb1WtB14BnEEnRz5ZVZckOSbJMc1upwNXAlcAHwBePl/Zpsy7gZ2AM5s7ck8c2N/LiJm/kjThpvQaeGhjICfZH3g48PWu1U8Erquqy3sU6TXpwqOb9/drvtWmqtYl2XOOOo8GjgZ4wD4O9yxJg1WwcfyCbxqNOoO32W7XrWm+JGkzw8vgqjqdTidx97oTu94XcGy/ZZv1PzvgZi5Jo87fbZftuFXtlyTNNr3XwG0PYQFAkh3pPKZzXFXd0rXpKHp/8wr9Tdgwr6paPTOe133vs3xLikqSNBGWQgav3MYLWEnSdFkK+btq2XZbUlSSpDm1fltukpV0gvPkqjq1a/0K4DeBR85RdL5JF65LslfzzetewPWDb7kkaV4FVdM5A+24MIMlaUKZwUua+StJE2qK87fVO5Cb8Z0+BKypqnfO2vx04NtVtXaO4vNN2HAa8KLm/YuAzw625ZKkvmyswbw0cGawJE0483dJMn8lacJN6TVw20NYPB54IfDUZnKEC5Ic0Wx7AbMe3Umyd5LTYcFJF94KPCPJ5cAzmmVJknQvM1iSpOEzfyVJE6fVISyq6mx6j+NEVb24x7prgSO6lueadOFG4GkDa6gkaXHGcPbYaWEGS9KEM4OXJPNXkibclOZv62MgS5ImVBVsnM7xnyRJGikzWJKk4Zvi/G17CAtJkiRJkiRJ0pjyDmRJ0uJN6eM7kiSNnBksSdLwTWn+2oEsSVq0mtLHdyRJGjUzWJKk4ZvW/HUIC0mSJEmSJElST96BLElapJrax3ckSRotM1iSpOGb3vy1A1mStDgFbJzO8JQkaaTMYEmShm+K89chLCRJkiRJkiRJPXkHsiRp8Wo6JxCQJGnkzGBJkoZvSvPXDmRJ0qIUUFP6+I4kSaNkBkuSNHzTnL92IEuSFqdqar99lSRppMxgSZKGb4rz1zGQJUmSJEmSJEk9eQeyJGnRpvXxHUmSRs0MliRp+KY1f+1AliQt3pQ+viNJ0siZwZIkDd+U5q9DWEiSJEmSJEmSekrVdNx6neSHwPe2oMgewA0tNWeYJuE8JuEcYDLOYxLOASbjPBZzDj9TVfcdVAOSfKFpxyDcUFXPGtCxtMRMaQZPwjnAZJzHJJwDTMZ5TMI5wJafx0DzFwaawebvBFtE/sJk/DudhHOAyTiPSTgHmIzzmIRzgBFn8DRfA09NB/KWSnJuVR066nZsrUk4j0k4B5iM85iEc4DJOI9JOAdpLpPw8z0J5wCTcR6TcA4wGecxCecAk3MeUi+T8PM9CecAk3Eek3AOMBnnMQnnAJNzHuPIISwkSZIkSZIkST3ZgSxJkiRJkiRJ6skO5LmtHnUDBmQSzmMSzgEm4zwm4RxgMs5jEs5Bmssk/HxPwjnAZJzHJJwDTMZ5TMI5wOSch9TLJPx8T8I5wGScxyScA0zGeUzCOcDknMfYcQxkSZIkSZIkSVJP3oEsSZIkSZIkSerJDmRJkiRJkiRJUk9T2YGc5NVJLklycZKPJ9m2a9ufJKkke8xR9llJLktyRZLjh9fqzdqxNedwVZKLklyQ5NzhtbpnWzY7jyRvSnJN074LkhwxR9kl+1lswTks6c+iWf9Hzd/zJUneNkfZJftZNOv7OYcl/Vkk+UTXz9NVSS6Yo+yS+CykXiYhf5u2jH0GT0L+Nm0Z+wyehPxt2jL2GWz+apJNQgZPQv42bTGDl8jnYQYv7c/CDF5iqmqqXsA+wHeB7ZrlTwIvbt7vB5wBfA/Yo0fZ5cB3gAcCq4BvAQeP0zk0+1w117alcB7Am4A/WaDskv4s+jmHMfksngL8P2CbZv2eY/hZLHgO4/BZzNrnHcAbl+pn4ctXr9ck5O/Wnkezz8j/r5mE/N3a8xiDz2Js8ndrz2Opfxaz9jF/fY3laxIyeBLyd77zMIOX1DmYwUvkHGbtYwaP+DWVdyADK4DtkqwAtgeubdb/LfBnwFwzCx4GXFFVV1bVXcApwJFtN3YOiz2HpWau81jIOHwW46bXebwMeGtV3QlQVdf3KLfUP4t+zmGpmfNnKkmA5wEf71FuKX0WUi+TkL8wGRk8CfkLk5H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      "text/plain": [
       "<Figure size 1440x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot multiple: \n",
    "\n",
    "# fig, axes = plt.subplots(1, 5, figsize = (25,6))\n",
    "fig, axes = plt.subplots(1, 3, figsize = (20,6))\n",
    "# plt.title('mean vallues 1990-2021')\n",
    "\n",
    "t2m_mean [:,:].plot(ax=axes[0])  # \n",
    "tp_mean  [:,:].plot(ax=axes[1])  # \n",
    "fal_mean [:,:].plot(ax=axes[2])  # \n",
    "# sd_mean  [:,:].plot(ax=axes[3])  # \n",
    "# slhf_mean[:,:].plot(ax=axes[4])  # only 2 indexes needed for coordinates\n",
    "\n",
    "# fig.suptitle('title', fontsize=16, y=1.02)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0701ae2f-eba3-4c81-9cd6-fc288d836638",
   "metadata": {},
   "outputs": [
    {
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       "  --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-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",
       "  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",
       "  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-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-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",
       "  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;\n",
       "Dimensions:    (longitude: 13, latitude: 9)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 84.0 84.25 84.5 84.75 ... 86.5 86.75 87.0\n",
       "  * latitude   (latitude) float32 29.0 28.75 28.5 28.25 ... 27.5 27.25 27.0\n",
       "Data variables:\n",
       "    t2m        (latitude, longitude) float32 271.2 268.7 267.5 ... 293.6 292.4\n",
       "    fal        (latitude, longitude) float32 0.3633 0.4273 ... 0.1421 0.1446\n",
       "    sd         (latitude, longitude) float32 0.02584 0.04403 ... 7.575e-07\n",
       "    slhf       (latitude, longitude) float32 -2.394e+06 ... -6.342e+06\n",
       "    tp         (latitude, longitude) float32 0.001671 0.001676 ... 0.007178\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-28 15:24:18 GMT by grib_to_netcdf-2.24.2: /opt/ecmw...</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-282ac8a6-ad46-4ad5-95c3-f9d6cc41e5b5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-282ac8a6-ad46-4ad5-95c3-f9d6cc41e5b5' 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'>longitude</span>: 13</li><li><span class='xr-has-index'>latitude</span>: 9</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-16106e2b-5d5e-4acb-986f-584649f7d653' class='xr-section-summary-in' type='checkbox'  checked><label for='section-16106e2b-5d5e-4acb-986f-584649f7d653' 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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>84.0 84.25 84.5 ... 86.5 86.75 87.0</div><input id='attrs-627ab17e-52c8-4a31-a631-952ba0a1edfd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-627ab17e-52c8-4a31-a631-952ba0a1edfd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fc2facc-d501-491e-a6ef-bd0fb5b7060e' class='xr-var-data-in' type='checkbox'><label for='data-7fc2facc-d501-491e-a6ef-bd0fb5b7060e' title='Show/Hide data repr'><svg 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><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([84.  , 84.25, 84.5 , 84.75, 85.  , 85.25, 85.5 , 85.75, 86.  , 86.25,\n",
       "       86.5 , 86.75, 87.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>29.0 28.75 28.5 ... 27.5 27.25 27.0</div><input id='attrs-48093299-213a-489a-9f7b-8864786953c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48093299-213a-489a-9f7b-8864786953c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c43b0c3e-39a7-436d-83bc-f22d3fe657d2' class='xr-var-data-in' type='checkbox'><label for='data-c43b0c3e-39a7-436d-83bc-f22d3fe657d2' title='Show/Hide data repr'><svg 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><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([29.  , 28.75, 28.5 , 28.25, 28.  , 27.75, 27.5 , 27.25, 27.  ],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ca5ebaa3-e726-44b1-a3fa-f4863188e24f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ca5ebaa3-e726-44b1-a3fa-f4863188e24f' 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>t2m</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>271.2 268.7 267.5 ... 293.6 292.4</div><input id='attrs-a06dd73c-0d2c-462b-8d43-69ccd21992b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a06dd73c-0d2c-462b-8d43-69ccd21992b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-477537ed-4646-4269-bce0-0d48b06c8682' class='xr-var-data-in' type='checkbox'><label for='data-477537ed-4646-4269-bce0-0d48b06c8682' title='Show/Hide data repr'><svg 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>long_name :</span></dt><dd>2 metre temperature</dd></dl></div><div class='xr-var-data'><pre>array([[271.22028, 268.73843, 267.51938, 268.27597, 268.09677, 267.82785,\n",
       "        269.4283 , 270.2579 , 270.32004, 269.97617, 270.62973, 271.56058,\n",
       "        272.8085 ],\n",
       "       [268.95786, 266.69415, 266.38705, 267.79367, 267.18988, 268.15018,\n",
       "        269.59677, 269.4288 , 269.74774, 270.47964, 271.26572, 271.73978,\n",
       "        271.92514],\n",
       "       [274.70233, 274.332  , 273.7365 , 271.7954 , 270.03635, 270.64328,\n",
       "        267.71652, 266.3951 , 266.85574, 269.26285, 271.14005, 273.2671 ,\n",
       "        273.76526],\n",
       "       [289.0708 , 289.58267, 287.31647, 282.70572, 280.0374 , 278.42856,\n",
       "        272.37888, 268.00552, 266.77145, 266.71616, 266.93344, 268.26398,\n",
       "        268.84122],\n",
       "       [293.53622, 294.21317, 293.77353, 291.38574, 289.81668, 288.2423 ,\n",
       "        283.9691 , 280.5553 , 278.5179 , 274.05243, 267.94458, 266.24503,\n",
       "        266.23123],\n",
       "       [294.56387, 295.33405, 295.46262, 293.7035 , 291.78793, 290.32303,\n",
       "        289.27222, 289.04672, 286.566  , 282.15518, 276.74283, 272.78226,\n",
       "        272.33698],\n",
       "       [296.66446, 296.68332, 296.58087, 295.55264, 293.64682, 292.42874,\n",
       "        291.71063, 291.94702, 290.6428 , 286.95905, 285.38834, 282.89325,\n",
       "        282.20023],\n",
       "       [297.90445, 297.74176, 297.6506 , 296.68048, 296.76328, 295.8863 ,\n",
       "        295.01007, 294.7003 , 293.48572, 292.08884, 290.543  , 289.43423,\n",
       "        288.442  ],\n",
       "       [298.1993 , 298.18942, 298.1964 , 298.0607 , 298.14383, 298.2628 ,\n",
       "        297.76584, 297.37607, 296.8121 , 295.41214, 294.67322, 293.5587 ,\n",
       "        292.42212]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fal</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.3633 0.4273 ... 0.1421 0.1446</div><input id='attrs-a8c1a956-5f93-475c-81d3-77dd2707ab7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8c1a956-5f93-475c-81d3-77dd2707ab7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b8b5cbd-d93b-4040-949a-2b80b17a70a1' class='xr-var-data-in' type='checkbox'><label for='data-2b8b5cbd-d93b-4040-949a-2b80b17a70a1' title='Show/Hide data repr'><svg 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>(0 - 1)</dd><dt><span>long_name :</span></dt><dd>Forecast albedo</dd></dl></div><div class='xr-var-data'><pre>array([[0.3633202 , 0.427267  , 0.43438008, 0.3928168 , 0.40847448,\n",
       "        0.46347204, 0.38578188, 0.32224804, 0.29408684, 0.2901497 ,\n",
       "        0.268401  , 0.24310136, 0.21369876],\n",
       "       [0.45609942, 0.579802  , 0.5896097 , 0.49082366, 0.54664874,\n",
       "        0.519751  , 0.42201325, 0.38059542, 0.37285957, 0.32653496,\n",
       "        0.30511534, 0.2819396 , 0.2640403 ],\n",
       "       [0.40687394, 0.4517181 , 0.46080402, 0.47131905, 0.5698497 ,\n",
       "        0.50295407, 0.5253894 , 0.50560814, 0.4699233 , 0.37764275,\n",
       "        0.36035958, 0.29946125, 0.27014366],\n",
       "       [0.14007822, 0.14085938, 0.14973143, 0.18111576, 0.25965208,\n",
       "        0.24899228, 0.4365054 , 0.6065113 , 0.6787067 , 0.63694745,\n",
       "        0.5165333 , 0.39985502, 0.39015126],\n",
       "       [0.14010046, 0.13927104, 0.13897397, 0.15446918, 0.15410195,\n",
       "        0.14981739, 0.19202287, 0.23417355, 0.2971693 , 0.346509  ,\n",
       "        0.528799  , 0.52610254, 0.5939619 ],\n",
       "       [0.14187877, 0.14360635, 0.14096434, 0.13628697, 0.13595201,\n",
       "        0.1405368 , 0.14285128, 0.13464577, 0.15676934, 0.18507642,\n",
       "        0.27454564, 0.34227458, 0.41060266],\n",
       "       [0.1407005 , 0.13986911, 0.13823213, 0.13777767, 0.13830334,\n",
       "        0.13923562, 0.13838194, 0.13557185, 0.13885342, 0.14848207,\n",
       "        0.1445844 , 0.19573158, 0.20536526],\n",
       "       [0.15173802, 0.15540245, 0.16035737, 0.15956165, 0.15174502,\n",
       "        0.15007919, 0.14768706, 0.13826434, 0.14019196, 0.14049688,\n",
       "        0.13723941, 0.14125426, 0.13700743],\n",
       "       [0.16831727, 0.16458112, 0.17045295, 0.17777388, 0.16994137,\n",
       "        0.1693746 , 0.16591705, 0.15561174, 0.15334482, 0.15364964,\n",
       "        0.14121194, 0.14208655, 0.14455158]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sd</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.02584 0.04403 ... 7.575e-07</div><input id='attrs-1ac19bc3-f7dc-499d-b96a-305ab62fbbd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ac19bc3-f7dc-499d-b96a-305ab62fbbd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7b08828-f021-43f6-a003-6b1c4b3018eb' class='xr-var-data-in' type='checkbox'><label for='data-e7b08828-f021-43f6-a003-6b1c4b3018eb' title='Show/Hide data repr'><svg 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>m of water equivalent</dd><dt><span>long_name :</span></dt><dd>Snow depth</dd><dt><span>standard_name :</span></dt><dd>lwe_thickness_of_surface_snow_amount</dd></dl></div><div class='xr-var-data'><pre>array([[2.58381050e-02, 4.40342687e-02, 4.45874631e-02, 2.73605790e-02,\n",
       "        2.87198406e-02, 3.95346917e-02, 2.02700552e-02, 1.10747851e-02,\n",
       "        5.75961685e-03, 5.10275038e-03, 3.59394657e-03, 2.37074122e-03,\n",
       "        1.69621652e-03],\n",
       "       [4.70276587e-02, 8.83967653e-02, 9.21914876e-02, 5.54073155e-02,\n",
       "        9.94359255e-02, 7.45248273e-02, 4.64647599e-02, 1.92543846e-02,\n",
       "        1.32579384e-02, 7.73420045e-03, 4.39949892e-03, 3.16279824e-03,\n",
       "        2.69441865e-03],\n",
       "       [4.88803498e-02, 1.01333946e-01, 1.03393264e-01, 8.11599568e-02,\n",
       "        2.18430415e-01, 1.23367153e-01, 7.60850161e-02, 4.36827354e-02,\n",
       "        3.76755558e-02, 1.94397513e-02, 1.31855821e-02, 3.47556290e-03,\n",
       "        3.00008175e-03],\n",
       "       [1.33067870e-03, 1.32427365e-03, 1.73155090e-03, 1.13076093e-02,\n",
       "        5.06525971e-02, 3.31103653e-02, 5.36439419e-02, 1.08815737e-01,\n",
       "        1.57960564e-01, 9.08898935e-02, 3.66598740e-02, 1.27627375e-02,\n",
       "        1.70329753e-02],\n",
       "       [3.87119735e-06, 3.17953527e-06, 3.87181854e-06, 6.17421465e-03,\n",
       "        6.18061563e-03, 6.17161812e-03, 9.25494451e-03, 1.75691936e-02,\n",
       "        3.03454846e-02, 2.99819764e-02, 3.95114832e-02, 4.40253168e-01,\n",
       "        5.88984907e-01],\n",
       "       [4.73856926e-06, 2.31464696e-06, 1.96819497e-06, 3.18015623e-06,\n",
       "        1.96819497e-06, 9.29459929e-07, 7.10052773e-05, 1.15662195e-04,\n",
       "        5.06922789e-03, 5.66531578e-03, 1.03609720e-02, 2.28204489e-01,\n",
       "        1.85146868e-01],\n",
       "       [2.66047823e-06, 2.31402623e-06, 2.14142096e-06, 1.79496908e-06,\n",
       "        1.27653277e-06, 1.27591193e-06, 7.56854831e-07, 7.56854831e-07,\n",
       "        5.83628832e-07, 6.69349625e-04, 6.78178563e-04, 4.06650594e-03,\n",
       "        5.90833416e-03],\n",
       "       [9.30701674e-07, 1.27653277e-06, 1.27653277e-06, 1.10330677e-06,\n",
       "        1.10330677e-06, 7.56854831e-07, 7.56854831e-07, 7.56854831e-07,\n",
       "        5.83628832e-07, 5.83628832e-07, 8.88854265e-06, 1.09660132e-05,\n",
       "        1.33675829e-04],\n",
       "       [5.84249676e-07, 7.57475675e-07, 7.57475675e-07, 5.84249676e-07,\n",
       "        7.56854831e-07, 5.83628832e-07, 5.83628832e-07, 5.83628832e-07,\n",
       "        4.11023706e-07, 5.83628832e-07, 4.11023706e-07, 5.84249676e-07,\n",
       "        7.57475675e-07]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slhf</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-2.394e+06 ... -6.342e+06</div><input id='attrs-746cdc02-f67e-43fc-b4b3-d06b12cea4a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-746cdc02-f67e-43fc-b4b3-d06b12cea4a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b79c3f63-b80e-4245-b6e5-251c218a11df' class='xr-var-data-in' type='checkbox'><label for='data-b79c3f63-b80e-4245-b6e5-251c218a11df' title='Show/Hide data repr'><svg 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>J m**-2</dd><dt><span>long_name :</span></dt><dd>Surface latent heat flux</dd><dt><span>standard_name :</span></dt><dd>surface_upward_latent_heat_flux</dd></dl></div><div class='xr-var-data'><pre>array([[-2393778.5, -2113208. , -2515683. , -2962652.2, -2926997.8,\n",
       "        -2745850.2, -3012790. , -2898728. , -2679005.2, -3011506.2,\n",
       "        -3050964. , -3150911.8, -3165622.8],\n",
       "       [-2727818.2, -1846933.9, -1753553.9, -2455025.8, -2136877. ,\n",
       "        -2353735.2, -2847947.2, -2991840. , -2717395.2, -2781641.5,\n",
       "        -2771754.2, -2910558. , -3016748.2],\n",
       "       [-3159499.8, -2767136.2, -2652452.2, -2473968.2, -1708944. ,\n",
       "        -2103937.2, -2093707.1, -2259423.8, -2309670.8, -2618572.2,\n",
       "        -2269155. , -2354948.2, -2507040.2],\n",
       "       [-6301518. , -5895540.5, -5303751.5, -4798823. , -4464417. ,\n",
       "        -4377374.5, -2927206.8, -1681897.4, -1185222.8, -1477669.9,\n",
       "        -2154249. , -2065002.9, -2336073.5],\n",
       "       [-6261261.5, -5899965.5, -5743060.5, -5686281.5, -5619334. ,\n",
       "        -5468113. , -5107693. , -4776059. , -4271534.5, -3629818. ,\n",
       "        -2163728. , -1892401.4, -1350456.1],\n",
       "       [-6979720. , -6764170.5, -6326926. , -6334928. , -6268906. ,\n",
       "        -6091340.5, -6194022.5, -5630658.5, -5064265.5, -4898600.5,\n",
       "        -4303478.5, -3337380.2, -2810692.8],\n",
       "       [-6545270. , -6071943.5, -5779013.5, -6193566.5, -6271825.5,\n",
       "        -6423862. , -6478403.5, -6284686.5, -5489574. , -5461662.5,\n",
       "        -5833289.5, -5426504. , -5201358.5],\n",
       "       [-6732218. , -6345738.5, -6241005.5, -6620374.5, -6303321.5,\n",
       "        -6225385.5, -6237174.5, -6355618. , -5765798. , -6159081.5,\n",
       "        -6555073.5, -6311555.5, -6389518. ],\n",
       "       [-6852338.5, -6894408.5, -6806233.5, -6847585.5, -6529838.5,\n",
       "        -6309279.5, -6238524. , -6143079.5, -5833156.5, -6227282.5,\n",
       "        -6231215.5, -5847710.5, -6342039.5]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.001671 0.001676 ... 0.007178</div><input id='attrs-67b39b68-d99f-4c36-9c66-3cf798fe6cb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67b39b68-d99f-4c36-9c66-3cf798fe6cb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce1838cc-7deb-497d-b650-ed490cefbcb7' class='xr-var-data-in' type='checkbox'><label for='data-ce1838cc-7deb-497d-b650-ed490cefbcb7' title='Show/Hide data repr'><svg 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>m</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd></dl></div><div class='xr-var-data'><pre>array([[0.00167074, 0.00167586, 0.0019004 , 0.00176064, 0.00172053,\n",
       "        0.00172485, 0.00129706, 0.00116026, 0.00136158, 0.0016442 ,\n",
       "        0.00178896, 0.00190827, 0.00201904],\n",
       "       [0.00310761, 0.00322931, 0.00290776, 0.00241429, 0.00277882,\n",
       "        0.00209841, 0.00161375, 0.00119415, 0.00144712, 0.00143539,\n",
       "        0.00145989, 0.00158967, 0.00174772],\n",
       "       [0.00616907, 0.00802575, 0.00747883, 0.00526238, 0.0066099 ,\n",
       "        0.00420331, 0.00276212, 0.00206119, 0.00163784, 0.00144285,\n",
       "        0.00139039, 0.00134078, 0.00141249],\n",
       "       [0.01356958, 0.01368054, 0.01089659, 0.00830085, 0.00961687,\n",
       "        0.00717992, 0.00540845, 0.00448278, 0.00394101, 0.00278893,\n",
       "        0.00193786, 0.0012892 , 0.00138884],\n",
       "       [0.00625344, 0.0062567 , 0.00684684, 0.0076508 , 0.00677814,\n",
       "        0.00811851, 0.00796054, 0.00832597, 0.00788783, 0.00526172,\n",
       "        0.00318435, 0.00231946, 0.00304072],\n",
       "       [0.00772755, 0.00706993, 0.00670928, 0.00793458, 0.00791163,\n",
       "        0.00786684, 0.00725683, 0.00729855, 0.00883463, 0.00815426,\n",
       "        0.00638462, 0.00423203, 0.00509546],\n",
       "       [0.0051218 , 0.00501816, 0.00481939, 0.00545096, 0.00586418,\n",
       "        0.00710843, 0.00721631, 0.00647188, 0.00621707, 0.00703525,\n",
       "        0.00953236, 0.00978909, 0.01031536],\n",
       "       [0.00408274, 0.00411246, 0.00395182, 0.0045112 , 0.00396307,\n",
       "        0.00479351, 0.00572053, 0.00534707, 0.00538156, 0.0062744 ,\n",
       "        0.00872632, 0.00968437, 0.01066702],\n",
       "       [0.0042163 , 0.00433846, 0.00419966, 0.00465869, 0.00410923,\n",
       "        0.0037335 , 0.00418702, 0.00406463, 0.00428582, 0.00518069,\n",
       "        0.00550851, 0.00593035, 0.0071781 ]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e2117261-71c1-49eb-b00f-58951998b1c2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e2117261-71c1-49eb-b00f-58951998b1c2' class='xr-section-summary' >Attributes: <span>(2)</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-1.6</dd><dt><span>history :</span></dt><dd>2022-02-28 15:24:18 GMT by grib_to_netcdf-2.24.2: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data3/adaptor.mars.internal-1646061852.1854177-30809-7-ee9e709c-5235-49e2-81a1-8416b62d741d.nc /cache/tmp/ee9e709c-5235-49e2-81a1-8416b62d741d-adaptor.mars.internal-1646061530.8465672-30809-1-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (longitude: 13, latitude: 9)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 84.0 84.25 84.5 84.75 ... 86.5 86.75 87.0\n",
       "  * latitude   (latitude) float32 29.0 28.75 28.5 28.25 ... 27.5 27.25 27.0\n",
       "Data variables:\n",
       "    t2m        (latitude, longitude) float32 271.2 268.7 267.5 ... 293.6 292.4\n",
       "    fal        (latitude, longitude) float32 0.3633 0.4273 ... 0.1421 0.1446\n",
       "    sd         (latitude, longitude) float32 0.02584 0.04403 ... 7.575e-07\n",
       "    slhf       (latitude, longitude) float32 -2.394e+06 ... -6.342e+06\n",
       "    tp         (latitude, longitude) float32 0.001671 0.001676 ... 0.007178\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-28 15:24:18 GMT by grib_to_netcdf-2.24.2: /opt/ecmw..."
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# catchments.x_wgs\n",
    "fmeans"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e6ac9fb-4f5b-4951-8060-bbdd2c5b43bb",
   "metadata": {},
   "source": [
    "### append means to the \"cathments\" table "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "dff03f17-310f-4f62-99bb-7d5e400243df",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. get coordinates:\n",
    "'''(NB: be carefil with x and y) \n",
    "x - 85, y - 28\n",
    "longitude - 85, latitude - 28 ''' \n",
    "\n",
    "catchments = catchments.sort_values(by=['x_wgs', 'y_wgs'])\n",
    "\n",
    "lats = catchments.y_wgs\n",
    "lons = catchments.x_wgs\n",
    "\n",
    "mean_points = fmeans.sel(longitude=lons, latitude=lats, method='nearest')\n",
    "\n",
    "# 1.1. add old coordinates - ovewrite dimentions \n",
    "mean_points['longitude'] = lons.values\n",
    "mean_points['latitude']= lats.values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "dfe29dff-bf35-482d-b32e-7c6c9de366e0",
   "metadata": {},
   "outputs": [
    {
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       "  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-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",
       "  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",
       "  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-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-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",
       "  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;\n",
       "Dimensions:    (longitude: 297, latitude: 297)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float64 85.23 85.24 85.24 85.25 ... 85.88 85.88 85.88\n",
       "  * latitude   (latitude) float64 28.09 28.12 28.26 28.09 ... 28.16 28.28 28.23\n",
       "Data variables:\n",
       "    t2m        (latitude, longitude) float32 288.2 288.2 288.2 ... 266.8 266.8\n",
       "    fal        (latitude, longitude) float32 0.1498 0.1498 ... 0.6787 0.6787\n",
       "    sd         (latitude, longitude) float32 0.006172 0.006172 ... 0.158 0.158\n",
       "    slhf       (latitude, longitude) float32 -5.468e+06 ... -1.185e+06\n",
       "    tp         (latitude, longitude) float32 0.008119 0.008119 ... 0.003941\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-28 15:24:18 GMT by grib_to_netcdf-2.24.2: /opt/ecmw...</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-a6cd0da2-b2c4-4d5c-8ae3-ea6b4770c95d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a6cd0da2-b2c4-4d5c-8ae3-ea6b4770c95d' 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'>longitude</span>: 297</li><li><span class='xr-has-index'>latitude</span>: 297</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2537daa7-5165-4df5-8728-6ebd17a84b84' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2537daa7-5165-4df5-8728-6ebd17a84b84' 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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>85.23 85.24 85.24 ... 85.88 85.88</div><input id='attrs-27b817ef-f5a6-41dd-a3d8-b41ccda49cb1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-27b817ef-f5a6-41dd-a3d8-b41ccda49cb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b85f19b6-82fd-4572-a24e-add93ec05638' class='xr-var-data-in' type='checkbox'><label for='data-b85f19b6-82fd-4572-a24e-add93ec05638' title='Show/Hide data 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([85.235, 85.238, 85.242, ..., 85.876, 85.877, 85.878])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>28.09 28.12 28.26 ... 28.28 28.23</div><input id='attrs-2cafc881-9310-4243-ab3e-991bfc46ec7d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2cafc881-9310-4243-ab3e-991bfc46ec7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5120683c-54f3-43d1-b9fd-823e92634e49' class='xr-var-data-in' type='checkbox'><label for='data-5120683c-54f3-43d1-b9fd-823e92634e49' title='Show/Hide data 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([28.093, 28.116, 28.259, ..., 28.157, 28.28 , 28.225])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8bfc7042-3ea9-48f3-b673-efcbd8c3a764' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8bfc7042-3ea9-48f3-b673-efcbd8c3a764' 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>t2m</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>288.2 288.2 288.2 ... 266.8 266.8</div><input id='attrs-598c2071-d6f3-4577-80f7-588d8209b164' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-598c2071-d6f3-4577-80f7-588d8209b164' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-208d63cf-9f0c-4b4d-b0e8-f1b539b0b5e9' class='xr-var-data-in' type='checkbox'><label for='data-208d63cf-9f0c-4b4d-b0e8-f1b539b0b5e9' title='Show/Hide data repr'><svg 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>long_name :</span></dt><dd>2 metre temperature</dd></dl></div><div class='xr-var-data'><pre>array([[288.2423 , 288.2423 , 288.2423 , ..., 278.5179 , 278.5179 ,\n",
       "        278.5179 ],\n",
       "       [288.2423 , 288.2423 , 288.2423 , ..., 278.5179 , 278.5179 ,\n",
       "        278.5179 ],\n",
       "       [278.42856, 278.42856, 278.42856, ..., 266.77145, 266.77145,\n",
       "        266.77145],\n",
       "       ...,\n",
       "       [278.42856, 278.42856, 278.42856, ..., 266.77145, 266.77145,\n",
       "        266.77145],\n",
       "       [278.42856, 278.42856, 278.42856, ..., 266.77145, 266.77145,\n",
       "        266.77145],\n",
       "       [278.42856, 278.42856, 278.42856, ..., 266.77145, 266.77145,\n",
       "        266.77145]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fal</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1498 0.1498 ... 0.6787 0.6787</div><input id='attrs-1cb1bae1-f5be-4cd5-84b3-b1fd7a6f437f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cb1bae1-f5be-4cd5-84b3-b1fd7a6f437f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81562af8-149a-47db-9c08-363ae6aacbc8' class='xr-var-data-in' type='checkbox'><label for='data-81562af8-149a-47db-9c08-363ae6aacbc8' title='Show/Hide data repr'><svg 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>(0 - 1)</dd><dt><span>long_name :</span></dt><dd>Forecast albedo</dd></dl></div><div class='xr-var-data'><pre>array([[0.14981739, 0.14981739, 0.14981739, ..., 0.2971693 , 0.2971693 ,\n",
       "        0.2971693 ],\n",
       "       [0.14981739, 0.14981739, 0.14981739, ..., 0.2971693 , 0.2971693 ,\n",
       "        0.2971693 ],\n",
       "       [0.24899228, 0.24899228, 0.24899228, ..., 0.6787067 , 0.6787067 ,\n",
       "        0.6787067 ],\n",
       "       ...,\n",
       "       [0.24899228, 0.24899228, 0.24899228, ..., 0.6787067 , 0.6787067 ,\n",
       "        0.6787067 ],\n",
       "       [0.24899228, 0.24899228, 0.24899228, ..., 0.6787067 , 0.6787067 ,\n",
       "        0.6787067 ],\n",
       "       [0.24899228, 0.24899228, 0.24899228, ..., 0.6787067 , 0.6787067 ,\n",
       "        0.6787067 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sd</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.006172 0.006172 ... 0.158 0.158</div><input id='attrs-1199e8b2-86cf-4c3d-88be-7e3e6c8b06ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1199e8b2-86cf-4c3d-88be-7e3e6c8b06ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f126231-b5d5-4894-9a8e-a35f8fbd98b4' class='xr-var-data-in' type='checkbox'><label for='data-1f126231-b5d5-4894-9a8e-a35f8fbd98b4' title='Show/Hide data repr'><svg 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>m of water equivalent</dd><dt><span>long_name :</span></dt><dd>Snow depth</dd><dt><span>standard_name :</span></dt><dd>lwe_thickness_of_surface_snow_amount</dd></dl></div><div class='xr-var-data'><pre>array([[0.00617162, 0.00617162, 0.00617162, ..., 0.03034548, 0.03034548,\n",
       "        0.03034548],\n",
       "       [0.00617162, 0.00617162, 0.00617162, ..., 0.03034548, 0.03034548,\n",
       "        0.03034548],\n",
       "       [0.03311037, 0.03311037, 0.03311037, ..., 0.15796056, 0.15796056,\n",
       "        0.15796056],\n",
       "       ...,\n",
       "       [0.03311037, 0.03311037, 0.03311037, ..., 0.15796056, 0.15796056,\n",
       "        0.15796056],\n",
       "       [0.03311037, 0.03311037, 0.03311037, ..., 0.15796056, 0.15796056,\n",
       "        0.15796056],\n",
       "       [0.03311037, 0.03311037, 0.03311037, ..., 0.15796056, 0.15796056,\n",
       "        0.15796056]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slhf</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-5.468e+06 ... -1.185e+06</div><input id='attrs-d8b51d64-25e1-47f5-81ac-3a0a3cc10524' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8b51d64-25e1-47f5-81ac-3a0a3cc10524' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-344a663d-9973-4a45-a4a9-fe99cb3ad036' class='xr-var-data-in' type='checkbox'><label for='data-344a663d-9973-4a45-a4a9-fe99cb3ad036' title='Show/Hide data repr'><svg 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>J m**-2</dd><dt><span>long_name :</span></dt><dd>Surface latent heat flux</dd><dt><span>standard_name :</span></dt><dd>surface_upward_latent_heat_flux</dd></dl></div><div class='xr-var-data'><pre>array([[-5468113. , -5468113. , -5468113. , ..., -4271534.5, -4271534.5,\n",
       "        -4271534.5],\n",
       "       [-5468113. , -5468113. , -5468113. , ..., -4271534.5, -4271534.5,\n",
       "        -4271534.5],\n",
       "       [-4377374.5, -4377374.5, -4377374.5, ..., -1185222.8, -1185222.8,\n",
       "        -1185222.8],\n",
       "       ...,\n",
       "       [-4377374.5, -4377374.5, -4377374.5, ..., -1185222.8, -1185222.8,\n",
       "        -1185222.8],\n",
       "       [-4377374.5, -4377374.5, -4377374.5, ..., -1185222.8, -1185222.8,\n",
       "        -1185222.8],\n",
       "       [-4377374.5, -4377374.5, -4377374.5, ..., -1185222.8, -1185222.8,\n",
       "        -1185222.8]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.008119 0.008119 ... 0.003941</div><input id='attrs-edf7b456-d33d-44a7-8a8d-9ca606c07911' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edf7b456-d33d-44a7-8a8d-9ca606c07911' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c327c2e9-f66a-4664-9eb9-7133fbbf8f2d' class='xr-var-data-in' type='checkbox'><label for='data-c327c2e9-f66a-4664-9eb9-7133fbbf8f2d' title='Show/Hide data repr'><svg 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>m</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd></dl></div><div class='xr-var-data'><pre>array([[0.00811851, 0.00811851, 0.00811851, ..., 0.00788783, 0.00788783,\n",
       "        0.00788783],\n",
       "       [0.00811851, 0.00811851, 0.00811851, ..., 0.00788783, 0.00788783,\n",
       "        0.00788783],\n",
       "       [0.00717992, 0.00717992, 0.00717992, ..., 0.00394101, 0.00394101,\n",
       "        0.00394101],\n",
       "       ...,\n",
       "       [0.00717992, 0.00717992, 0.00717992, ..., 0.00394101, 0.00394101,\n",
       "        0.00394101],\n",
       "       [0.00717992, 0.00717992, 0.00717992, ..., 0.00394101, 0.00394101,\n",
       "        0.00394101],\n",
       "       [0.00717992, 0.00717992, 0.00717992, ..., 0.00394101, 0.00394101,\n",
       "        0.00394101]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2a05e642-27fa-4084-aca5-4f3b421db205' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2a05e642-27fa-4084-aca5-4f3b421db205' class='xr-section-summary' >Attributes: <span>(2)</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-1.6</dd><dt><span>history :</span></dt><dd>2022-02-28 15:24:18 GMT by grib_to_netcdf-2.24.2: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data3/adaptor.mars.internal-1646061852.1854177-30809-7-ee9e709c-5235-49e2-81a1-8416b62d741d.nc /cache/tmp/ee9e709c-5235-49e2-81a1-8416b62d741d-adaptor.mars.internal-1646061530.8465672-30809-1-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (longitude: 297, latitude: 297)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float64 85.23 85.24 85.24 85.25 ... 85.88 85.88 85.88\n",
       "  * latitude   (latitude) float64 28.09 28.12 28.26 28.09 ... 28.16 28.28 28.23\n",
       "Data variables:\n",
       "    t2m        (latitude, longitude) float32 288.2 288.2 288.2 ... 266.8 266.8\n",
       "    fal        (latitude, longitude) float32 0.1498 0.1498 ... 0.6787 0.6787\n",
       "    sd         (latitude, longitude) float32 0.006172 0.006172 ... 0.158 0.158\n",
       "    slhf       (latitude, longitude) float32 -5.468e+06 ... -1.185e+06\n",
       "    tp         (latitude, longitude) float32 0.008119 0.008119 ... 0.003941\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-28 15:24:18 GMT by grib_to_netcdf-2.24.2: /opt/ecmw..."
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b48e5884-f4ff-4eda-9065-2a423dcf0a55",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "a0ae7e89-63ff-4460-9f90-ffb33e49ad77",
   "metadata": {},
   "outputs": [],
   "source": [
    "# mean_points plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c2587693-3507-4242-b89d-2502d6d8e109",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2. convert to data frame \n",
    "# mean_points_df = mean_points.reset_coords(drop=True).to_dataframe()\n",
    "mean_points_df = mean_points.to_dataframe() # dimentions: number of catchments squared\n",
    "\n",
    "# check: coordinates should be: (lon: 85,25 - 86, lat: 28.0 - 28.5) \n",
    "#        old coordinates should be there! \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "a7b36475-3327-4c0b-a6ba-49936d0c70e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "88209"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# new table looks like this \n",
    "# mean_points_df.head()\n",
    "len(mean_points_df) # should = 297*297\n",
    "\n",
    "# 297*297"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b62017d2-db14-4cf3-a72d-97fac4a4c8c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# reset index - make\n",
    "# latitude and longitude new columns \n",
    "mean_points_df = mean_points_df.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "28d7a457-78a8-4216-87ac-9bc9d5c9a2f1",
   "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>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>t2m</th>\n",
       "      <th>fal</th>\n",
       "      <th>sd</th>\n",
       "      <th>slhf</th>\n",
       "      <th>tp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.093</td>\n",
       "      <td>288.242310</td>\n",
       "      <td>0.149817</td>\n",
       "      <td>0.006172</td>\n",
       "      <td>-5468113.0</td>\n",
       "      <td>0.008119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.116</td>\n",
       "      <td>288.242310</td>\n",
       "      <td>0.149817</td>\n",
       "      <td>0.006172</td>\n",
       "      <td>-5468113.0</td>\n",
       "      <td>0.008119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.259</td>\n",
       "      <td>278.428558</td>\n",
       "      <td>0.248992</td>\n",
       "      <td>0.033110</td>\n",
       "      <td>-4377374.5</td>\n",
       "      <td>0.007180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.089</td>\n",
       "      <td>288.242310</td>\n",
       "      <td>0.149817</td>\n",
       "      <td>0.006172</td>\n",
       "      <td>-5468113.0</td>\n",
       "      <td>0.008119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.298</td>\n",
       "      <td>278.428558</td>\n",
       "      <td>0.248992</td>\n",
       "      <td>0.033110</td>\n",
       "      <td>-4377374.5</td>\n",
       "      <td>0.007180</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude         t2m       fal        sd       slhf        tp\n",
       "0     85.235    28.093  288.242310  0.149817  0.006172 -5468113.0  0.008119\n",
       "1     85.235    28.116  288.242310  0.149817  0.006172 -5468113.0  0.008119\n",
       "2     85.235    28.259  278.428558  0.248992  0.033110 -4377374.5  0.007180\n",
       "3     85.235    28.089  288.242310  0.149817  0.006172 -5468113.0  0.008119\n",
       "4     85.235    28.298  278.428558  0.248992  0.033110 -4377374.5  0.007180"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_points_df.head()\n",
    "# catchments.x_wgs # = longitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "1cabb4ee-725b-45a3-b7c7-1abf39d4edc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make new dataframe more appealing (!!! be carefull with x and y !!!) \n",
    "\n",
    "# reset index - make latitude and longitude new columns \n",
    "# mean_points_df= mean_points_df.reset_index()\n",
    "mean_points_df_renamed = mean_points_df.rename(columns = {'longitude': 'x_wgs', 'latitude': 'y_wgs'}) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "8c8c0167-ee25-434f-97a5-829b8e160ac4",
   "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>x_wgs</th>\n",
       "      <th>y_wgs</th>\n",
       "      <th>t2m</th>\n",
       "      <th>fal</th>\n",
       "      <th>sd</th>\n",
       "      <th>slhf</th>\n",
       "      <th>tp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.093</td>\n",
       "      <td>288.242310</td>\n",
       "      <td>0.149817</td>\n",
       "      <td>0.006172</td>\n",
       "      <td>-5468113.0</td>\n",
       "      <td>0.008119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.116</td>\n",
       "      <td>288.242310</td>\n",
       "      <td>0.149817</td>\n",
       "      <td>0.006172</td>\n",
       "      <td>-5468113.0</td>\n",
       "      <td>0.008119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.259</td>\n",
       "      <td>278.428558</td>\n",
       "      <td>0.248992</td>\n",
       "      <td>0.033110</td>\n",
       "      <td>-4377374.5</td>\n",
       "      <td>0.007180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.089</td>\n",
       "      <td>288.242310</td>\n",
       "      <td>0.149817</td>\n",
       "      <td>0.006172</td>\n",
       "      <td>-5468113.0</td>\n",
       "      <td>0.008119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>85.235</td>\n",
       "      <td>28.298</td>\n",
       "      <td>278.428558</td>\n",
       "      <td>0.248992</td>\n",
       "      <td>0.033110</td>\n",
       "      <td>-4377374.5</td>\n",
       "      <td>0.007180</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    x_wgs   y_wgs         t2m       fal        sd       slhf        tp\n",
       "0  85.235  28.093  288.242310  0.149817  0.006172 -5468113.0  0.008119\n",
       "1  85.235  28.116  288.242310  0.149817  0.006172 -5468113.0  0.008119\n",
       "2  85.235  28.259  278.428558  0.248992  0.033110 -4377374.5  0.007180\n",
       "3  85.235  28.089  288.242310  0.149817  0.006172 -5468113.0  0.008119\n",
       "4  85.235  28.298  278.428558  0.248992  0.033110 -4377374.5  0.007180"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# catchments.x_wgs\n",
    "mean_points_df_renamed.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "96711baf-95e9-4be5-a93c-f56411af7217",
   "metadata": {},
   "outputs": [],
   "source": [
    "# new table looks like this\n",
    "# catchments\n",
    "# catchments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "1b8f0b45-0611-4012-9447-a00f5aebdd4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#  merge tables: take 'smaller' table and add the 'bigger' table to it \n",
    "# (otherwise there will be a lot of nan vallues, .dropna - if there are any)\n",
    "\n",
    "catchments_climate = catchments.merge(mean_points_df_renamed, on=['x_wgs', 'y_wgs'], how='left').drop_duplicates()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "1198be66-8f6f-41b1-9aaf-6655f24bcada",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "297"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(catchments_climate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d75064b7-491d-4c88-be77-25404ff0cf3e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2839183c-f7f5-488d-b0de-51516b3ed581",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ba2600b0-0e73-4570-a9de-838aaa5941cb",
   "metadata": {},
   "source": [
    "### plot correlations with climatic variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "04902f04-1f83-4a5a-9aa4-b510b5038920",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PolygonId', 'catchment_area_m2', 'x_utm', 'y_utm', 'mean_elevation',\n",
       "       'median_elevation', 'std_elevation', 'min_elevation', 'max_elevation',\n",
       "       'range_elevation', 'variance_elevation', 'stream_order',\n",
       "       'stream_length', 'stream_drop', 'stream_slope', 'variance_slope',\n",
       "       'mean_slope', 'median_slope', 'std_slope', 'min_elevation', 'max_slope',\n",
       "       'range_slope', 'x_wgs', 'y_wgs', 'StraightL', 'area_glacier_m2',\n",
       "       'glacier_percent', 't2m', 'fal', 'sd', 'slhf', 'tp'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "catchments_climate.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "c187f2ae-d3e6-49e1-a87e-87ad5fdfd3a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. correlations:\n",
    "catchments_climate_corr = catchments_climate.corr()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "ba4e38cb-1063-4731-951d-b678d04da0c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# catchments and streams \n",
    "\n",
    "plt.figure(figsize=(10, 10))\n",
    "\n",
    "# mask for the upper triangle\n",
    "mask = np.triu(np.ones_like(catchments_climate_corr, dtype=bool))\n",
    "# color palette\n",
    "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
    "# heatmap \n",
    "sns.heatmap(catchments_climate_corr, cmap=cmap, mask = mask)\n",
    "plt.title('catcmhent, streams, glaciers and climate', fontsize = 15)\n",
    "plt.tight_layout()\n",
    "\n",
    "# plt.savefig('catch_climate_corr.png', dpi = 300, bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "8024b44c-87ae-4c9d-a135-5ff61225647c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['PolygonId', 'catchment_area_m2', 'x_utm', 'y_utm', 'mean_elevation',\n",
       "       'median_elevation', 'std_elevation', 'min_elevation', 'max_elevation',\n",
       "       'range_elevation', 'variance_elevation', 'stream_order',\n",
       "       'stream_length', 'stream_drop', 'stream_slope', 'variance_slope',\n",
       "       'mean_slope', 'median_slope', 'std_slope', 'min_elevation', 'max_slope',\n",
       "       'range_slope', 'x_wgs', 'y_wgs', 'StraightL', 'area_glacier_m2',\n",
       "       'glacier_percent', 't2m', 'fal', 'sd', 'slhf', 'tp'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "catchments_climate.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "4811ece6-18d9-4757-9760-edf9a8152304",
   "metadata": {},
   "outputs": [],
   "source": [
    "### take only interesting parameters: \n",
    "\n",
    "params = catchments_climate[[#'PolygonId',\n",
    "                             # 'mean_elevation', \n",
    "                            'range_elevation', \n",
    "                             'stream_length', \n",
    "                             'glacier_percent', \n",
    "                             'catchment_area_m2', \n",
    "                              'tp', 't2m'\n",
    "]]\n",
    "\n",
    "# params.glacier_percent"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1eb78ca1-c992-4f50-ab60-9d2bd19c253a",
   "metadata": {},
   "source": [
    "### make multiple scatter plots "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "ae80950c-8e11-4bab-8715-8283cb89a0dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7fde90a56190>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 42 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.PairGrid(params)\n",
    "\n",
    "g.map_diag(sns.histplot)\n",
    "g.map_offdiag(sns.scatterplot)\n",
    "\n",
    "# plt.savefig('params_scatter.png', dpi = 300, bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cc0b998b-8a61-46f7-8321-445b4195f1eb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f77a27a1-08b6-45d3-a6db-6a74ef470a39",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83e7c811-df15-4895-83aa-5ad07935cfa7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "11f15801-4c70-46a2-b14e-be13347143de",
   "metadata": {},
   "source": [
    "## Means by month"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52332edb-28e5-4c0a-8171-4d0821b0db7c",
   "metadata": {},
   "source": [
    "### 1. means by month (monthly means over time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "db1dc2b5-b070-40a4-8835-7eb76f4e3b8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# f - original era5 dataset\n",
    "\n",
    "fmonth = f.groupby('time.month').mean(dim = 'time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "0b86acfa-790a-4717-ac04-d709286e63f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/varyabazilova/opt/anaconda3/envs/project1/lib/python3.7/site-packages/xarray/plot/plot.py:1409: UserWarning: No contour levels were found within the data range.\n",
      "  primitive = ax.contour(x, y, z, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<xarray.plot.facetgrid.FacetGrid at 0x7fdea18f2150>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 936x648 with 13 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# tutorial: https://xarray-contrib.github.io/xarray-tutorial/scipy-tutorial/04_plotting_and_visualization.html\n",
    "\n",
    "fig = fmonth.tp.plot.pcolormesh(\n",
    "    # \"longitude\",\n",
    "    # \"latitude\",\n",
    "    col=\"month\",\n",
    "    col_wrap=4,\n",
    "    robust=True,\n",
    "    cbar_kwargs={\"label\": \"total precipitation\"})\n",
    "\n",
    "plt.suptitle('mean total precipitation', fontsize=16, y=1.02)\n",
    "\n",
    "\n",
    "\n",
    "''' add lines if you want to: '''\n",
    "\n",
    "# Use this to plot contours on each panel\n",
    "# Note that this plotting call uses the original DataArray gradients\n",
    "fig.map_dataarray(\n",
    "    xr.plot.contour, x=\"longitude\", y=\"latitude\", colors=\"k\", levels=10, add_colorbar=False)\n",
    "\n",
    "# Add a point (or anything else!)\n",
    "# fg.map(lambda: plt.plot(250, 40, markersize=20, marker=\".\", color=\"w\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6592e452-bfdd-4e82-bcb2-bf847ecfb073",
   "metadata": {},
   "source": [
    "### get coordinates for monthly mean vallues "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "67b1b2b8-10f8-4455-b1f8-af0d8fc5d232",
   "metadata": {},
   "outputs": [],
   "source": [
    "# select points for each parameter: \n",
    "\n",
    "# 1. get coordinates:\n",
    "'''(NB: be carefil with x and y)''' \n",
    "\n",
    "catchments = catchments.sort_values(by=['x_wgs', 'y_wgs'])\n",
    "\n",
    "lats = catchments.y_wgs\n",
    "lons = catchments.x_wgs\n",
    "\n",
    "mean_points_monthly = fmonth.sel(longitude=lons, latitude=lats, method='nearest')\n",
    "\n",
    "# 1.1. add old coordinates - ovewrite dimentions \n",
    "mean_points_monthly['longitude'] = lons.values\n",
    "mean_points_monthly['latitude']= lats.values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "415e524b-f80e-4da2-bdd5-69ba273f6707",
   "metadata": {},
   "outputs": [
    {
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       "  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-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",
       "  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",
       "  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-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-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",
       "  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;\n",
       "Dimensions:    (longitude: 297, latitude: 297, month: 12)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float64 85.23 85.24 85.24 85.25 ... 85.88 85.88 85.88\n",
       "  * latitude   (latitude) float64 28.09 28.12 28.26 28.09 ... 28.16 28.28 28.23\n",
       "  * month      (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    t2m        (month, latitude, longitude) float32 280.6 280.6 ... 260.0 260.0\n",
       "    fal        (month, latitude, longitude) float32 0.1625 0.1625 ... 0.7449\n",
       "    sd         (month, latitude, longitude) float32 0.01093 0.01093 ... 0.08625\n",
       "    slhf       (month, latitude, longitude) float32 -3.059e+06 ... -1.935e+05\n",
       "    tp         (month, latitude, longitude) float32 0.001904 ... 0.001406</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-159c4811-79f0-4b40-83b9-2ac78d873149' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-159c4811-79f0-4b40-83b9-2ac78d873149' 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'>longitude</span>: 297</li><li><span class='xr-has-index'>latitude</span>: 297</li><li><span class='xr-has-index'>month</span>: 12</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f3926f12-4a9b-4600-a47b-db9182216027' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f3926f12-4a9b-4600-a47b-db9182216027' class='xr-section-summary' >Coordinates: <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-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>85.23 85.24 85.24 ... 85.88 85.88</div><input id='attrs-a82e834b-6a77-4648-a3c1-8f166caf344c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a82e834b-6a77-4648-a3c1-8f166caf344c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f8a4fef-00a3-440d-86c4-c76de9a96fe2' class='xr-var-data-in' type='checkbox'><label for='data-8f8a4fef-00a3-440d-86c4-c76de9a96fe2' title='Show/Hide data 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([85.235, 85.238, 85.242, ..., 85.876, 85.877, 85.878])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>28.09 28.12 28.26 ... 28.28 28.23</div><input id='attrs-abd4af76-79b3-43d3-a645-7a46ef4de225' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-abd4af76-79b3-43d3-a645-7a46ef4de225' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87695194-1a4b-432b-b655-9eab0230b6d4' class='xr-var-data-in' type='checkbox'><label for='data-87695194-1a4b-432b-b655-9eab0230b6d4' title='Show/Hide data 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([28.093, 28.116, 28.259, ..., 28.157, 28.28 , 28.225])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-24727c77-6028-42c2-a212-e355d5c4eecb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24727c77-6028-42c2-a212-e355d5c4eecb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-771ec48e-114b-43d5-9e18-9473531ca7d4' class='xr-var-data-in' type='checkbox'><label for='data-771ec48e-114b-43d5-9e18-9473531ca7d4' title='Show/Hide data 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([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-03ec7964-c0e1-4ffd-9cd7-67f0afeb95f0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-03ec7964-c0e1-4ffd-9cd7-67f0afeb95f0' 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>t2m</span></div><div class='xr-var-dims'>(month, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>280.6 280.6 280.6 ... 260.0 260.0</div><input id='attrs-28783830-1064-48e3-88c5-409f109ef7f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28783830-1064-48e3-88c5-409f109ef7f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-109672b6-7c61-498d-86f4-11fe4f7cbf52' class='xr-var-data-in' type='checkbox'><label for='data-109672b6-7c61-498d-86f4-11fe4f7cbf52' title='Show/Hide data 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([[[280.56946, 280.56946, 280.56946, ..., 269.96942, 269.96942,\n",
       "         269.96942],\n",
       "        [280.56946, 280.56946, 280.56946, ..., 269.96942, 269.96942,\n",
       "         269.96942],\n",
       "        [269.2345 , 269.2345 , 269.2345 , ..., 257.3972 , 257.3972 ,\n",
       "         257.3972 ],\n",
       "        ...,\n",
       "        [269.2345 , 269.2345 , 269.2345 , ..., 257.3972 , 257.3972 ,\n",
       "         257.3972 ],\n",
       "        [269.2345 , 269.2345 , 269.2345 , ..., 257.3972 , 257.3972 ,\n",
       "         257.3972 ],\n",
       "        [269.2345 , 269.2345 , 269.2345 , ..., 257.3972 , 257.3972 ,\n",
       "         257.3972 ]],\n",
       "\n",
       "       [[282.43875, 282.43875, 282.43875, ..., 270.9635 , 270.9635 ,\n",
       "         270.9635 ],\n",
       "        [282.43875, 282.43875, 282.43875, ..., 270.9635 , 270.9635 ,\n",
       "         270.9635 ],\n",
       "        [270.8381 , 270.8381 , 270.8381 , ..., 258.14713, 258.14713,\n",
       "         258.14713],\n",
       "...\n",
       "        [275.24057, 275.24057, 275.24057, ..., 262.81226, 262.81226,\n",
       "         262.81226],\n",
       "        [275.24057, 275.24057, 275.24057, ..., 262.81226, 262.81226,\n",
       "         262.81226],\n",
       "        [275.24057, 275.24057, 275.24057, ..., 262.81226, 262.81226,\n",
       "         262.81226]],\n",
       "\n",
       "       [[282.09808, 282.09808, 282.09808, ..., 272.3753 , 272.3753 ,\n",
       "         272.3753 ],\n",
       "        [282.09808, 282.09808, 282.09808, ..., 272.3753 , 272.3753 ,\n",
       "         272.3753 ],\n",
       "        [271.68317, 271.68317, 271.68317, ..., 260.0334 , 260.0334 ,\n",
       "         260.0334 ],\n",
       "        ...,\n",
       "        [271.68317, 271.68317, 271.68317, ..., 260.0334 , 260.0334 ,\n",
       "         260.0334 ],\n",
       "        [271.68317, 271.68317, 271.68317, ..., 260.0334 , 260.0334 ,\n",
       "         260.0334 ],\n",
       "        [271.68317, 271.68317, 271.68317, ..., 260.0334 , 260.0334 ,\n",
       "         260.0334 ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fal</span></div><div class='xr-var-dims'>(month, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1625 0.1625 ... 0.7449 0.7449</div><input id='attrs-b88f978e-94a9-43f1-912c-00415eeca11c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b88f978e-94a9-43f1-912c-00415eeca11c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4a7d249-f2fc-4f94-ae4c-4b5981c5e65e' class='xr-var-data-in' type='checkbox'><label for='data-b4a7d249-f2fc-4f94-ae4c-4b5981c5e65e' title='Show/Hide data 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([[[0.1624935 , 0.1624935 , 0.1624935 , ..., 0.48877174,\n",
       "         0.48877174, 0.48877174],\n",
       "        [0.1624935 , 0.1624935 , 0.1624935 , ..., 0.48877174,\n",
       "         0.48877174, 0.48877174],\n",
       "        [0.4396928 , 0.4396928 , 0.4396928 , ..., 0.7993281 ,\n",
       "         0.7993281 , 0.7993281 ],\n",
       "        ...,\n",
       "        [0.4396928 , 0.4396928 , 0.4396928 , ..., 0.7993281 ,\n",
       "         0.7993281 , 0.7993281 ],\n",
       "        [0.4396928 , 0.4396928 , 0.4396928 , ..., 0.7993281 ,\n",
       "         0.7993281 , 0.7993281 ],\n",
       "        [0.4396928 , 0.4396928 , 0.4396928 , ..., 0.7993281 ,\n",
       "         0.7993281 , 0.7993281 ]],\n",
       "\n",
       "       [[0.16953704, 0.16953704, 0.16953704, ..., 0.5451061 ,\n",
       "         0.5451061 , 0.5451061 ],\n",
       "        [0.16953704, 0.16953704, 0.16953704, ..., 0.5451061 ,\n",
       "         0.5451061 , 0.5451061 ],\n",
       "        [0.48086596, 0.48086596, 0.48086596, ..., 0.8300914 ,\n",
       "         0.8300914 , 0.8300914 ],\n",
       "...\n",
       "        [0.16395253, 0.16395253, 0.16395253, ..., 0.7315829 ,\n",
       "         0.7315829 , 0.7315829 ],\n",
       "        [0.16395253, 0.16395253, 0.16395253, ..., 0.7315829 ,\n",
       "         0.7315829 , 0.7315829 ],\n",
       "        [0.16395253, 0.16395253, 0.16395253, ..., 0.7315829 ,\n",
       "         0.7315829 , 0.7315829 ]],\n",
       "\n",
       "       [[0.13846701, 0.13846701, 0.13846701, ..., 0.31984645,\n",
       "         0.31984645, 0.31984645],\n",
       "        [0.13846701, 0.13846701, 0.13846701, ..., 0.31984645,\n",
       "         0.31984645, 0.31984645],\n",
       "        [0.27754185, 0.27754185, 0.27754185, ..., 0.7448799 ,\n",
       "         0.7448799 , 0.7448799 ],\n",
       "        ...,\n",
       "        [0.27754185, 0.27754185, 0.27754185, ..., 0.7448799 ,\n",
       "         0.7448799 , 0.7448799 ],\n",
       "        [0.27754185, 0.27754185, 0.27754185, ..., 0.7448799 ,\n",
       "         0.7448799 , 0.7448799 ],\n",
       "        [0.27754185, 0.27754185, 0.27754185, ..., 0.7448799 ,\n",
       "         0.7448799 , 0.7448799 ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sd</span></div><div class='xr-var-dims'>(month, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.01093 0.01093 ... 0.08625 0.08625</div><input id='attrs-b55bd2cb-d672-49fc-bfe0-38af11b79c8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b55bd2cb-d672-49fc-bfe0-38af11b79c8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-673208c3-ea89-4110-b0fa-c10640363af7' class='xr-var-data-in' type='checkbox'><label for='data-673208c3-ea89-4110-b0fa-c10640363af7' title='Show/Hide data 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([[[1.0931648e-02, 1.0931648e-02, 1.0931648e-02, ...,\n",
       "         4.8879329e-02, 4.8879329e-02, 4.8879329e-02],\n",
       "        [1.0931648e-02, 1.0931648e-02, 1.0931648e-02, ...,\n",
       "         4.8879329e-02, 4.8879329e-02, 4.8879329e-02],\n",
       "        [5.3484157e-02, 5.3484157e-02, 5.3484157e-02, ...,\n",
       "         1.4445677e-01, 1.4445677e-01, 1.4445677e-01],\n",
       "        ...,\n",
       "        [5.3484157e-02, 5.3484157e-02, 5.3484157e-02, ...,\n",
       "         1.4445677e-01, 1.4445677e-01, 1.4445677e-01],\n",
       "        [5.3484157e-02, 5.3484157e-02, 5.3484157e-02, ...,\n",
       "         1.4445677e-01, 1.4445677e-01, 1.4445677e-01],\n",
       "        [5.3484157e-02, 5.3484157e-02, 5.3484157e-02, ...,\n",
       "         1.4445677e-01, 1.4445677e-01, 1.4445677e-01]],\n",
       "\n",
       "       [[2.4810493e-02, 2.4810493e-02, 2.4810493e-02, ...,\n",
       "         1.0206423e-01, 1.0206423e-01, 1.0206423e-01],\n",
       "        [2.4810493e-02, 2.4810493e-02, 2.4810493e-02, ...,\n",
       "         1.0206423e-01, 1.0206423e-01, 1.0206423e-01],\n",
       "        [1.2028829e-01, 1.2028829e-01, 1.2028829e-01, ...,\n",
       "         2.2638601e-01, 2.2638601e-01, 2.2638601e-01],\n",
       "...\n",
       "        [2.6836917e-03, 2.6836917e-03, 2.6836917e-03, ...,\n",
       "         5.2898422e-02, 5.2898422e-02, 5.2898422e-02],\n",
       "        [2.6836917e-03, 2.6836917e-03, 2.6836917e-03, ...,\n",
       "         5.2898422e-02, 5.2898422e-02, 5.2898422e-02],\n",
       "        [2.6836917e-03, 2.6836917e-03, 2.6836917e-03, ...,\n",
       "         5.2898422e-02, 5.2898422e-02, 5.2898422e-02]],\n",
       "\n",
       "       [[2.6587397e-03, 2.6587397e-03, 2.6587397e-03, ...,\n",
       "         1.7968692e-02, 1.7968692e-02, 1.7968692e-02],\n",
       "        [2.6587397e-03, 2.6587397e-03, 2.6587397e-03, ...,\n",
       "         1.7968692e-02, 1.7968692e-02, 1.7968692e-02],\n",
       "        [1.4142759e-02, 1.4142759e-02, 1.4142759e-02, ...,\n",
       "         8.6251654e-02, 8.6251654e-02, 8.6251654e-02],\n",
       "        ...,\n",
       "        [1.4142759e-02, 1.4142759e-02, 1.4142759e-02, ...,\n",
       "         8.6251654e-02, 8.6251654e-02, 8.6251654e-02],\n",
       "        [1.4142759e-02, 1.4142759e-02, 1.4142759e-02, ...,\n",
       "         8.6251654e-02, 8.6251654e-02, 8.6251654e-02],\n",
       "        [1.4142759e-02, 1.4142759e-02, 1.4142759e-02, ...,\n",
       "         8.6251654e-02, 8.6251654e-02, 8.6251654e-02]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slhf</span></div><div class='xr-var-dims'>(month, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-3.059e+06 ... -1.935e+05</div><input id='attrs-8143c212-8fb9-4822-b201-49c0941f1a98' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8143c212-8fb9-4822-b201-49c0941f1a98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fc47f95-dee5-464f-988e-14bde13666bb' class='xr-var-data-in' type='checkbox'><label for='data-0fc47f95-dee5-464f-988e-14bde13666bb' title='Show/Hide data 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([[[-3058500.5  , -3058500.5  , -3058500.5  , ..., -1396831.9  ,\n",
       "         -1396831.9  , -1396831.9  ],\n",
       "        [-3058500.5  , -3058500.5  , -3058500.5  , ..., -1396831.9  ,\n",
       "         -1396831.9  , -1396831.9  ],\n",
       "        [-1148321.   , -1148321.   , -1148321.   , ...,   -73937.016,\n",
       "           -73937.016,   -73937.016],\n",
       "        ...,\n",
       "        [-1148321.   , -1148321.   , -1148321.   , ...,   -73937.016,\n",
       "           -73937.016,   -73937.016],\n",
       "        [-1148321.   , -1148321.   , -1148321.   , ...,   -73937.016,\n",
       "           -73937.016,   -73937.016],\n",
       "        [-1148321.   , -1148321.   , -1148321.   , ...,   -73937.016,\n",
       "           -73937.016,   -73937.016]],\n",
       "\n",
       "       [[-4012124.8  , -4012124.8  , -4012124.8  , ..., -1488387.9  ,\n",
       "         -1488387.9  , -1488387.9  ],\n",
       "        [-4012124.8  , -4012124.8  , -4012124.8  , ..., -1488387.9  ,\n",
       "         -1488387.9  , -1488387.9  ],\n",
       "        [-1352244.5  , -1352244.5  , -1352244.5  , ...,   -52223.61 ,\n",
       "           -52223.61 ,   -52223.61 ],\n",
       "...\n",
       "        [-3256027.   , -3256027.   , -3256027.   , ...,  -439654.84 ,\n",
       "          -439654.84 ,  -439654.84 ],\n",
       "        [-3256027.   , -3256027.   , -3256027.   , ...,  -439654.84 ,\n",
       "          -439654.84 ,  -439654.84 ],\n",
       "        [-3256027.   , -3256027.   , -3256027.   , ...,  -439654.84 ,\n",
       "          -439654.84 ,  -439654.84 ]],\n",
       "\n",
       "       [[-3027217.8  , -3027217.8  , -3027217.8  , ..., -2114237.5  ,\n",
       "         -2114237.5  , -2114237.5  ],\n",
       "        [-3027217.8  , -3027217.8  , -3027217.8  , ..., -2114237.5  ,\n",
       "         -2114237.5  , -2114237.5  ],\n",
       "        [-1826628.2  , -1826628.2  , -1826628.2  , ...,  -193514.69 ,\n",
       "          -193514.69 ,  -193514.69 ],\n",
       "        ...,\n",
       "        [-1826628.2  , -1826628.2  , -1826628.2  , ...,  -193514.69 ,\n",
       "          -193514.69 ,  -193514.69 ],\n",
       "        [-1826628.2  , -1826628.2  , -1826628.2  , ...,  -193514.69 ,\n",
       "          -193514.69 ,  -193514.69 ],\n",
       "        [-1826628.2  , -1826628.2  , -1826628.2  , ...,  -193514.69 ,\n",
       "          -193514.69 ,  -193514.69 ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(month, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.001904 0.001904 ... 0.001406</div><input id='attrs-784a0da9-4dc7-46f3-aae0-fbec9bb0e7e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-784a0da9-4dc7-46f3-aae0-fbec9bb0e7e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5330a7c-b615-4c87-9d9d-3ae91e17b850' class='xr-var-data-in' type='checkbox'><label for='data-a5330a7c-b615-4c87-9d9d-3ae91e17b850' title='Show/Hide data 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([[[0.00190404, 0.00190404, 0.00190404, ..., 0.00287445,\n",
       "         0.00287445, 0.00287445],\n",
       "        [0.00190404, 0.00190404, 0.00190404, ..., 0.00287445,\n",
       "         0.00287445, 0.00287445],\n",
       "        [0.00264763, 0.00264763, 0.00264763, ..., 0.00260014,\n",
       "         0.00260014, 0.00260014],\n",
       "        ...,\n",
       "        [0.00264763, 0.00264763, 0.00264763, ..., 0.00260014,\n",
       "         0.00260014, 0.00260014],\n",
       "        [0.00264763, 0.00264763, 0.00264763, ..., 0.00260014,\n",
       "         0.00260014, 0.00260014],\n",
       "        [0.00264763, 0.00264763, 0.00264763, ..., 0.00260014,\n",
       "         0.00260014, 0.00260014]],\n",
       "\n",
       "       [[0.00259962, 0.00259962, 0.00259962, ..., 0.00426947,\n",
       "         0.00426947, 0.00426947],\n",
       "        [0.00259962, 0.00259962, 0.00259962, ..., 0.00426947,\n",
       "         0.00426947, 0.00426947],\n",
       "        [0.00378626, 0.00378626, 0.00378626, ..., 0.00361515,\n",
       "         0.00361515, 0.00361515],\n",
       "...\n",
       "        [0.00183247, 0.00183247, 0.00183247, ..., 0.00113605,\n",
       "         0.00113605, 0.00113605],\n",
       "        [0.00183247, 0.00183247, 0.00183247, ..., 0.00113605,\n",
       "         0.00113605, 0.00113605],\n",
       "        [0.00183247, 0.00183247, 0.00183247, ..., 0.00113605,\n",
       "         0.00113605, 0.00113605]],\n",
       "\n",
       "       [[0.00167202, 0.00167202, 0.00167202, ..., 0.00201025,\n",
       "         0.00201025, 0.00201025],\n",
       "        [0.00167202, 0.00167202, 0.00167202, ..., 0.00201025,\n",
       "         0.00201025, 0.00201025],\n",
       "        [0.00166971, 0.00166971, 0.00166971, ..., 0.00140557,\n",
       "         0.00140557, 0.00140557],\n",
       "        ...,\n",
       "        [0.00166971, 0.00166971, 0.00166971, ..., 0.00140557,\n",
       "         0.00140557, 0.00140557],\n",
       "        [0.00166971, 0.00166971, 0.00166971, ..., 0.00140557,\n",
       "         0.00140557, 0.00140557],\n",
       "        [0.00166971, 0.00166971, 0.00166971, ..., 0.00140557,\n",
       "         0.00140557, 0.00140557]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-25c993b4-ecd4-4bb8-a8c1-62cfbe522e38' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-25c993b4-ecd4-4bb8-a8c1-62cfbe522e38' 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>\n",
       "Dimensions:    (longitude: 297, latitude: 297, month: 12)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float64 85.23 85.24 85.24 85.25 ... 85.88 85.88 85.88\n",
       "  * latitude   (latitude) float64 28.09 28.12 28.26 28.09 ... 28.16 28.28 28.23\n",
       "  * month      (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    t2m        (month, latitude, longitude) float32 280.6 280.6 ... 260.0 260.0\n",
       "    fal        (month, latitude, longitude) float32 0.1625 0.1625 ... 0.7449\n",
       "    sd         (month, latitude, longitude) float32 0.01093 0.01093 ... 0.08625\n",
       "    slhf       (month, latitude, longitude) float32 -3.059e+06 ... -1.935e+05\n",
       "    tp         (month, latitude, longitude) float32 0.001904 ... 0.001406"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_points_monthly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "0d1c98b6-0044-4242-9eb4-1c50182cbe0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(240,)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(mean_points_monthly.longitude.values).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "53ae0216-cc51-41ad-95e0-00741550cb7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['t2m', 'fal', 'sd', 'slhf', 'tp'], dtype='object')"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_points_monthly_df = mean_points_monthly.to_dataframe()\n",
    "mean_points_monthly_df\n",
    "mean_points_monthly_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "5cc858c6-6af0-474c-9a15-b3c7d2febfbf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>t2m</th>\n",
       "      <th>fal</th>\n",
       "      <th>sd</th>\n",
       "      <th>slhf</th>\n",
       "      <th>tp</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>month</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 rowspan=\"5\" valign=\"top\">85.235</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">28.093</th>\n",
       "      <th>1</th>\n",
       "      <td>280.569458</td>\n",
       "      <td>0.162493</td>\n",
       "      <td>0.010932</td>\n",
       "      <td>-3.058500e+06</td>\n",
       "      <td>0.001904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>282.438751</td>\n",
       "      <td>0.169537</td>\n",
       "      <td>0.024810</td>\n",
       "      <td>-4.012125e+06</td>\n",
       "      <td>0.002600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>285.688324</td>\n",
       "      <td>0.166251</td>\n",
       "      <td>0.028393</td>\n",
       "      <td>-5.452529e+06</td>\n",
       "      <td>0.002122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>288.934479</td>\n",
       "      <td>0.149517</td>\n",
       "      <td>0.007083</td>\n",
       "      <td>-6.688130e+06</td>\n",
       "      <td>0.002719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>291.407043</td>\n",
       "      <td>0.137159</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>-7.718880e+06</td>\n",
       "      <td>0.006691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">85.878</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">28.225</th>\n",
       "      <th>8</th>\n",
       "      <td>276.712494</td>\n",
       "      <td>0.399902</td>\n",
       "      <td>0.008171</td>\n",
       "      <td>-3.738227e+06</td>\n",
       "      <td>0.008565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>274.539429</td>\n",
       "      <td>0.439551</td>\n",
       "      <td>0.008703</td>\n",
       "      <td>-3.454193e+06</td>\n",
       "      <td>0.005438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>267.887238</td>\n",
       "      <td>0.588792</td>\n",
       "      <td>0.021481</td>\n",
       "      <td>-1.879928e+06</td>\n",
       "      <td>0.002096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>262.812256</td>\n",
       "      <td>0.731583</td>\n",
       "      <td>0.052898</td>\n",
       "      <td>-4.396548e+05</td>\n",
       "      <td>0.001136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>260.033386</td>\n",
       "      <td>0.744880</td>\n",
       "      <td>0.086252</td>\n",
       "      <td>-1.935147e+05</td>\n",
       "      <td>0.001406</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1058508 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 t2m       fal        sd          slhf  \\\n",
       "longitude latitude month                                                 \n",
       "85.235    28.093   1      280.569458  0.162493  0.010932 -3.058500e+06   \n",
       "                   2      282.438751  0.169537  0.024810 -4.012125e+06   \n",
       "                   3      285.688324  0.166251  0.028393 -5.452529e+06   \n",
       "                   4      288.934479  0.149517  0.007083 -6.688130e+06   \n",
       "                   5      291.407043  0.137159  0.000004 -7.718880e+06   \n",
       "...                              ...       ...       ...           ...   \n",
       "85.878    28.225   8      276.712494  0.399902  0.008171 -3.738227e+06   \n",
       "                   9      274.539429  0.439551  0.008703 -3.454193e+06   \n",
       "                   10     267.887238  0.588792  0.021481 -1.879928e+06   \n",
       "                   11     262.812256  0.731583  0.052898 -4.396548e+05   \n",
       "                   12     260.033386  0.744880  0.086252 -1.935147e+05   \n",
       "\n",
       "                                tp  \n",
       "longitude latitude month            \n",
       "85.235    28.093   1      0.001904  \n",
       "                   2      0.002600  \n",
       "                   3      0.002122  \n",
       "                   4      0.002719  \n",
       "                   5      0.006691  \n",
       "...                            ...  \n",
       "85.878    28.225   8      0.008565  \n",
       "                   9      0.005438  \n",
       "                   10     0.002096  \n",
       "                   11     0.001136  \n",
       "                   12     0.001406  \n",
       "\n",
       "[1058508 rows x 5 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_points_monthly_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "2abe42b9-9d5b-4888-9f61-546490452af1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# pivot table so that columns correspond to months: \n",
    "\n",
    "mean_points_monthly_df_t2m = mean_points_monthly_df.pivot_table(index=['longitude', 'latitude'], \n",
    "                                                                 columns='month', values='t2m')\n",
    "\n",
    "# rename columns\n",
    "mean_points_monthly_df_t2m.columns = ['t2m_1','t2m_2','t2m_3','t2m_4','t2m_5','t2m_6','t2m_7',\n",
    "                                        't2m_8','t2m_9','t2m_10','t2m_11','t2m_12']\n",
    "\n",
    "# mean_points_monthly_df_fal = mean_points_monthly_df.pivot_table(index=['longitude', 'latitude'], \n",
    "                                                                # columns='month', values='fal')\n",
    "\n",
    "# mean_points_monthly_df_sd = mean_points_monthly_df.pivot_table(index=['longitude', 'latitude'], \n",
    "                                                                # columns='month', values='sd')\n",
    "\n",
    "# mean_points_monthly_df_slhf = mean_points_monthly_df.pivot_table(index=['longitude', 'latitude'], \n",
    "                                                                # columns='month', values='slhf')\n",
    "\n",
    "mean_points_monthly_df_tp = mean_points_monthly_df.pivot_table(index=['longitude', 'latitude'], \n",
    "                                                                columns='month', values='tp')\n",
    "\n",
    "mean_points_monthly_df_tp.columns = ['tp_1','tp_2','tp_3','tp_4','tp_5','tp_6','tp_7','tp_8',\n",
    "                                     'tp_9','tp_10','tp_11','tp_12']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "8903ae82-1dee-4862-8686-3d13cd73bf4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>t2m_1</th>\n",
       "      <th>t2m_2</th>\n",
       "      <th>t2m_3</th>\n",
       "      <th>t2m_4</th>\n",
       "      <th>t2m_5</th>\n",
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       "      <th>t2m_11</th>\n",
       "      <th>t2m_12</th>\n",
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       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th></th>\n",
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       "      <td>288.934479</td>\n",
       "      <td>291.407043</td>\n",
       "      <td>293.462250</td>\n",
       "      <td>293.759399</td>\n",
       "      <td>293.706146</td>\n",
       "      <td>292.576080</td>\n",
       "      <td>289.061920</td>\n",
       "      <td>285.20462</td>\n",
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       "      <th>28.116</th>\n",
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       "      <td>293.759399</td>\n",
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       "      <td>292.576080</td>\n",
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       "      <th>28.089</th>\n",
       "      <td>280.569458</td>\n",
       "      <td>282.438751</td>\n",
       "      <td>285.688324</td>\n",
       "      <td>288.934479</td>\n",
       "      <td>291.407043</td>\n",
       "      <td>293.462250</td>\n",
       "      <td>293.759399</td>\n",
       "      <td>293.706146</td>\n",
       "      <td>292.576080</td>\n",
       "      <td>289.061920</td>\n",
       "      <td>285.20462</td>\n",
       "      <td>282.098083</td>\n",
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       "    <tr>\n",
       "      <th>28.298</th>\n",
       "      <td>269.234497</td>\n",
       "      <td>270.838104</td>\n",
       "      <td>273.857086</td>\n",
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      "text/plain": [
       "                         t2m_1       t2m_2       t2m_3       t2m_4  \\\n",
       "longitude latitude                                                   \n",
       "85.235    28.093    280.569458  282.438751  285.688324  288.934479   \n",
       "          28.116    280.569458  282.438751  285.688324  288.934479   \n",
       "          28.259    269.234497  270.838104  273.857086  277.412933   \n",
       "          28.089    280.569458  282.438751  285.688324  288.934479   \n",
       "          28.298    269.234497  270.838104  273.857086  277.412933   \n",
       "\n",
       "                         t2m_5       t2m_6       t2m_7       t2m_8  \\\n",
       "longitude latitude                                                   \n",
       "85.235    28.093    291.407043  293.462250  293.759399  293.706146   \n",
       "          28.116    291.407043  293.462250  293.759399  293.706146   \n",
       "          28.259    281.508423  284.956146  286.316895  286.055450   \n",
       "          28.089    291.407043  293.462250  293.759399  293.706146   \n",
       "          28.298    281.508423  284.956146  286.316895  286.055450   \n",
       "\n",
       "                         t2m_9      t2m_10     t2m_11      t2m_12  \n",
       "longitude latitude                                                 \n",
       "85.235    28.093    292.576080  289.061920  285.20462  282.098083  \n",
       "          28.116    292.576080  289.061920  285.20462  282.098083  \n",
       "          28.259    284.347351  279.690582  275.24057  271.683167  \n",
       "          28.089    292.576080  289.061920  285.20462  282.098083  \n",
       "          28.298    284.347351  279.690582  275.24057  271.683167  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_points_monthly_df_t2m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "015c8efa-b267-4426-b4a5-3ffa48967f9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# reset index - make latitude and longitude new columns \n",
    "# rename columns \n",
    "mean_points_monthly_df_tp = mean_points_monthly_df_tp.reset_index()\n",
    "mean_points_monthly_df_tp_renamed = mean_points_monthly_df_tp.rename(columns = {'longitude': 'x_wgs', 'latitude': 'y_wgs'}) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "f88f6733-662c-44c5-b991-3d809021ca5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# reset index - make latitude and longitude new columns \n",
    "# rename columns \n",
    "mean_points_monthly_df_t2m = mean_points_monthly_df_t2m.reset_index()\n",
    "mean_points_monthly_df_t2m_renamed = mean_points_monthly_df_t2m.rename(columns = {'longitude': 'x_wgs', 'latitude': 'y_wgs'}) \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "a5a93297-a4a2-436e-adda-c57585d32256",
   "metadata": {},
   "outputs": [],
   "source": [
    "# add to catchments dataset (merge) \n",
    "\n",
    "#  merge tables: take 'smaller' table and add the 'bigger' table to it \n",
    "# (otherwise there will be a lot of nan vallues, .dropna - if there are any)\n",
    "\n",
    "catchments_climate1 = catchments_climate.merge(mean_points_monthly_df_tp_renamed, on=['x_wgs', 'y_wgs'], how='left').drop_duplicates()\n",
    "catchments_climate1 = catchments_climate1.merge(mean_points_monthly_df_t2m_renamed, on=['x_wgs', 'y_wgs'], how='left').drop_duplicates()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9806ce6-51bc-49a3-9928-fadc4c0e0d64",
   "metadata": {},
   "source": [
    "### Monsoon precipitation (just sum the columns) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "adb40aeb-774e-49ec-abf0-d84b87451f5c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# mansoon - may - october \n",
    "catchments_climate1_mansoon = catchments_climate1\n",
    "\n",
    "catchments_climate1_mansoon['mansoon_tp'] = catchments_climate1.tp_5 + catchments_climate1.tp_6 + catchments_climate1.tp_7 + catchments_climate1.tp_8 + catchments_climate1.tp_9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "4c8cd994-13eb-42c3-9913-72fb4eaf2f44",
   "metadata": {},
   "outputs": [],
   "source": [
    "catchments_climate1_mansoon['location'] = 'langtang'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e9037fc-2cd5-435c-97d9-961c2c712a3d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "3cd98e8d-941d-4b79-b65e-60f87a78fd9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# catchments_climate1_mansoon.to_csv('langtang_and_ladakh/langtang_catchments.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "457c3416-7f25-4256-8173-c9dcabf2438d",
   "metadata": {},
   "source": [
    "## 2. seasonal avarages "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f90d412-2115-4316-8793-17320f7f0321",
   "metadata": {},
   "outputs": [],
   "source": [
    "# tutorial: \n",
    "# https://xarray.pydata.org/en/v0.14.1/examples/monthly-means.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f7dee82e-4987-49e7-9114-1130d5717132",
   "metadata": {},
   "outputs": [],
   "source": [
    "# only used for comparisons\n",
    "fseasons = f.groupby('time.season').mean('time')\n",
    "fseasons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e318003a-7e50-4709-bca1-6e3818940c3a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "495a3cb2-f4a7-4828-83e0-6d0242e1444a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "62203702-f500-4384-9675-f04c4b82b9c8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed6deba9-782c-454c-8ad7-839df1b3b1a2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0a156bd-3542-48ce-9d41-525e8af1fc0c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a7d79e03-c003-43a0-bda5-667e36ab69c9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "753d2c1c-90db-4e03-b319-462e2b91b0c8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ff8ad1a-0b81-49fd-94f6-04a46c64b895",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19af4300-5eec-4d9d-b136-f0c6309c748e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7151ed8b-7919-41a9-8b98-e1347ac1b681",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ebdc6891-6087-4357-bc53-43c97ac6dfc9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5b3a17ac-5ec6-4070-9ca6-097dd0e6685e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d1b034ce-5e5c-4f06-bb1f-e1ee6148aff9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a560fece-470c-4b85-8ee3-302b3bc5318c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "461b5e22-7853-4cce-81bf-fc29b968a62c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "67e16959-46bb-4a54-a6fd-e8b596b9ef91",
   "metadata": {},
   "source": [
    "#### 3. monsoon times: may - october"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "696d003d-568c-4f8e-a96c-0035e4649683",
   "metadata": {},
   "outputs": [],
   "source": [
    "# same idea as seasonal averages: \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "690a4035-7345-4f1a-9a7d-70cb8f79a959",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87d91921-eb80-4b5c-a7a6-67a120ef792b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "819d93ca-0c16-4e58-8c75-dff0a8cdfefa",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "24a1d627-b202-41ef-ab05-ad8971114625",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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