diff --git a/datasets/ecmwf-forecast/ecmwf-forecast-example.ipynb b/datasets/ecmwf-forecast/ecmwf-forecast-example.ipynb
index 9393e58a..7f509f4e 100755
--- a/datasets/ecmwf-forecast/ecmwf-forecast-example.ipynb
+++ b/datasets/ecmwf-forecast/ecmwf-forecast-example.ipynb
@@ -7,30 +7,76 @@
    "source": [
     "## Accessing ECMWF Open Data – Real Time\n",
     "\n",
-    "The Planetary Computer includes data from the ECMWF Open Data (real time) program. See the [dataset](https://planetarycomputer.microsoft.com/dataset/ecmwf-forecast) page and [ECMWF Uesr Guide](https://confluence.ecmwf.int/display/UDOC/ECMWF+Open+Data+-+Real+Time) for more.\n",
+    "The Planetary Computer includes data from the ECMWF Open Data (real time) program. See the [dataset](https://planetarycomputer.microsoft.com/dataset/ecmwf-forecast) page and [ECMWF User Guide](https://confluence.ecmwf.int/display/UDOC/ECMWF+Open+Data+-+Real+Time) for more.\n",
     "\n",
-    "Each item in this collection includes metadata about the *stream* (or forecasting system) and *type* that produced that particular dataset. Filter on these values to select the item of interest. For example, we can select data from the `wave` stream, with the `fc` type that are forecast `0h` hours out."
+    "A separate collection exists for each combination of *stream* (or forecasting system) and *type*, namely, enfo-ep, oper-fc, scda-fc, scwv-fc, waef-ef, waef-ep, wave-fc. This notebook will focus on the wave-fc collection.\n",
+    "\n",
+    "Each item in this collection includes metadata about the data that produced that particular dataset. Filter on these values to select the item of interest. For example, we can select data that are forecast `0h` hours out."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "667f654a",
+   "execution_count": 1,
+   "id": "604b112f-e25a-417d-a462-61c602dfbec5",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda/envs/py38_default/lib/python3.8/site-packages/gribapi/__init__.py:23: UserWarning: ecCodes 2.21.0 or higher is recommended. You are running version 2.16.0\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
    "source": [
+    "import cartopy.crs as ccrs\n",
+    "import fsspec\n",
+    "import matplotlib.pyplot as plt\n",
     "import pystac_client\n",
     "import planetary_computer\n",
+    "import urllib.request\n",
+    "import xarray as xr\n",
     "\n",
+    "#Loading custom codec\n",
+    "from stactools.ecmwf_forecast.range_codec import Range\n",
+    "from numcodecs.registry import register_codec\n",
+    "register_codec(Range)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "667f654a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/anaconda/envs/py38_default/lib/python3.8/site-packages/pystac_client/item_search.py:846: FutureWarning: get_all_items() is deprecated, use item_collection() instead.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1271"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
     "catalog = pystac_client.Client.open(\n",
-    "    \"https://planetarycomputer.microsoft.com/api/stac/v1\",\n",
+    "    \"https://pct-apis-staging.westeurope.cloudapp.azure.com/stac/\",\n",
     "    modifier=planetary_computer.sign_inplace,\n",
     ")\n",
     "search = catalog.search(\n",
-    "    collections=[\"ecmwf-forecast\"],\n",
+    "    collections=[\"ecmwf-forecast-wave-fc\"],\n",
     "    query={\n",
-    "        \"ecmwf:stream\": {\"eq\": \"wave\"},\n",
-    "        \"ecmwf:type\": {\"eq\": \"fc\"},\n",
     "        \"ecmwf:step\": {\"eq\": \"0h\"},\n",
     "    },\n",
     ")\n",
@@ -48,17 +94,1307 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "e3ac3d8b-042a-42d0-8a57-383f4562da5e",
    "metadata": {},
    "outputs": [
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+       "            <span class=\"pystac-key\">pp1d/0.0.0</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 3 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"https://ai4edataeuwest.blob.core.windows.net/ecmwf/20231019/00z/0p4-beta/wave/20231019000000-0h-wave-fc.grib2\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">1</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">992461</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">2</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">340620</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">longitude/0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"base64:AAAAAACAZsAAAAAAAIBmQJqZmZmZmdk/\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">mp2/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"mp2\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">mp2/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"mp2\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Mean zero-crossing wave period\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140221,\"GRIB_shortName\":\"mp2\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"s\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Mean zero-crossing wave period\",\"standard_name\":\"unknown\",\"units\":\"s\"}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">mwd/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"mwd\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">mwd/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"mwd\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Mean wave direction\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140230,\"GRIB_shortName\":\"mwd\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"Degree true\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Mean wave direction\",\"standard_name\":\"unknown\",\"units\":\"Degree true\"}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">mwp/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"mwp\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">mwp/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"mwp\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Mean wave period\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140232,\"GRIB_shortName\":\"mwp\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"s\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Mean wave period\",\"standard_name\":\"unknown\",\"units\":\"s\"}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">swh/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"swh\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">swh/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"swh\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Significant height of combined wind waves and swell\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140229,\"GRIB_shortName\":\"swh\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"m\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Significant height of combined wind waves and swell\",\"standard_name\":\"unknown\",\"units\":\"m\"}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">pp1d/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"pp1d\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">pp1d/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"pp1d\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Peak wave period\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140231,\"GRIB_shortName\":\"pp1d\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"s\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Peak wave period\",\"standard_name\":\"unknown\",\"units\":\"s\"}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">step/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[1],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":null,\"order\":\"C\",\"shape\":[1],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">step/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"_ARRAY_DIMENSIONS\":[\"time\"],\"long_name\":\"time since forecast_reference_time\",\"standard_name\":\"forecast_period\",\"units\":\"hours\"}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">time/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"base64:ewogICAgImNodW5rcyI6IFsKICAgICAgICAxCiAgICBdLAogICAgImNvbXByZXNzb3IiOiBudWxsLAogICAgImR0eXBlIjogIjxpOCIsCiAgICAiZmlsbF92YWx1ZSI6IG51bGwsCiAgICAiZmlsdGVycyI6IG51bGwsCiAgICAib3JkZXIiOiAiQyIsCiAgICAic2hhcGUiOiBbCiAgICAgICAgMQogICAgXSwKICAgICJ6YXJyX2Zvcm1hdCI6IDIKfQ==\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">time/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"base64:ewogICAgIl9BUlJBWV9ESU1FTlNJT05TIjogWwogICAgICAgICJ0aW1lIgogICAgXSwKICAgICJjYWxlbmRhciI6ICJwcm9sZXB0aWNfZ3JlZ29yaWFuIiwKICAgICJsb25nX25hbWUiOiAiaW5pdGlhbCB0aW1lIG9mIGZvcmVjYXN0IiwKICAgICJzdGFuZGFyZF9uYW1lIjogImZvcmVjYXN0X3JlZmVyZW5jZV90aW1lIiwKICAgICJ1bml0cyI6ICJzZWNvbmRzIHNpbmNlIDE5NzAtMDEtMDFUMDA6MDA6MDAiCn0=\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">valid_time/0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"base64:gHEwZQAAAAA=\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">meanSea/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[1],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":null,\"order\":\"C\",\"shape\":[1],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">meanSea/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"_ARRAY_DIMENSIONS\":[\"time\"]}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">latitude/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[451],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"id\": \"range\"}],\"order\":\"C\",\"shape\":[451],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">latitude/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"_ARRAY_DIMENSIONS\":[\"latitude\"],\"long_name\":\"latitude\",\"standard_name\":\"latitude\",\"units\":\"degrees_north\"}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">longitude/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"id\": \"range\"}],\"order\":\"C\",\"shape\":[900],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">longitude/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"_ARRAY_DIMENSIONS\":[\"longitude\"],\"long_name\":\"longitude\",\"standard_name\":\"longitude\",\"units\":\"degrees_east\"}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">valid_time/.zarray</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"chunks\":[1],\"compressor\":null,\"dtype\":\"<i8\",\"fill_value\":null,\"filters\":null,\"order\":\"C\",\"shape\":[1],\"zarr_format\":2}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">valid_time/.zattrs</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"{\"_ARRAY_DIMENSIONS\":[\"time\"],\"calendar\":\"proleptic_gregorian\",\"long_name\":\"time\",\"standard_name\":\"time\",\"units\":\"seconds since 1970-01-01T00:00:00\"}\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">version</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">1</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">ecmwf:forecast_datetime</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"2023-10-19T00:00:00Z\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">ecmwf:reference_datetime</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"2023-10-19T00:00:00Z\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-key\">geometry</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">type</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"Polygon\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">coordinates</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 1 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">0</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 5 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">0</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 2 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">180</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">1</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">-90</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">1</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 2 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">180</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">1</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">90</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">2</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 2 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">-180</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">1</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">90</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">3</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 2 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">-180</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">1</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">-90</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">4</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 2 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">180</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">1</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">-90</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">links</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 4 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-key\">0</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">rel</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"collection\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">href</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"https://pct-apis-staging.westeurope.cloudapp.azure.com/stac/collections/ecmwf-forecast-wave-fc\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">type</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"application/json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-key\">1</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">rel</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"parent\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">href</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"https://pct-apis-staging.westeurope.cloudapp.azure.com/stac/collections/ecmwf-forecast-wave-fc\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">type</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"application/json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-key\">2</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">rel</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"root\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">href</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"https://pct-apis-staging.westeurope.cloudapp.azure.com/stac/\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">type</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"application/json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">title</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"Microsoft Planetary Computer STAC API\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-key\">3</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">rel</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"self\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">href</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"https://pct-apis-staging.westeurope.cloudapp.azure.com/stac/collections/ecmwf-forecast-wave-fc/items/ecmwf-2023-10-19T00-wave-fc-0h\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">type</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"application/geo+json\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-key\">assets</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-key\">data</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">href</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"https://ai4edataeuwest.blob.core.windows.net/ecmwf/20231019/00z/0p4-beta/wave/20231019000000-0h-wave-fc.grib2?st=2023-10-18T17%3A43%3A36Z&se=2023-10-19T18%3A28%3A36Z&sp=rl&sv=2021-06-08&sr=c&skoid=c85c15d6-d1ae-42d4-af60-e2ca0f81359b&sktid=72f988bf-86f1-41af-91ab-2d7cd011db47&skt=2023-10-19T17%3A42%3A26Z&ske=2023-10-26T17%3A42%3A26Z&sks=b&skv=2021-06-08&sig=Sk8tgcshG8wDd8CuuvVZi6CdSEPi1jNIeAYlNBfZBlk%3D\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">type</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"application/wmo-GRIB2\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">roles</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 1 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"data\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li><details>\n",
+       "            <summary class=\"pystac-summary\"><span class=\"pystac-key\">index</span></summary>\n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">href</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"https://ai4edataeuwest.blob.core.windows.net/ecmwf/20231019/00z/0p4-beta/wave/20231019000000-0h-wave-fc.index?st=2023-10-18T17%3A43%3A36Z&se=2023-10-19T18%3A28%3A36Z&sp=rl&sv=2021-06-08&sr=c&skoid=c85c15d6-d1ae-42d4-af60-e2ca0f81359b&sktid=72f988bf-86f1-41af-91ab-2d7cd011db47&skt=2023-10-19T17%3A42%3A26Z&ske=2023-10-26T17%3A42%3A26Z&sks=b&skv=2021-06-08&sig=Sk8tgcshG8wDd8CuuvVZi6CdSEPi1jNIeAYlNBfZBlk%3D\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">type</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"application/x-ndjson\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "            \n",
+       "                <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">roles</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 1 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"index\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        </details></li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">bbox</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 4 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">0</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">-180.0</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">1</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">-90.0</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">2</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">180.0</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "            <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+       "        \n",
+       "            \n",
+       "                \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">3</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">90.0</span>\n",
+       "        </li>\n",
+       "    \n",
+       "            \n",
+       "        \n",
+       "    </ul>\n",
+       "        \n",
+       "    </details></li>\n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    <li><details>\n",
+       "        <summary class=\"pystac-summary\">\n",
+       "            <span class=\"pystac-key\">stac_extensions</span>\n",
+       "            <span style=\"padding-left: 0.5em; color: rgb(64, 128, 128); font-style: italic;\">[] 0 items</span>\n",
+       "        </summary>\n",
+       "        \n",
+       "    </details></li>\n",
+       "                \n",
+       "            \n",
+       "                \n",
+       "                    \n",
+       "        <li style=\"overflow-wrap: break-word; padding-left: 2.125em; text-indent: -0.5em;\">\n",
+       "            <span class=\"pystac-key pystac-key-value\">collection</span>\n",
+       "            <span style=\"color: rgb(186, 33, 33);\">\"ecmwf-forecast-wave-fc\"</span>\n",
+       "        </li>\n",
+       "    \n",
+       "                \n",
+       "            \n",
+       "        </ul>\n",
+       "    </div>\n",
+       "</div>"
+      ],
       "text/plain": [
-       "<Item id=ecmwf-2022-03-10T00-wave-fc-0h>"
+       "<Item id=ecmwf-2023-10-19T00-wave-fc-0h>"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -78,17 +1414,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "c34fc8a3-1ecd-4b4b-848e-f506bdf1bcbe",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'https://ai4edataeuwest.blob.core.windows.net/ecmwf/20220310/00z/0p4-beta/wave/20220310000000-0h-wave-fc.grib2'"
+       "'https://ai4edataeuwest.blob.core.windows.net/ecmwf/20231019/00z/0p4-beta/wave/20231019000000-0h-wave-fc.grib2?st=2023-10-18T17%3A43%3A36Z&se=2023-10-19T18%3A28%3A36Z&sp=rl&sv=2021-06-08&sr=c&skoid=c85c15d6-d1ae-42d4-af60-e2ca0f81359b&sktid=72f988bf-86f1-41af-91ab-2d7cd011db47&skt=2023-10-19T17%3A42%3A26Z&ske=2023-10-26T17%3A42%3A26Z&sks=b&skv=2021-06-08&sig=Sk8tgcshG8wDd8CuuvVZi6CdSEPi1jNIeAYlNBfZBlk%3D'"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -108,7 +1444,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "9dba8491-8e37-435e-abb8-0a73626c11d2",
    "metadata": {},
    "outputs": [
@@ -146,6 +1482,7 @@
        "}\n",
        "\n",
        "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
        "body.vscode-dark {\n",
        "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
        "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
@@ -375,6 +1712,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -396,14 +1738,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  display: none;\n",
        "  background-color: var(--xr-background-color) !important;\n",
        "  padding-bottom: 5px !important;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -413,13 +1757,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -457,7 +1804,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -469,16 +1817,16 @@
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
        "Dimensions:     (latitude: 451, longitude: 900)\n",
        "Coordinates:\n",
-       "    time        datetime64[ns] 2022-03-10\n",
-       "    step        timedelta64[ns] 00:00:00\n",
-       "    meanSea     float64 0.0\n",
+       "    time        datetime64[ns] ...\n",
+       "    step        timedelta64[ns] ...\n",
+       "    meanSea     float64 ...\n",
        "  * latitude    (latitude) float64 90.0 89.6 89.2 88.8 ... -89.2 -89.6 -90.0\n",
        "  * longitude   (longitude) float64 -180.0 -179.6 -179.2 ... 178.8 179.2 179.6\n",
-       "    valid_time  datetime64[ns] 2022-03-10\n",
+       "    valid_time  datetime64[ns] ...\n",
        "Data variables:\n",
        "    swh         (latitude, longitude) float32 ...\n",
-       "    mwp         (latitude, longitude) float32 ...\n",
        "    mwd         (latitude, longitude) float32 ...\n",
+       "    mwp         (latitude, longitude) float32 ...\n",
        "    pp1d        (latitude, longitude) float32 ...\n",
        "    mp2         (latitude, longitude) float32 ...\n",
        "Attributes:\n",
@@ -488,7 +1836,25 @@
        "    GRIB_subCentre:          0\n",
        "    Conventions:             CF-1.7\n",
        "    institution:             European Centre for Medium-Range Weather Forecasts\n",
-       "    history:                 2022-03-10T19:02 GRIB to CDM+CF via cfgrib-0.9.1...</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-cafa594a-5d61-4daf-aa91-5768dd27a603' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cafa594a-5d61-4daf-aa91-5768dd27a603' 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'>latitude</span>: 451</li><li><span class='xr-has-index'>longitude</span>: 900</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8b9a6b50-c2c2-4726-8d66-03715abc6431' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8b9a6b50-c2c2-4726-8d66-03715abc6431' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d527b6c7-6b66-4750-a059-ee1983896753' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d527b6c7-6b66-4750-a059-ee1983896753' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3ef641b-3326-4362-a118-4e3f3f339d69' class='xr-var-data-in' type='checkbox'><label for='data-f3ef641b-3326-4362-a118-4e3f3f339d69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-03-10T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c619b3f9-68ac-4436-b2b9-47321c51c348' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c619b3f9-68ac-4436-b2b9-47321c51c348' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-081d2a92-c791-4ebc-af4e-01a3313797eb' class='xr-var-data-in' type='checkbox'><label for='data-081d2a92-c791-4ebc-af4e-01a3313797eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>meanSea</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bb919fb1-2544-4b26-94ef-ec31cbec90b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb919fb1-2544-4b26-94ef-ec31cbec90b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ba43153-ffba-477b-9dfb-5751bc80922b' class='xr-var-data-in' type='checkbox'><label for='data-7ba43153-ffba-477b-9dfb-5751bc80922b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(meanSea)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(0.)</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'>90.0 89.6 89.2 ... -89.6 -90.0</div><input id='attrs-d235b143-48e3-442e-933d-691050001d49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d235b143-48e3-442e-933d-691050001d49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dbadcc1-26da-4df2-af9f-7e5a1660b0f8' class='xr-var-data-in' type='checkbox'><label for='data-3dbadcc1-26da-4df2-af9f-7e5a1660b0f8' title='Show/Hide data repr'><svg 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([ 90. ,  89.6,  89.2, ..., -89.2, -89.6, -90. ])</pre></div></li><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'>-180.0 -179.6 ... 179.2 179.6</div><input id='attrs-32b5e6a9-d953-480a-acad-06ed97f512f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32b5e6a9-d953-480a-acad-06ed97f512f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-482374cc-743d-4237-937b-7a7b2c69acfd' class='xr-var-data-in' type='checkbox'><label for='data-482374cc-743d-4237-937b-7a7b2c69acfd' title='Show/Hide data repr'><svg 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-180. , -179.6, -179.2, ...,  178.8,  179.2,  179.6])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b9d1a917-a35a-43b8-b426-76da0108d7ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9d1a917-a35a-43b8-b426-76da0108d7ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64176c94-3fae-43d2-91b4-1cc205671069' class='xr-var-data-in' type='checkbox'><label for='data-64176c94-3fae-43d2-91b4-1cc205671069' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-03-10T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4e516d94-1d34-47da-b010-2201568baa68' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4e516d94-1d34-47da-b010-2201568baa68' 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>swh</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ebefa79b-a99d-4f2c-8f09-74c499bc724d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ebefa79b-a99d-4f2c-8f09-74c499bc724d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78c96506-f191-4814-b7bd-721d7334afaa' class='xr-var-data-in' type='checkbox'><label for='data-78c96506-f191-4814-b7bd-721d7334afaa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140229</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>swh</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Significant height of combined wind waves and swell</dd><dt><span>GRIB_shortName :</span></dt><dd>swh</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Significant height of combined wind waves and swell</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mwp</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d3ffa73d-cbec-410c-b1f0-71fd665b3b88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3ffa73d-cbec-410c-b1f0-71fd665b3b88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71f26fc3-8242-49fc-8232-bb077ac6c3bc' class='xr-var-data-in' type='checkbox'><label for='data-71f26fc3-8242-49fc-8232-bb077ac6c3bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140232</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>mwp</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Mean wave period</dd><dt><span>GRIB_shortName :</span></dt><dd>mwp</dd><dt><span>GRIB_units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Mean wave period</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mwd</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a3b46e90-3ec2-4c09-8f56-ceea1adcae38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3b46e90-3ec2-4c09-8f56-ceea1adcae38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fea069bf-de9c-4762-99a7-4c2d98dca4c0' class='xr-var-data-in' type='checkbox'><label for='data-fea069bf-de9c-4762-99a7-4c2d98dca4c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140230</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>mwd</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Mean wave direction</dd><dt><span>GRIB_shortName :</span></dt><dd>mwd</dd><dt><span>GRIB_units :</span></dt><dd>Degree true</dd><dt><span>long_name :</span></dt><dd>Mean wave direction</dd><dt><span>units :</span></dt><dd>Degree true</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pp1d</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-00efe23c-e973-41e4-82d4-fabbac9e45f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00efe23c-e973-41e4-82d4-fabbac9e45f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94d97d03-2c0b-440b-a468-1c34fb8afed0' class='xr-var-data-in' type='checkbox'><label for='data-94d97d03-2c0b-440b-a468-1c34fb8afed0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140231</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>pp1d</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Peak wave period</dd><dt><span>GRIB_shortName :</span></dt><dd>pp1d</dd><dt><span>GRIB_units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Peak wave period</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mp2</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f2322878-f803-48c0-a0a0-064c287489ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2322878-f803-48c0-a0a0-064c287489ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9876960c-3ea5-4363-af9b-db56d90e0f9f' class='xr-var-data-in' type='checkbox'><label for='data-9876960c-3ea5-4363-af9b-db56d90e0f9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140221</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>mp2</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Mean zero-crossing wave period</dd><dt><span>GRIB_shortName :</span></dt><dd>mp2</dd><dt><span>GRIB_units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Mean zero-crossing wave period</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9d1ce9fd-7587-457c-9069-43c3bf424fa1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9d1ce9fd-7587-457c-9069-43c3bf424fa1' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2022-03-10T19:02 GRIB to CDM+CF via cfgrib-0.9.10.0/ecCodes-2.24.2 with {&quot;source&quot;: &quot;../../../tmp/tmpcicrlg64&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd></dl></div></li></ul></div></div>"
+       "    history:                 2023-10-19T17:43 GRIB to CDM+CF via cfgrib-0.9.1...</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-a6b11aa9-1e1f-4c0f-be28-dfb7bacc2f2f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a6b11aa9-1e1f-4c0f-be28-dfb7bacc2f2f' 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'>latitude</span>: 451</li><li><span class='xr-has-index'>longitude</span>: 900</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-266fd8db-06aa-41f8-8d2d-bd8bd84e304c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-266fd8db-06aa-41f8-8d2d-bd8bd84e304c' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1a9df5ed-f13b-49d0-8476-508d9ab75cef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a9df5ed-f13b-49d0-8476-508d9ab75cef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-258ba980-5482-487c-98ac-ca963f3070d6' class='xr-var-data-in' type='checkbox'><label for='data-258ba980-5482-487c-98ac-ca963f3070d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-73c934d5-9865-4693-9b72-28ebe0f18f00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73c934d5-9865-4693-9b72-28ebe0f18f00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a2c7948-6cdf-4520-ad3e-1daa604bc5ff' class='xr-var-data-in' type='checkbox'><label for='data-8a2c7948-6cdf-4520-ad3e-1daa604bc5ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=timedelta64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>meanSea</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ba310146-c749-4b97-b7d8-56923fa3566c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba310146-c749-4b97-b7d8-56923fa3566c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9205d9c5-7d3f-4d42-854d-3a4ff50d4559' class='xr-var-data-in' type='checkbox'><label for='data-9205d9c5-7d3f-4d42-854d-3a4ff50d4559' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(meanSea)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.6 89.2 ... -89.6 -90.0</div><input id='attrs-f131d82f-2eba-4f72-b0ba-2406f4def266' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f131d82f-2eba-4f72-b0ba-2406f4def266' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cd440b2-f32d-4d46-a96c-bb81e0f9b3fb' class='xr-var-data-in' type='checkbox'><label for='data-1cd440b2-f32d-4d46-a96c-bb81e0f9b3fb' title='Show/Hide data repr'><svg 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([ 90. ,  89.6,  89.2, ..., -89.2, -89.6, -90. ])</pre></div></li><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'>-180.0 -179.6 ... 179.2 179.6</div><input id='attrs-18b3357d-6d9a-4fa1-9c5f-703af50dd090' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18b3357d-6d9a-4fa1-9c5f-703af50dd090' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-180fdc58-2c24-425e-9007-57f2ad9d45d5' class='xr-var-data-in' type='checkbox'><label for='data-180fdc58-2c24-425e-9007-57f2ad9d45d5' title='Show/Hide data repr'><svg 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-180. , -179.6, -179.2, ...,  178.8,  179.2,  179.6])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-491081a0-f772-447d-9dc6-26fd8a73724e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-491081a0-f772-447d-9dc6-26fd8a73724e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-892bbb38-89d2-4553-b911-9bb40f94077c' class='xr-var-data-in' type='checkbox'><label for='data-892bbb38-89d2-4553-b911-9bb40f94077c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2b189d9c-aff9-4a47-944d-ee4e88b52af3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2b189d9c-aff9-4a47-944d-ee4e88b52af3' 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>swh</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6ee456b8-a2a8-4bed-955d-6c85d9aa11c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ee456b8-a2a8-4bed-955d-6c85d9aa11c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25856830-9464-4028-bbf4-0b8006c463ce' class='xr-var-data-in' type='checkbox'><label for='data-25856830-9464-4028-bbf4-0b8006c463ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140229</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>swh</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Significant height of combined wind waves and swell</dd><dt><span>GRIB_shortName :</span></dt><dd>swh</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Significant height of combined wind waves and swell</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mwd</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cf6a2426-66a1-402a-a0b8-e724414a9b4a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf6a2426-66a1-402a-a0b8-e724414a9b4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-368bad26-5602-45ff-8b94-3d6da3a3f288' class='xr-var-data-in' type='checkbox'><label for='data-368bad26-5602-45ff-8b94-3d6da3a3f288' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140230</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>mwd</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Mean wave direction</dd><dt><span>GRIB_shortName :</span></dt><dd>mwd</dd><dt><span>GRIB_units :</span></dt><dd>Degree true</dd><dt><span>long_name :</span></dt><dd>Mean wave direction</dd><dt><span>units :</span></dt><dd>Degree true</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mwp</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-85054ab8-1265-490d-b047-93846524b03b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85054ab8-1265-490d-b047-93846524b03b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-069d924d-3194-4652-962b-b8cd3e319ad9' class='xr-var-data-in' type='checkbox'><label for='data-069d924d-3194-4652-962b-b8cd3e319ad9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140232</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>mwp</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Mean wave period</dd><dt><span>GRIB_shortName :</span></dt><dd>mwp</dd><dt><span>GRIB_units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Mean wave period</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pp1d</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c2b70ae6-f276-4507-932c-782439cc246b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2b70ae6-f276-4507-932c-782439cc246b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dea5570-bfaf-47e1-a224-7a2c693f3e32' class='xr-var-data-in' type='checkbox'><label for='data-0dea5570-bfaf-47e1-a224-7a2c693f3e32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140231</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>pp1d</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Peak wave period</dd><dt><span>GRIB_shortName :</span></dt><dd>pp1d</dd><dt><span>GRIB_units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Peak wave period</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mp2</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b68f4e51-d78f-40a9-a688-01cb3bc3766a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b68f4e51-d78f-40a9-a688-01cb3bc3766a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58d8b830-6ec5-471f-b39e-b971132ac2f8' class='xr-var-data-in' type='checkbox'><label for='data-58d8b830-6ec5-471f-b39e-b971132ac2f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>140221</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>mp2</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Mean zero-crossing wave period</dd><dt><span>GRIB_shortName :</span></dt><dd>mp2</dd><dt><span>GRIB_units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Mean zero-crossing wave period</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-130ce4ad-b032-4093-87ab-a63e7eb5104e' class='xr-section-summary-in' type='checkbox'  ><label for='section-130ce4ad-b032-4093-87ab-a63e7eb5104e' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0e34e974-307f-4d46-af2a-56c97f6e6342' class='xr-index-data-in' type='checkbox'/><label for='index-0e34e974-307f-4d46-af2a-56c97f6e6342' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([              90.0,               89.6,  89.19999999999999,\n",
+       "               88.79999999999998,  88.39999999999998,  87.99999999999997,\n",
+       "               87.59999999999997,  87.19999999999996,  86.79999999999995,\n",
+       "               86.39999999999995,\n",
+       "              ...\n",
+       "              -86.40000000000036, -86.80000000000037, -87.20000000000037,\n",
+       "              -87.60000000000038, -88.00000000000038, -88.40000000000039,\n",
+       "               -88.8000000000004,  -89.2000000000004,  -89.6000000000004,\n",
+       "              -90.00000000000041],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=451))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-04cb0144-1293-45fe-9a31-810a175ae3ab' class='xr-index-data-in' type='checkbox'/><label for='index-04cb0144-1293-45fe-9a31-810a175ae3ab' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([             -180.0,              -179.6,              -179.2,\n",
+       "              -178.79999999999998, -178.39999999999998, -177.99999999999997,\n",
+       "              -177.59999999999997, -177.19999999999996, -176.79999999999995,\n",
+       "              -176.39999999999995,\n",
+       "              ...\n",
+       "                176.0000000000029,   176.4000000000029,   176.8000000000029,\n",
+       "               177.20000000000292,  177.60000000000292,  178.00000000000293,\n",
+       "               178.40000000000293,  178.80000000000294,  179.20000000000294,\n",
+       "               179.60000000000295],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=900))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f412b313-3902-4bd2-8466-80f44e76dd47' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f412b313-3902-4bd2-8466-80f44e76dd47' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2023-10-19T17:43 GRIB to CDM+CF via cfgrib-0.9.10.4/ecCodes-2.16.0 with {&quot;source&quot;: &quot;../../../../../tmp/tmpzmbwr6j0&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -502,8 +1868,8 @@
        "    valid_time  datetime64[ns] ...\n",
        "Data variables:\n",
        "    swh         (latitude, longitude) float32 ...\n",
-       "    mwp         (latitude, longitude) float32 ...\n",
        "    mwd         (latitude, longitude) float32 ...\n",
+       "    mwp         (latitude, longitude) float32 ...\n",
        "    pp1d        (latitude, longitude) float32 ...\n",
        "    mp2         (latitude, longitude) float32 ...\n",
        "Attributes:\n",
@@ -513,159 +1879,108 @@
        "    GRIB_subCentre:          0\n",
        "    Conventions:             CF-1.7\n",
        "    institution:             European Centre for Medium-Range Weather Forecasts\n",
-       "    history:                 2022-03-10T19:02 GRIB to CDM+CF via cfgrib-0.9.1..."
+       "    history:                 2023-10-19T17:43 GRIB to CDM+CF via cfgrib-0.9.1..."
       ]
      },
-     "execution_count": 4,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "import urllib.request\n",
-    "import xarray as xr\n",
-    "\n",
     "filename, _ = urllib.request.urlretrieve(url)\n",
-    "\n",
     "ds = xr.open_dataset(filename, engine=\"cfgrib\")\n",
     "ds"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "9e481590-5e18-45ff-a3ae-ed0db41abf40",
-   "metadata": {},
-   "source": [
-    "We can plot the various data variables, for example the significant height of combined wind waves and swell."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "468e3062-f159-44cb-89ce-b2ded4e352d3",
+   "id": "b0cf9b31",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<img src=\"https://ai4edatasetspublicassets.blob.core.windows.net/assets/notebook-output/datasets-ecmwf-forecast-ecmwf-forecast-example.ipynb/5.png\"/>"
-      ],
-      "text/plain": [
-       "<Figure size 1152x648 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
    "source": [
-    "import matplotlib.pyplot as plt\n",
-    "import cartopy.crs as ccrs\n",
+    "As opposed to having to download the data locally to take a look at it, we can open it more efficiently using kerchunk indices. [Kerchunk](https://pypi.org/project/kerchunk/) is a python library that provides a unified way to represent a variety of chunked, compressed data formats (e.g. NetCDF, HDF5, GRIB) through metadata, allowing efficient access to the data from traditional file systems or cloud object storage.\n",
     "\n",
-    "projection = ccrs.Robinson()\n",
-    "fig, ax = plt.subplots(figsize=(16, 9), subplot_kw=dict(projection=projection))\n",
-    "\n",
-    "ds.swh.plot(ax=ax, transform=ccrs.PlateCarree());"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cc4f0715-89ec-415d-89f7-520ad7b79a24",
-   "metadata": {},
-   "source": [
-    "Or the joint distribution between the wave period and height."
+    "We used the Kerchunk library to generate metadata indices for this STAC collection and stored them in the properties section for each item. Let's take a look."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "70780ca2-840c-42b8-850f-d51e6442dcfe",
+   "id": "ae9d5e0d",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "text/html": [
-       "<img src=\"https://ai4edatasetspublicassets.blob.core.windows.net/assets/notebook-output/datasets-ecmwf-forecast-ecmwf-forecast-example.ipynb/6.png\"/>"
-      ],
       "text/plain": [
-       "<Figure size 864x864 with 3 Axes>"
+       "{'refs': {'step/0': 'base64:AAAAAAAAAAA=',\n",
+       "  'time/0': 'base64:gHEwZQAAAAA=',\n",
+       "  '.zattrs': '{\"GRIB_centre\":\"ecmf\",\"GRIB_centreDescription\":\"European Centre for Medium-Range Weather Forecasts\",\"GRIB_edition\":2,\"GRIB_subCentre\":0,\"coordinates\":\"meanSea latitude longitude step time valid_time\",\"institution\":\"European Centre for Medium-Range Weather Forecasts\"}',\n",
+       "  '.zgroup': '{\"zarr_format\":2}',\n",
+       "  'meanSea/0': 'base64:AAAAAAAAAAA=',\n",
+       "  'mp2/0.0.0': ['https://ai4edataeuwest.blob.core.windows.net/ecmwf/20231019/00z/0p4-beta/wave/20231019000000-0h-wave-fc.grib2',\n",
+       "   1333081,\n",
+       "   354874],\n",
+       "  'mwd/0.0.0': ['https://ai4edataeuwest.blob.core.windows.net/ecmwf/20231019/00z/0p4-beta/wave/20231019000000-0h-wave-fc.grib2',\n",
+       "   322850,\n",
+       "   342261],\n",
+       "  'mwp/0.0.0': ['https://ai4edataeuwest.blob.core.windows.net/ecmwf/20231019/00z/0p4-beta/wave/20231019000000-0h-wave-fc.grib2',\n",
+       "   665111,\n",
+       "   327350],\n",
+       "  'swh/0.0.0': ['https://ai4edataeuwest.blob.core.windows.net/ecmwf/20231019/00z/0p4-beta/wave/20231019000000-0h-wave-fc.grib2',\n",
+       "   0,\n",
+       "   322850],\n",
+       "  'latitude/0': 'base64:AAAAAACAVkCamZmZmZlWwJqZmZmZmdm/',\n",
+       "  'pp1d/0.0.0': ['https://ai4edataeuwest.blob.core.windows.net/ecmwf/20231019/00z/0p4-beta/wave/20231019000000-0h-wave-fc.grib2',\n",
+       "   992461,\n",
+       "   340620],\n",
+       "  'longitude/0': 'base64:AAAAAACAZsAAAAAAAIBmQJqZmZmZmdk/',\n",
+       "  'mp2/.zarray': '{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"mp2\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}',\n",
+       "  'mp2/.zattrs': '{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"mp2\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Mean zero-crossing wave period\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140221,\"GRIB_shortName\":\"mp2\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"s\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Mean zero-crossing wave period\",\"standard_name\":\"unknown\",\"units\":\"s\"}',\n",
+       "  'mwd/.zarray': '{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"mwd\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}',\n",
+       "  'mwd/.zattrs': '{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"mwd\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Mean wave direction\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140230,\"GRIB_shortName\":\"mwd\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"Degree true\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Mean wave direction\",\"standard_name\":\"unknown\",\"units\":\"Degree true\"}',\n",
+       "  'mwp/.zarray': '{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"mwp\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}',\n",
+       "  'mwp/.zattrs': '{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"mwp\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Mean wave period\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140232,\"GRIB_shortName\":\"mwp\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"s\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Mean wave period\",\"standard_name\":\"unknown\",\"units\":\"s\"}',\n",
+       "  'swh/.zarray': '{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"swh\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}',\n",
+       "  'swh/.zattrs': '{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"swh\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Significant height of combined wind waves and swell\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140229,\"GRIB_shortName\":\"swh\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"m\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Significant height of combined wind waves and swell\",\"standard_name\":\"unknown\",\"units\":\"m\"}',\n",
+       "  'pp1d/.zarray': '{\"chunks\":[1,451,900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"dtype\":\"float64\",\"id\":\"grib\",\"var\":\"pp1d\"}],\"order\":\"C\",\"shape\":[1,451,900],\"zarr_format\":2}',\n",
+       "  'pp1d/.zattrs': '{\"GRIB_NV\":0,\"GRIB_Nx\":900,\"GRIB_Ny\":451,\"GRIB_cfName\":\"unknown\",\"GRIB_cfVarName\":\"pp1d\",\"GRIB_dataType\":\"fc\",\"GRIB_gridDefinitionDescription\":\"Latitude\\\\/longitude\",\"GRIB_gridType\":\"regular_ll\",\"GRIB_iDirectionIncrementInDegrees\":0.4,\"GRIB_iScansNegatively\":0,\"GRIB_jDirectionIncrementInDegrees\":0.4,\"GRIB_jPointsAreConsecutive\":0,\"GRIB_jScansPositively\":0,\"GRIB_latitudeOfFirstGridPointInDegrees\":90.0,\"GRIB_latitudeOfLastGridPointInDegrees\":-90.0,\"GRIB_longitudeOfFirstGridPointInDegrees\":180.0,\"GRIB_longitudeOfLastGridPointInDegrees\":179.6,\"GRIB_missingValue\":3.4028234663852886e+38,\"GRIB_name\":\"Peak wave period\",\"GRIB_numberOfPoints\":405900,\"GRIB_paramId\":140231,\"GRIB_shortName\":\"pp1d\",\"GRIB_stepType\":\"instant\",\"GRIB_stepUnits\":1,\"GRIB_typeOfLevel\":\"meanSea\",\"GRIB_units\":\"s\",\"_ARRAY_DIMENSIONS\":[\"time\",\"latitude\",\"longitude\"],\"long_name\":\"Peak wave period\",\"standard_name\":\"unknown\",\"units\":\"s\"}',\n",
+       "  'step/.zarray': '{\"chunks\":[1],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":null,\"order\":\"C\",\"shape\":[1],\"zarr_format\":2}',\n",
+       "  'step/.zattrs': '{\"_ARRAY_DIMENSIONS\":[\"time\"],\"long_name\":\"time since forecast_reference_time\",\"standard_name\":\"forecast_period\",\"units\":\"hours\"}',\n",
+       "  'time/.zarray': 'base64:ewogICAgImNodW5rcyI6IFsKICAgICAgICAxCiAgICBdLAogICAgImNvbXByZXNzb3IiOiBudWxsLAogICAgImR0eXBlIjogIjxpOCIsCiAgICAiZmlsbF92YWx1ZSI6IG51bGwsCiAgICAiZmlsdGVycyI6IG51bGwsCiAgICAib3JkZXIiOiAiQyIsCiAgICAic2hhcGUiOiBbCiAgICAgICAgMQogICAgXSwKICAgICJ6YXJyX2Zvcm1hdCI6IDIKfQ==',\n",
+       "  'time/.zattrs': 'base64:ewogICAgIl9BUlJBWV9ESU1FTlNJT05TIjogWwogICAgICAgICJ0aW1lIgogICAgXSwKICAgICJjYWxlbmRhciI6ICJwcm9sZXB0aWNfZ3JlZ29yaWFuIiwKICAgICJsb25nX25hbWUiOiAiaW5pdGlhbCB0aW1lIG9mIGZvcmVjYXN0IiwKICAgICJzdGFuZGFyZF9uYW1lIjogImZvcmVjYXN0X3JlZmVyZW5jZV90aW1lIiwKICAgICJ1bml0cyI6ICJzZWNvbmRzIHNpbmNlIDE5NzAtMDEtMDFUMDA6MDA6MDAiCn0=',\n",
+       "  'valid_time/0': 'base64:gHEwZQAAAAA=',\n",
+       "  'meanSea/.zarray': '{\"chunks\":[1],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":null,\"order\":\"C\",\"shape\":[1],\"zarr_format\":2}',\n",
+       "  'meanSea/.zattrs': '{\"_ARRAY_DIMENSIONS\":[\"time\"]}',\n",
+       "  'latitude/.zarray': '{\"chunks\":[451],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"id\": \"range\"}],\"order\":\"C\",\"shape\":[451],\"zarr_format\":2}',\n",
+       "  'latitude/.zattrs': '{\"_ARRAY_DIMENSIONS\":[\"latitude\"],\"long_name\":\"latitude\",\"standard_name\":\"latitude\",\"units\":\"degrees_north\"}',\n",
+       "  'longitude/.zarray': '{\"chunks\":[900],\"compressor\":null,\"dtype\":\"<f8\",\"fill_value\":null,\"filters\":[{\"id\": \"range\"}],\"order\":\"C\",\"shape\":[900],\"zarr_format\":2}',\n",
+       "  'longitude/.zattrs': '{\"_ARRAY_DIMENSIONS\":[\"longitude\"],\"long_name\":\"longitude\",\"standard_name\":\"longitude\",\"units\":\"degrees_east\"}',\n",
+       "  'valid_time/.zarray': '{\"chunks\":[1],\"compressor\":null,\"dtype\":\"<i8\",\"fill_value\":null,\"filters\":null,\"order\":\"C\",\"shape\":[1],\"zarr_format\":2}',\n",
+       "  'valid_time/.zattrs': '{\"_ARRAY_DIMENSIONS\":[\"time\"],\"calendar\":\"proleptic_gregorian\",\"long_name\":\"time\",\"standard_name\":\"time\",\"units\":\"seconds since 1970-01-01T00:00:00\"}'},\n",
+       " 'version': 1}"
       ]
      },
+     "execution_count": 6,
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "import seaborn as sns\n",
-    "\n",
-    "grid = sns.jointplot(\n",
-    "    x=ds.mwp.data.ravel(), y=ds.swh.data.ravel(), alpha=0.25, marker=\".\", height=12\n",
-    ")\n",
-    "grid.ax_joint.set(xlabel=\"Mean wave period\", ylabel=\"Significant wave height\");"
+    "item.properties['kerchunk_indices']"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "ba157759-147c-4247-ad4b-ad321da571c4",
+   "id": "7c788c60-caa3-49b9-bfc8-107f7aeaabb2",
    "metadata": {},
    "source": [
-    "### GRIB2 files with multiple datasets \n",
-    "\n",
-    "Some GRIB2 files contain many messages that for separate xarray Datasets. For example, we can find the STAC item containing the atmospheric fields ensemble forecast (`stream=enfo`) from the ensemble forecast model (`type=ef`)."
+    "Kerchunk indices are similar to a Zarr store. We can use the packages fsspec and xarray to view the virtual dataset. You'll see it matches the dataset loaded above from the downloaded .grib2 file."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "0095f86f-3c76-4ab4-ac4f-4dbdb03d8159",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "189 matched\n"
-     ]
-    }
-   ],
-   "source": [
-    "search = catalog.search(\n",
-    "    collections=[\"ecmwf-forecast\"],\n",
-    "    query={\n",
-    "        \"ecmwf:stream\": {\"eq\": \"enfo\"},\n",
-    "        \"ecmwf:type\": {\"eq\": \"ef\"},\n",
-    "        \"ecmwf:step\": {\"eq\": \"0h\"},\n",
-    "    },\n",
-    ")\n",
-    "items = search.get_all_items()\n",
-    "print(len(items), \"matched\")\n",
-    "# select the most recent forecast\n",
-    "item = max(items, key=lambda item: item.datetime)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "0e2d2cba-6052-405e-a5cd-84b0035488d7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "url = item.assets[\"data\"].href\n",
-    "filename, _ = urllib.request.urlretrieve(url)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "baa890b6-0ca6-4ca9-8b27-6954099a249d",
-   "metadata": {},
-   "source": [
-    "If we provided just the `filename` to `xarray.open_dataset`, we'd get an error from `cfgrib` saying it can't form a valid DataArray from the file. That's because the GRIB2 file contains multiple data variables that don't form a neat hypercube. Provide `filter_by_keys` to indicate which subset of the data to read in."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "cb28e64a-8376-41c7-ac29-a6bd3181d159",
+   "id": "5cb3b3d1-2b75-4486-bf07-d8d9822a0cfa",
    "metadata": {},
    "outputs": [
     {
@@ -702,6 +2017,7 @@
        "}\n",
        "\n",
        "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
        "body.vscode-dark {\n",
        "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
        "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
@@ -931,6 +2247,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -952,14 +2273,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  display: none;\n",
        "  background-color: var(--xr-background-color) !important;\n",
        "  padding-bottom: 5px !important;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -969,13 +2292,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -1013,7 +2339,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -1023,101 +2350,969 @@
        "  fill: currentColor;\n",
        "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:     (number: 50, latitude: 451, longitude: 900)\n",
+       "Dimensions:     (latitude: 451, longitude: 900, time: 1)\n",
        "Coordinates:\n",
-       "  * number      (number) int64 1 2 3 4 5 6 7 8 9 ... 42 43 44 45 46 47 48 49 50\n",
-       "    time        datetime64[ns] 2022-03-10T06:00:00\n",
-       "    step        timedelta64[ns] 00:00:00\n",
-       "    surface     float64 0.0\n",
        "  * latitude    (latitude) float64 90.0 89.6 89.2 88.8 ... -89.2 -89.6 -90.0\n",
        "  * longitude   (longitude) float64 -180.0 -179.6 -179.2 ... 178.8 179.2 179.6\n",
-       "    valid_time  datetime64[ns] 2022-03-10T06:00:00\n",
+       "    meanSea     (time) float64 ...\n",
+       "    step        (time) timedelta64[ns] ...\n",
+       "  * time        (time) datetime64[ns] 2023-10-19\n",
+       "    valid_time  (time) datetime64[ns] ...\n",
        "Data variables:\n",
-       "    tp          (number, latitude, longitude) float32 ...\n",
-       "    sp          (number, latitude, longitude) float32 ...\n",
-       "    skt         (number, latitude, longitude) float32 ...\n",
-       "    ro          (number, latitude, longitude) float32 ...\n",
+       "    mp2         (time, latitude, longitude) float64 ...\n",
+       "    mwd         (time, latitude, longitude) float64 ...\n",
+       "    mwp         (time, latitude, longitude) float64 ...\n",
+       "    pp1d        (time, latitude, longitude) float64 ...\n",
+       "    swh         (time, latitude, longitude) float64 ...\n",
        "Attributes:\n",
-       "    GRIB_edition:            2\n",
        "    GRIB_centre:             ecmf\n",
        "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    GRIB_edition:            2\n",
        "    GRIB_subCentre:          0\n",
-       "    Conventions:             CF-1.7\n",
-       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
-       "    history:                 2022-03-10T19:03 GRIB to CDM+CF via cfgrib-0.9.1...</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-cf9cd2d5-2a4a-4d37-acda-a8050dc3a25a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cf9cd2d5-2a4a-4d37-acda-a8050dc3a25a' 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'>number</span>: 50</li><li><span class='xr-has-index'>latitude</span>: 451</li><li><span class='xr-has-index'>longitude</span>: 900</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-eaf66581-d7b7-4422-bc40-fff459ac344e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eaf66581-d7b7-4422-bc40-fff459ac344e' class='xr-section-summary' >Coordinates: <span>(7)</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'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 45 46 47 48 49 50</div><input id='attrs-71007fa2-78ec-4c5c-9a87-d4230a2e695f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71007fa2-78ec-4c5c-9a87-d4230a2e695f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e3e0e3b-a27f-43d4-b748-717a5964b1f5' class='xr-var-data-in' type='checkbox'><label for='data-3e3e0e3b-a27f-43d4-b748-717a5964b1f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18,\n",
-       "       19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,\n",
-       "       37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b7607a07-1d7f-44a9-8aff-7b1c8a0bff89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7607a07-1d7f-44a9-8aff-7b1c8a0bff89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65148a9b-a1cb-4fbd-9e84-1fefc5f674b0' class='xr-var-data-in' type='checkbox'><label for='data-65148a9b-a1cb-4fbd-9e84-1fefc5f674b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-03-10T06:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-72562eb5-4d5f-4717-866f-4048fba8b0a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72562eb5-4d5f-4717-866f-4048fba8b0a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65be7dff-2edc-4ab2-bb04-9e5e67f1d82d' class='xr-var-data-in' type='checkbox'><label for='data-65be7dff-2edc-4ab2-bb04-9e5e67f1d82d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-48f32f96-c725-47ec-97bb-7a6805810b95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48f32f96-c725-47ec-97bb-7a6805810b95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb2c28e1-1507-4101-9bd5-b0022a9792f0' class='xr-var-data-in' type='checkbox'><label for='data-fb2c28e1-1507-4101-9bd5-b0022a9792f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(surface)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(0.)</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'>90.0 89.6 89.2 ... -89.6 -90.0</div><input id='attrs-736e6083-c683-4e52-ada3-0ed1f74608ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-736e6083-c683-4e52-ada3-0ed1f74608ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21836641-2269-4215-8735-af82c4f3c280' class='xr-var-data-in' type='checkbox'><label for='data-21836641-2269-4215-8735-af82c4f3c280' title='Show/Hide data repr'><svg 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([ 90. ,  89.6,  89.2, ..., -89.2, -89.6, -90. ])</pre></div></li><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'>-180.0 -179.6 ... 179.2 179.6</div><input id='attrs-a50b3d49-e090-4a9b-8c2d-51c4d646203d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a50b3d49-e090-4a9b-8c2d-51c4d646203d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8134924-198f-44a1-bb63-a754c4f0c5a8' class='xr-var-data-in' type='checkbox'><label for='data-f8134924-198f-44a1-bb63-a754c4f0c5a8' title='Show/Hide data repr'><svg 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-180. , -179.6, -179.2, ...,  178.8,  179.2,  179.6])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f80d59ad-22f3-4fb0-bfed-3fa03862b822' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f80d59ad-22f3-4fb0-bfed-3fa03862b822' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ea79d34-2c06-4267-8d73-430174f8f29b' class='xr-var-data-in' type='checkbox'><label for='data-2ea79d34-2c06-4267-8d73-430174f8f29b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2022-03-10T06:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1220dde8-f856-434d-91fd-d81cb9293ccd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1220dde8-f856-434d-91fd-d81cb9293ccd' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(number, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7f0b541a-e2e7-4f36-ad39-07032e38afb3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f0b541a-e2e7-4f36-ad39-07032e38afb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73fd632e-7b0c-4146-a3a4-a8fa40770c08' class='xr-var-data-in' type='checkbox'><label for='data-73fd632e-7b0c-4146-a3a4-a8fa40770c08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>228</dd><dt><span>GRIB_dataType :</span></dt><dd>pf</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>tp</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_totalNumber :</span></dt><dd>51</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[20295000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sp</span></div><div class='xr-var-dims'>(number, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-97bf30d4-24b5-4a32-9440-e38ec3a3163f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97bf30d4-24b5-4a32-9440-e38ec3a3163f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40612ccc-1eb6-4fda-a124-339b2b657c06' class='xr-var-data-in' type='checkbox'><label for='data-40612ccc-1eb6-4fda-a124-339b2b657c06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>134</dd><dt><span>GRIB_dataType :</span></dt><dd>pf</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>surface_air_pressure</dd><dt><span>GRIB_cfVarName :</span></dt><dd>sp</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Surface pressure</dd><dt><span>GRIB_shortName :</span></dt><dd>sp</dd><dt><span>GRIB_totalNumber :</span></dt><dd>51</dd><dt><span>GRIB_units :</span></dt><dd>Pa</dd><dt><span>long_name :</span></dt><dd>Surface pressure</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>standard_name :</span></dt><dd>surface_air_pressure</dd></dl></div><div class='xr-var-data'><pre>[20295000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>skt</span></div><div class='xr-var-dims'>(number, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f1c9ad8f-fa3c-465f-a476-e9fa6c3d92b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1c9ad8f-fa3c-465f-a476-e9fa6c3d92b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a97a6f0-92c9-40c4-a156-51ab6f595546' class='xr-var-data-in' type='checkbox'><label for='data-8a97a6f0-92c9-40c4-a156-51ab6f595546' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>235</dd><dt><span>GRIB_dataType :</span></dt><dd>pf</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>skt</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Skin temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>skt</dd><dt><span>GRIB_totalNumber :</span></dt><dd>51</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Skin temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[20295000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ro</span></div><div class='xr-var-dims'>(number, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-291fdd20-21c2-483f-b048-ae5ddd3ab4ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-291fdd20-21c2-483f-b048-ae5ddd3ab4ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9f4472a-cc32-4542-be4a-5b195c2cab07' class='xr-var-data-in' type='checkbox'><label for='data-e9f4472a-cc32-4542-be4a-5b195c2cab07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>205</dd><dt><span>GRIB_dataType :</span></dt><dd>pf</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>ro</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude </dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>Runoff</dd><dt><span>GRIB_shortName :</span></dt><dd>ro</dd><dt><span>GRIB_totalNumber :</span></dt><dd>51</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Runoff</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>[20295000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7526c626-efe3-4e1a-931f-42afb7ad99d2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7526c626-efe3-4e1a-931f-42afb7ad99d2' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2022-03-10T19:03 GRIB to CDM+CF via cfgrib-0.9.10.0/ecCodes-2.24.2 with {&quot;source&quot;: &quot;../../../tmp/tmpjrw62suc&quot;, &quot;filter_by_keys&quot;: {&quot;dataType&quot;: &quot;pf&quot;, &quot;typeOfLevel&quot;: &quot;surface&quot;}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd></dl></div></li></ul></div></div>"
+       "    institution:             European Centre for Medium-Range Weather Forecasts</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-6a1546c4-4278-4e0a-86c3-156e4f7bc878' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6a1546c4-4278-4e0a-86c3-156e4f7bc878' 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'>latitude</span>: 451</li><li><span class='xr-has-index'>longitude</span>: 900</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ca8abfd0-382e-438a-81b1-2538f12787b6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ca8abfd0-382e-438a-81b1-2538f12787b6' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>90.0 89.6 89.2 ... -89.6 -90.0</div><input id='attrs-6bd1cfc7-5724-4004-ba5a-04423ae7f4b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bd1cfc7-5724-4004-ba5a-04423ae7f4b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ac7f782-5ea9-441c-87c4-6d9e5ca93200' class='xr-var-data-in' type='checkbox'><label for='data-0ac7f782-5ea9-441c-87c4-6d9e5ca93200' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 90. ,  89.6,  89.2, ..., -89.2, -89.6, -90. ])</pre></div></li><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'>-180.0 -179.6 ... 179.2 179.6</div><input id='attrs-c79b7f41-eddd-4911-8c8b-73510451e6f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c79b7f41-eddd-4911-8c8b-73510451e6f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bb049dc-8aae-4930-9ea7-e3193d168533' class='xr-var-data-in' type='checkbox'><label for='data-7bb049dc-8aae-4930-9ea7-e3193d168533' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180. , -179.6, -179.2, ...,  178.8,  179.2,  179.6])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>meanSea</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-60a4f81c-02d5-4a46-a0c7-553249479418' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60a4f81c-02d5-4a46-a0c7-553249479418' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-018a8874-1b74-4d32-98c6-1eaf180ae889' class='xr-var-data-in' type='checkbox'><label for='data-018a8874-1b74-4d32-98c6-1eaf180ae889' title='Show/Hide data 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>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-29de5871-754c-42ea-9ebe-92daf78bbc1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29de5871-754c-42ea-9ebe-92daf78bbc1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5709944a-b77a-421a-8ada-0e2ead5639dd' class='xr-var-data-in' type='checkbox'><label for='data-5709944a-b77a-421a-8ada-0e2ead5639dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=timedelta64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-10-19</div><input id='attrs-ff1bc42c-913e-44e5-bff2-93cce1a73323' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff1bc42c-913e-44e5-bff2-93cce1a73323' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-767f1920-54b1-4593-ae6c-7fbed3e8d4d6' class='xr-var-data-in' type='checkbox'><label for='data-767f1920-54b1-4593-ae6c-7fbed3e8d4d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2023-10-19T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cbd44690-2309-447d-b03e-50c15e3def19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbd44690-2309-447d-b03e-50c15e3def19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7549fc0a-7268-4033-ac54-c77173f8dc1e' class='xr-var-data-in' type='checkbox'><label for='data-7549fc0a-7268-4033-ac54-c77173f8dc1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-519732c9-f176-4921-aa53-7d55ee581490' class='xr-section-summary-in' type='checkbox'  checked><label for='section-519732c9-f176-4921-aa53-7d55ee581490' 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>mp2</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8ddb752e-a6e5-40f9-9c6b-f89c05bfac1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ddb752e-a6e5-40f9-9c6b-f89c05bfac1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83703447-3cc3-4386-93ff-ffcaa7c72e58' class='xr-var-data-in' type='checkbox'><label for='data-83703447-3cc3-4386-93ff-ffcaa7c72e58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>mp2</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Mean zero-crossing wave period</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_paramId :</span></dt><dd>140221</dd><dt><span>GRIB_shortName :</span></dt><dd>mp2</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Mean zero-crossing wave period</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mwd</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1ea19d60-c698-4ba7-86e9-d0d9d60471e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ea19d60-c698-4ba7-86e9-d0d9d60471e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff32965f-4640-4d20-9f67-f5e62f54f8f7' class='xr-var-data-in' type='checkbox'><label for='data-ff32965f-4640-4d20-9f67-f5e62f54f8f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>mwd</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Mean wave direction</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_paramId :</span></dt><dd>140230</dd><dt><span>GRIB_shortName :</span></dt><dd>mwd</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_units :</span></dt><dd>Degree true</dd><dt><span>long_name :</span></dt><dd>Mean wave direction</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>Degree true</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mwp</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2d928d84-7a45-493f-a744-43ff2a3be464' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d928d84-7a45-493f-a744-43ff2a3be464' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cb6a7d2-ee1f-46c3-853c-a5931046b42c' class='xr-var-data-in' type='checkbox'><label for='data-3cb6a7d2-ee1f-46c3-853c-a5931046b42c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>mwp</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Mean wave period</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_paramId :</span></dt><dd>140232</dd><dt><span>GRIB_shortName :</span></dt><dd>mwp</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Mean wave period</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pp1d</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-47891d9a-0cc6-4c79-9e38-8d20a4e1bae4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47891d9a-0cc6-4c79-9e38-8d20a4e1bae4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ad9eb39-205f-4c9f-8cf1-d156794be49e' class='xr-var-data-in' type='checkbox'><label for='data-3ad9eb39-205f-4c9f-8cf1-d156794be49e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>pp1d</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Peak wave period</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_paramId :</span></dt><dd>140231</dd><dt><span>GRIB_shortName :</span></dt><dd>pp1d</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Peak wave period</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swh</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5bbc8e03-61ac-4649-92e7-2c4032de157e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5bbc8e03-61ac-4649-92e7-2c4032de157e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a720130-0a83-47fc-8fdd-1fbaf76162f5' class='xr-var-data-in' type='checkbox'><label for='data-3a720130-0a83-47fc-8fdd-1fbaf76162f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>900</dd><dt><span>GRIB_Ny :</span></dt><dd>451</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>swh</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.4</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.6</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Significant height of combined wind waves and swell</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>405900</dd><dt><span>GRIB_paramId :</span></dt><dd>140229</dd><dt><span>GRIB_shortName :</span></dt><dd>swh</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Significant height of combined wind waves and swell</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[405900 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d2560ea8-c1a9-4b73-bb2f-08b1c37f0cee' class='xr-section-summary-in' type='checkbox'  ><label for='section-d2560ea8-c1a9-4b73-bb2f-08b1c37f0cee' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6ec5c42c-98e8-4328-8174-0737d460fc36' class='xr-index-data-in' type='checkbox'/><label for='index-6ec5c42c-98e8-4328-8174-0737d460fc36' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([              90.0,               89.6,  89.19999999999999,\n",
+       "               88.79999999999998,  88.39999999999998,  87.99999999999997,\n",
+       "               87.59999999999997,  87.19999999999996,  86.79999999999995,\n",
+       "               86.39999999999995,\n",
+       "              ...\n",
+       "               -86.4000000000025, -86.80000000000251, -87.20000000000252,\n",
+       "              -87.60000000000252, -88.00000000000253, -88.40000000000254,\n",
+       "              -88.80000000000254, -89.20000000000255, -89.60000000000255,\n",
+       "              -90.00000000000256],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=451))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7728d224-b9fd-43a0-993a-a5e86899a3dd' class='xr-index-data-in' type='checkbox'/><label for='index-7728d224-b9fd-43a0-993a-a5e86899a3dd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([             -180.0,              -179.6,              -179.2,\n",
+       "              -178.79999999999998, -178.39999999999998, -177.99999999999997,\n",
+       "              -177.59999999999997, -177.19999999999996, -176.79999999999995,\n",
+       "              -176.39999999999995,\n",
+       "              ...\n",
+       "               176.00000000000506,   176.4000000000051,  176.80000000000507,\n",
+       "               177.20000000000505,  177.60000000000508,  178.00000000000512,\n",
+       "                178.4000000000051,  178.80000000000507,   179.2000000000051,\n",
+       "               179.60000000000514],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=900))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f33de9e8-70a2-4282-b8bb-b910390265a1' class='xr-index-data-in' type='checkbox'/><label for='index-f33de9e8-70a2-4282-b8bb-b910390265a1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2023-10-19&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-92ed0016-888d-4e0c-8461-af9599ddcdfd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-92ed0016-888d-4e0c-8461-af9599ddcdfd' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
-       "Dimensions:     (number: 50, latitude: 451, longitude: 900)\n",
+       "Dimensions:     (latitude: 451, longitude: 900, time: 1)\n",
        "Coordinates:\n",
-       "  * number      (number) int64 1 2 3 4 5 6 7 8 9 ... 42 43 44 45 46 47 48 49 50\n",
-       "    time        datetime64[ns] ...\n",
-       "    step        timedelta64[ns] ...\n",
-       "    surface     float64 ...\n",
        "  * latitude    (latitude) float64 90.0 89.6 89.2 88.8 ... -89.2 -89.6 -90.0\n",
        "  * longitude   (longitude) float64 -180.0 -179.6 -179.2 ... 178.8 179.2 179.6\n",
-       "    valid_time  datetime64[ns] ...\n",
+       "    meanSea     (time) float64 ...\n",
+       "    step        (time) timedelta64[ns] ...\n",
+       "  * time        (time) datetime64[ns] 2023-10-19\n",
+       "    valid_time  (time) datetime64[ns] ...\n",
        "Data variables:\n",
-       "    tp          (number, latitude, longitude) float32 ...\n",
-       "    sp          (number, latitude, longitude) float32 ...\n",
-       "    skt         (number, latitude, longitude) float32 ...\n",
-       "    ro          (number, latitude, longitude) float32 ...\n",
+       "    mp2         (time, latitude, longitude) float64 ...\n",
+       "    mwd         (time, latitude, longitude) float64 ...\n",
+       "    mwp         (time, latitude, longitude) float64 ...\n",
+       "    pp1d        (time, latitude, longitude) float64 ...\n",
+       "    swh         (time, latitude, longitude) float64 ...\n",
        "Attributes:\n",
-       "    GRIB_edition:            2\n",
        "    GRIB_centre:             ecmf\n",
        "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    GRIB_edition:            2\n",
        "    GRIB_subCentre:          0\n",
-       "    Conventions:             CF-1.7\n",
-       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
-       "    history:                 2022-03-10T19:03 GRIB to CDM+CF via cfgrib-0.9.1..."
+       "    institution:             European Centre for Medium-Range Weather Forecasts"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "ds = xr.open_dataset(\n",
-    "    filename,\n",
-    "    engine=\"cfgrib\",\n",
-    "    filter_by_keys={\"dataType\": \"pf\", \"typeOfLevel\": \"surface\"},\n",
-    ")\n",
-    "ds"
+    "m = fsspec.get_mapper('reference://', fo=item.properties['kerchunk_indices'])\n",
+    "ds_kerchunk = xr.open_dataset(m, engine='zarr', consolidated=False)\n",
+    "ds_kerchunk"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "9587e2fd-a23f-4790-b250-4442497a60b5",
+   "id": "9e481590-5e18-45ff-a3ae-ed0db41abf40",
    "metadata": {},
    "source": [
-    "Now we can plot the skin temperature, `skt`."
+    "We can plot the various data variables, for example the significant height of combined wind waves and swell."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "a6aeb918-8f22-4400-bb31-e5efa3719e42",
+   "execution_count": 8,
+   "id": "468e3062-f159-44cb-89ce-b2ded4e352d3",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1600x900 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "import matplotlib.pyplot as plt\n",
-    "import cartopy.crs as ccrs\n",
-    "\n",
-    "projection = projection = ccrs.Robinson()\n",
+    "projection = ccrs.Robinson()\n",
     "fig, ax = plt.subplots(figsize=(16, 9), subplot_kw=dict(projection=projection))\n",
     "\n",
-    "ds.skt[0].plot(ax=ax, transform=ccrs.PlateCarree());"
+    "ds.swh.plot(ax=ax)\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "a9e7a71e-3bec-4c17-838d-8faa6bce8b37",
+   "id": "a6dad68b",
+   "metadata": {},
+   "source": [
+    "Now let's do a simple comparison of loading and analysis time between having to retrieve/download the data and accessing it via kerchunk.\n",
+    "\n",
+    "Performing the analysis using the original .grib2 file takes 3 seconds (~2 seconds to load, <1 second to calculate the mean of swh). Performing the analysis using kerchunk indices takes 1 second (<1 second to load, <1 second to calculate the mean of swh). When performing a more complex analysis, using the kerchunk indices can really speed up your work."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "8687dc7e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 925 ms, sys: 3.45 ms, total: 928 ms\n",
+      "Wall time: 2.34 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "filename, _ = urllib.request.urlretrieve(url)\n",
+    "ds = xr.open_dataset(filename, engine=\"cfgrib\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "d2623637",
    "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 11.5 ms, sys: 3 ms, total: 14.5 ms\n",
+      "Wall time: 13.7 ms\n"
+     ]
+    },
+    {
+     "data": {
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+       "  grid-column: 1;\n",
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+       "\n",
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+       "  color: var(--xr-font-color3);\n",
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+       ".xr-array-data {\n",
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+       "  display: block;\n",
+       "}\n",
+       "\n",
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+       "  float: right;\n",
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+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
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+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;swh&#x27; ()&gt;\n",
+       "array(2.561255, dtype=float32)\n",
+       "Coordinates:\n",
+       "    time        datetime64[ns] ...\n",
+       "    step        timedelta64[ns] ...\n",
+       "    meanSea     float64 ...\n",
+       "    valid_time  datetime64[ns] ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'swh'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c2cba6c6-481b-4ecf-9881-f774aa91a953' class='xr-array-in' type='checkbox' checked><label for='section-c2cba6c6-481b-4ecf-9881-f774aa91a953' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.561</span></div><div class='xr-array-data'><pre>array(2.561255, dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-a7f3e109-ef44-4a63-93a2-d96ffdf45638' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a7f3e109-ef44-4a63-93a2-d96ffdf45638' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4081dbb0-3b9e-44fc-9694-ff353958832b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4081dbb0-3b9e-44fc-9694-ff353958832b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8dc1ef43-ba93-4e6b-beee-1803d44d7105' class='xr-var-data-in' type='checkbox'><label for='data-8dc1ef43-ba93-4e6b-beee-1803d44d7105' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1fa468e1-fdf2-4d23-ad36-81fb317365b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1fa468e1-fdf2-4d23-ad36-81fb317365b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-910abaac-a58b-4d5c-9f8c-b43227d3f3fa' class='xr-var-data-in' type='checkbox'><label for='data-910abaac-a58b-4d5c-9f8c-b43227d3f3fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=timedelta64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>meanSea</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7e0c3c44-40c5-4ba6-89da-567233b6f009' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e0c3c44-40c5-4ba6-89da-567233b6f009' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-169ba2b1-8963-4230-a299-0759388aaf35' class='xr-var-data-in' type='checkbox'><label for='data-169ba2b1-8963-4230-a299-0759388aaf35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(meanSea)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-329bcb4d-3a8e-4a70-bc9c-1771c980724a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-329bcb4d-3a8e-4a70-bc9c-1771c980724a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d83b249-5da2-46a4-96e9-37fe2dc68cda' class='xr-var-data-in' type='checkbox'><label for='data-9d83b249-5da2-46a4-96e9-37fe2dc68cda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-913e52d4-45d8-466f-a331-d51b06d0fc80' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-913e52d4-45d8-466f-a331-d51b06d0fc80' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-b5d4d68b-9c00-4114-b83b-125508ea7797' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b5d4d68b-9c00-4114-b83b-125508ea7797' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'swh' ()>\n",
+       "array(2.561255, dtype=float32)\n",
+       "Coordinates:\n",
+       "    time        datetime64[ns] ...\n",
+       "    step        timedelta64[ns] ...\n",
+       "    meanSea     float64 ...\n",
+       "    valid_time  datetime64[ns] ..."
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "ds['swh'].mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "1726ad14",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 17.3 ms, sys: 268 µs, total: 17.5 ms\n",
+      "Wall time: 16.5 ms\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "m = fsspec.get_mapper('reference://', fo=item.properties['kerchunk_indices'])\n",
+    "ds = xr.open_dataset(m, engine='zarr', consolidated=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "423574ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 31.2 ms, sys: 680 µs, total: 31.9 ms\n",
+      "Wall time: 927 ms\n"
+     ]
+    },
+    {
+     "data": {
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+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;swh&#x27; ()&gt;\n",
+       "array(2.56125508)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'swh'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b1aa0ad7-e4fe-4bdd-b0f0-23fbd83d0eb4' class='xr-array-in' type='checkbox' checked><label for='section-b1aa0ad7-e4fe-4bdd-b0f0-23fbd83d0eb4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.561</span></div><div class='xr-array-data'><pre>array(2.56125508)</pre></div></div></li><li class='xr-section-item'><input id='section-2b4d98ac-79f4-4aa3-8701-d910f06f4327' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2b4d98ac-79f4-4aa3-8701-d910f06f4327' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-a7054f66-873a-4bc5-83ec-e20f8379d7b6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a7054f66-873a-4bc5-83ec-e20f8379d7b6' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-b18af34f-2931-41e9-9c38-f93d7efe340a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b18af34f-2931-41e9-9c38-f93d7efe340a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'swh' ()>\n",
+       "array(2.56125508)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "There are many more streams and forecast types available. See the [catalog](http://planetarycomputer.microsoft.com/dataset/ecmwf-forecast) for more."
+    "%%time\n",
+    "ds['swh'].mean()"
    ]
   }
  ],
@@ -1137,7 +3332,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.10"
+   "version": "3.8.16"
   }
  },
  "nbformat": 4,