cacheb/cacheb-climate-example.ipynb

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  {
   "cell_type": "markdown",
   "id": "fb158044-8729-4464-9811-4ef8393aaded",
   "metadata": {},
   "source": [
    "# DestinE Platform CacheB data access"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "990e6a7c-0fa0-46b9-b177-ac3f3f57d87b",
   "metadata": {},
   "source": [
    "## Prerequisites\n",
    "### DestinE Platform Credentials\n",
    "\n",
    "You need to have an account on the [Destination Earth Platform](https://auth.destine.eu/realms/desp/account).\n",
    "\n",
    "#### ⚠️ Warning: Authorized Access Only\n",
    "The usage of this notebook and data access is reserved only to authorized user groups."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4db2bbb1-2e10-4a64-9e84-601e3e7ee64c",
   "metadata": {},
   "source": [
    "## Access the Data\n",
    "With a DESP account you can access the dataset in the CacheB cache with Xarray / Zarr.\n",
    "\n",
    "Here below the list of available datasets, they are all reachable via a dedicated URL. In the following example we will work only with the Climate DT high resolution surface with hourly resolution, on atmosphere variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "efbaa0bb-8298-4ee9-a3b3-0fa9667968d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "datasets = [\n",
    "    \"https://cacheb.dcms.destine.eu/d1-climate-dt/ScenarioMIP-SSP3-7.0-IFS-NEMO-0001-high-sfc-v0.zarr\",\n",
    "    \"https://cacheb.dcms.destine.eu/d1-climate-dt/ScenarioMIP-SSP3-7.0-IFS-NEMO-0001-high-o2d-v0.zarr\",\n",
    "    \"https://cacheb.dcms.destine.eu/d1-climate-dt/ScenarioMIP-SSP3-7.0-IFS-NEMO-0001-high-pl-v0.zarr\",\n",
    "    \"https://cacheb.dcms.destine.eu/d1-climate-dt/ScenarioMIP-SSP3-7.0-ICON-0001-high-sfc-v0.zarr\",\n",
    "    \"https://cacheb.dcms.destine.eu/era5/reanalysis-era5-land-no-antartica-v0.zarr\",\n",
    "    \"https://cacheb.dcms.destine.eu/era5/reanalysis-era5-single-levels-v0.zarr\",\n",
    "]"
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  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e71b840",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture cap\n",
    "%run ./cacheb-authentication.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51b53ed4",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_1 = cap.stdout.split('}\\n')\n",
    "token = output_1[-1][0:-1]\n",
    "\n",
    "from pathlib import Path\n",
    "with open(Path.home() / \".netrc\", \"a\") as fp:\n",
    "    fp.write(token)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "033a05bd",
   "metadata": {},
   "source": [
    "**NOTE**: the temporary password is valid for a limited period of time and needs to be regenerated and reconfigured periodically by running the cells above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d6376bac-fb44-4d19-9e49-70760aa0c207",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "data = xr.open_dataset(\n",
    "        \"https://cacheb.dcms.destine.eu/d1-climate-dt/ScenarioMIP-SSP3-7.0-IFS-NEMO-0001-high-sfc-v0.zarr\",\n",
    "        engine=\"zarr\",\n",
    "        storage_options={\"client_kwargs\": {\"trust_env\": \"true\"}},\n",
    "        chunks={},\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d0cfb4e5-c7c2-4fed-a40a-18127fbe417c",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 82TB\n",
       "Dimensions:            (time: 87672, latitude: 4096, longitude: 8193)\n",
       "Coordinates:\n",
       "    heightAboveGround  float64 8B ...\n",
       "  * latitude           (latitude) float64 33kB -90.0 -89.96 ... 89.96 90.0\n",
       "  * longitude          (longitude) float64 66kB -180.0 -180.0 ... 180.0 180.0\n",
       "    step               timedelta64[ns] 8B ...\n",
       "    surface            float64 8B ...\n",
       "  * time               (time) datetime64[ns] 701kB 2020-01-01 ... 2029-12-31T...\n",
       "Data variables:\n",
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       "    ssr                (time, latitude, longitude) float32 12TB dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;\n",
       "    str                (time, latitude, longitude) float32 12TB dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;\n",
       "    t2m                (time, latitude, longitude) float32 12TB dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;\n",
       "    tprate             (time, latitude, longitude) float32 12TB dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;\n",
       "    u10                (time, latitude, longitude) float32 12TB dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;\n",
       "    v10                (time, latitude, longitude) float32 12TB dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    Conventions:             CF-1.7\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_edition:            2\n",
       "    GRIB_subCentre:          1003\n",
       "    history:                 2024-04-03T18:54 GRIB to CDM+CF via cfgrib-0.9.1...\n",
       "    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-f71f898e-ec78-4f0e-a23b-a053ac30501b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f71f898e-ec78-4f0e-a23b-a053ac30501b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 87672</li><li><span class='xr-has-index'>latitude</span>: 4096</li><li><span class='xr-has-index'>longitude</span>: 8193</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-85f26a41-044c-452d-8747-ccbcb4bc1681' class='xr-section-summary-in' type='checkbox'  checked><label for='section-85f26a41-044c-452d-8747-ccbcb4bc1681' 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>heightAboveGround</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-aba021e5-ce9a-492d-ad6f-4d78c314b015' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aba021e5-ce9a-492d-ad6f-4d78c314b015' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7121c53-9f7a-4c7f-a437-ee5033bd9b2d' class='xr-var-data-in' type='checkbox'><label for='data-e7121c53-9f7a-4c7f-a437-ee5033bd9b2d' title='Show/Hide data repr'><svg 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>height above the surface</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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 -89.96 -89.91 ... 89.96 90.0</div><input id='attrs-13c576bc-4a7d-4d16-abdb-0c567ddef028' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-13c576bc-4a7d-4d16-abdb-0c567ddef028' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e56c306-c684-4304-b453-ece91cb35d23' class='xr-var-data-in' type='checkbox'><label for='data-6e56c306-c684-4304-b453-ece91cb35d23' title='Show/Hide data repr'><svg 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.      , -89.956044, -89.912088, ...,  89.912088,  89.956044,\n",
       "        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 -180.0 ... 180.0 180.0</div><input id='attrs-99b55657-2ad9-4c30-8bf1-20d547cd559f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99b55657-2ad9-4c30-8bf1-20d547cd559f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6419d8d7-74b3-4ceb-99de-67d2c9d67a47' class='xr-var-data-in' type='checkbox'><label for='data-6419d8d7-74b3-4ceb-99de-67d2c9d67a47' title='Show/Hide data repr'><svg 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.      , -179.956055, -179.912109, ...,  179.912109,  179.956055,\n",
       "        180.      ])</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-aed0993c-cc2f-456f-9b73-9535d4f15a92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aed0993c-cc2f-456f-9b73-9535d4f15a92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-010d2ab1-88da-4063-a20a-3ac9df0ad065' class='xr-var-data-in' type='checkbox'><label for='data-010d2ab1-88da-4063-a20a-3ac9df0ad065' title='Show/Hide data repr'><svg 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>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-a201c179-161c-4376-b3f5-d72a3f4e31e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a201c179-161c-4376-b3f5-d72a3f4e31e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89e4745c-5385-4fb5-bef9-a6961a6abb9e' class='xr-var-data-in' type='checkbox'><label for='data-89e4745c-5385-4fb5-bef9-a6961a6abb9e' title='Show/Hide data repr'><svg 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>[1 values with dtype=float64]</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'>2020-01-01 ... 2029-12-31T23:00:00</div><input id='attrs-a3fa0d68-bd11-492a-b835-2f0173c10035' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a3fa0d68-bd11-492a-b835-2f0173c10035' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33ce68b6-eb7f-406f-a30c-8da0c2a344fc' class='xr-var-data-in' type='checkbox'><label for='data-33ce68b6-eb7f-406f-a30c-8da0c2a344fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-01-01T00:00:00.000000000&#x27;, &#x27;2020-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2020-01-01T02:00:00.000000000&#x27;, ..., &#x27;2029-12-31T21:00:00.000000000&#x27;,\n",
       "       &#x27;2029-12-31T22:00:00.000000000&#x27;, &#x27;2029-12-31T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-52a305f0-9b2d-4de8-ad82-b783bca0dee7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-52a305f0-9b2d-4de8-ad82-b783bca0dee7' class='xr-section-summary' >Data variables: <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>d2m</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;</div><input id='attrs-97a5d66f-bd65-4c00-8cce-2a027fd15780' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97a5d66f-bd65-4c00-8cce-2a027fd15780' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ec47526-e9a0-42a5-b857-e15b1bc7498d' class='xr-var-data-in' type='checkbox'><label for='data-6ec47526-e9a0-42a5-b857-e15b1bc7498d' title='Show/Hide data repr'><svg 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_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>d2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>150</dd><dt><span>GRIB_gridType :</span></dt><dd>healpix</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>2 metre dewpoint temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>12582912</dd><dt><span>GRIB_paramId :</span></dt><dd>168</dd><dt><span>GRIB_shortName :</span></dt><dd>2d</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>heightAboveGround</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>last_restart_dim_updated :</span></dt><dd>84936</dd><dt><span>long_name :</span></dt><dd>2 metre dewpoint temperature</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 10.70 TiB </td>\n",
       "                        <td> 48.00 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (87672, 4096, 8193) </td>\n",
       "                        <td> (48, 512, 512) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 248472 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                        <td> 10.70 TiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t2m</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;</div><input id='attrs-72751df3-5fd1-4cfd-b78b-957a24e765f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72751df3-5fd1-4cfd-b78b-957a24e765f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f95811d-8962-479f-a6d4-2cb664428fec' class='xr-var-data-in' type='checkbox'><label for='data-1f95811d-8962-479f-a6d4-2cb664428fec' title='Show/Hide data repr'><svg 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_cfName :</span></dt><dd>air_temperature</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>150</dd><dt><span>GRIB_gridType :</span></dt><dd>healpix</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>12582912</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</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>heightAboveGround</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>last_restart_dim_updated :</span></dt><dd>84936</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 10.70 TiB </td>\n",
       "                        <td> 48.00 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (87672, 4096, 8193) </td>\n",
       "                        <td> (48, 512, 512) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 248472 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                </tbody>\n",
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       "        </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tprate</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;</div><input id='attrs-4fb9dc43-548d-4955-aca8-ead6e417ea1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fb9dc43-548d-4955-aca8-ead6e417ea1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ad98812-a91a-4f06-81f8-e7835848f415' class='xr-var-data-in' type='checkbox'><label for='data-2ad98812-a91a-4f06-81f8-e7835848f415' title='Show/Hide data repr'><svg 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_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>tprate</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>150</dd><dt><span>GRIB_gridType :</span></dt><dd>healpix</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation rate</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>12582912</dd><dt><span>GRIB_paramId :</span></dt><dd>260048</dd><dt><span>GRIB_shortName :</span></dt><dd>tprate</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>surface</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2 s**-1</dd><dt><span>last_restart_dim_updated :</span></dt><dd>84936</dd><dt><span>long_name :</span></dt><dd>Total precipitation rate</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>kg m**-2 s**-1</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 10.70 TiB </td>\n",
       "                        <td> 48.00 MiB </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v10</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(48, 512, 512), meta=np.ndarray&gt;</div><input id='attrs-a3911b1a-8cca-4772-86ce-5e61981e832c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3911b1a-8cca-4772-86ce-5e61981e832c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2081158d-c82d-4eb5-9b63-4b3bf261dfbd' class='xr-var-data-in' type='checkbox'><label for='data-2081158d-c82d-4eb5-9b63-4b3bf261dfbd' title='Show/Hide data repr'><svg 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_cfName :</span></dt><dd>northward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>v10</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>150</dd><dt><span>GRIB_gridType :</span></dt><dd>healpix</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>10 metre V wind component</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>12582912</dd><dt><span>GRIB_paramId :</span></dt><dd>166</dd><dt><span>GRIB_shortName :</span></dt><dd>10v</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>heightAboveGround</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>last_restart_dim_updated :</span></dt><dd>84936</dd><dt><span>long_name :</span></dt><dd>10 metre V wind component</dd><dt><span>standard_name :</span></dt><dd>northward_wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 10.70 TiB </td>\n",
       "                        <td> 48.00 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (48, 512, 512) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 248472 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-9066c45c-ca97-4ccd-8a67-9f62bc6f8ff1' class='xr-section-summary-in' type='checkbox'  ><label for='section-9066c45c-ca97-4ccd-8a67-9f62bc6f8ff1' 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-39ea1c36-f26c-43d0-b88d-1b3b03b679e8' class='xr-index-data-in' type='checkbox'/><label for='index-39ea1c36-f26c-43d0-b88d-1b3b03b679e8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -90.0, -89.95604395604396, -89.91208791208791,\n",
       "       -89.86813186813187, -89.82417582417582, -89.78021978021978,\n",
       "       -89.73626373626374,  -89.6923076923077, -89.64835164835165,\n",
       "        -89.6043956043956,\n",
       "       ...\n",
       "        89.60439560439562,  89.64835164835165,  89.69230769230771,\n",
       "        89.73626373626374,   89.7802197802198,  89.82417582417582,\n",
       "        89.86813186813188,  89.91208791208791,  89.95604395604397,\n",
       "                     90.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=4096))</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-384ab7fe-6552-49d8-92b2-6a0d17ab047d' class='xr-index-data-in' type='checkbox'/><label for='index-384ab7fe-6552-49d8-92b2-6a0d17ab047d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([             -180.0,     -179.9560546875, -179.91210937500003,\n",
       "           -179.8681640625,       -179.82421875,     -179.7802734375,\n",
       "            -179.736328125,     -179.6923828125,        -179.6484375,\n",
       "           -179.6044921875,\n",
       "       ...\n",
       "            179.6044921875,         179.6484375,      179.6923828125,\n",
       "             179.736328125,      179.7802734375,        179.82421875,\n",
       "            179.8681640625,  179.91210937500003,      179.9560546875,\n",
       "                     180.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=8193))</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-28f89b83-d301-433d-96a0-98820d186baf' class='xr-index-data-in' type='checkbox'/><label for='index-28f89b83-d301-433d-96a0-98820d186baf' 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;2020-01-01 00:00:00&#x27;, &#x27;2020-01-01 01:00:00&#x27;,\n",
       "               &#x27;2020-01-01 02:00:00&#x27;, &#x27;2020-01-01 03:00:00&#x27;,\n",
       "               &#x27;2020-01-01 04:00:00&#x27;, &#x27;2020-01-01 05:00:00&#x27;,\n",
       "               &#x27;2020-01-01 06:00:00&#x27;, &#x27;2020-01-01 07:00:00&#x27;,\n",
       "               &#x27;2020-01-01 08:00:00&#x27;, &#x27;2020-01-01 09:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2029-12-31 14:00:00&#x27;, &#x27;2029-12-31 15:00:00&#x27;,\n",
       "               &#x27;2029-12-31 16:00:00&#x27;, &#x27;2029-12-31 17:00:00&#x27;,\n",
       "               &#x27;2029-12-31 18:00:00&#x27;, &#x27;2029-12-31 19:00:00&#x27;,\n",
       "               &#x27;2029-12-31 20:00:00&#x27;, &#x27;2029-12-31 21:00:00&#x27;,\n",
       "               &#x27;2029-12-31 22:00:00&#x27;, &#x27;2029-12-31 23:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=87672, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4b587155-1fac-45cc-8d42-5ed6287b6eb5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4b587155-1fac-45cc-8d42-5ed6287b6eb5' 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>Conventions :</span></dt><dd>CF-1.7</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_edition :</span></dt><dd>2</dd><dt><span>GRIB_subCentre :</span></dt><dd>1003</dd><dt><span>history :</span></dt><dd>2024-04-03T18:54 GRIB to CDM+CF via cfgrib-0.9.10.4/ecCodes-2.34.1 with {&quot;source&quot;: &quot;.xarray-ecmwf-cache/efe5e9288daf73b14b49af1fec67e456.grib&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</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> Size: 82TB\n",
       "Dimensions:            (time: 87672, latitude: 4096, longitude: 8193)\n",
       "Coordinates:\n",
       "    heightAboveGround  float64 8B ...\n",
       "  * latitude           (latitude) float64 33kB -90.0 -89.96 ... 89.96 90.0\n",
       "  * longitude          (longitude) float64 66kB -180.0 -180.0 ... 180.0 180.0\n",
       "    step               timedelta64[ns] 8B ...\n",
       "    surface            float64 8B ...\n",
       "  * time               (time) datetime64[ns] 701kB 2020-01-01 ... 2029-12-31T...\n",
       "Data variables:\n",
       "    d2m                (time, latitude, longitude) float32 12TB dask.array<chunksize=(48, 512, 512), meta=np.ndarray>\n",
       "    ssr                (time, latitude, longitude) float32 12TB dask.array<chunksize=(48, 512, 512), meta=np.ndarray>\n",
       "    str                (time, latitude, longitude) float32 12TB dask.array<chunksize=(48, 512, 512), meta=np.ndarray>\n",
       "    t2m                (time, latitude, longitude) float32 12TB dask.array<chunksize=(48, 512, 512), meta=np.ndarray>\n",
       "    tprate             (time, latitude, longitude) float32 12TB dask.array<chunksize=(48, 512, 512), meta=np.ndarray>\n",
       "    u10                (time, latitude, longitude) float32 12TB dask.array<chunksize=(48, 512, 512), meta=np.ndarray>\n",
       "    v10                (time, latitude, longitude) float32 12TB dask.array<chunksize=(48, 512, 512), meta=np.ndarray>\n",
       "Attributes:\n",
       "    Conventions:             CF-1.7\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_edition:            2\n",
       "    GRIB_subCentre:          1003\n",
       "    history:                 2024-04-03T18:54 GRIB to CDM+CF via cfgrib-0.9.1...\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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    "data"
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  {
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   "source": [
    "## Working with data\n",
    "\n",
    "Datasets on the DESP Data CacheB are typically very large and remotely hosted. Typical use imply a selection of the data followed by one or more reduction steps to be performed in a local or distributed Dask environment. \n",
    "\n",
    "The structure of a workflow that uses EDH data looks like this:\n",
    "1. data selection\n",
    "2. data reduction\n",
    "3. visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "65828ff0-618b-4f13-8cf0-ce0822497f8e",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;t2m&#x27; (time: 87672, latitude: 182, longitude: 251)&gt; Size: 16GB\n",
       "dask.array&lt;getitem, shape=(87672, 182, 251), dtype=float32, chunksize=(48, 182, 251), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "    heightAboveGround  float64 8B ...\n",
       "  * latitude           (latitude) float64 1kB 47.01 47.05 47.1 ... 54.92 54.97\n",
       "  * longitude          (longitude) float64 2kB 5.01 5.054 5.098 ... 15.95 16.0\n",
       "    step               timedelta64[ns] 8B ...\n",
       "    surface            float64 8B ...\n",
       "  * time               (time) datetime64[ns] 701kB 2020-01-01 ... 2029-12-31T...\n",
       "Attributes:\n",
       "    units:    C</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'t2m'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 87672</li><li><span class='xr-has-index'>latitude</span>: 182</li><li><span class='xr-has-index'>longitude</span>: 251</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2adbafdd-f455-421d-9095-31c557f06c6a' class='xr-array-in' type='checkbox' checked><label for='section-2adbafdd-f455-421d-9095-31c557f06c6a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(48, 182, 251), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 14.92 GiB </td>\n",
       "                        <td> 8.36 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
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       "                        <td> (87672, 182, 251) </td>\n",
       "                        <td> (48, 182, 251) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1827 chunks in 4 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "\n",
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       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"36\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"40\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"43\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"47\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"51\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"55\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"58\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"62\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"66\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"69\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"73\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"77\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"81\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"84\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"88\" />\n",
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       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"96\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,96.00085180870013 10.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"39\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"42\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"46\" y2=\"11\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"50\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"53\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"57\" y2=\"22\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"61\" y2=\"26\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"65\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"68\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"72\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"76\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"79\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"83\" y2=\"48\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"87\" y2=\"52\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"91\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"94\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"98\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"102\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"106\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"35\" y1=\"0\" x2=\"106\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 35.41261651458248,0.0 106.00085180870013,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"106\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"96\" x2=\"106\" y2=\"96\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"96\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"106\" y1=\"70\" x2=\"106\" y2=\"96\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 106.00085180870013,70.58823529411765 106.00085180870013,96.00085180870013 80.58823529411765,96.00085180870013\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"93.294544\" y=\"116.000852\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >251</text>\n",
       "  <text x=\"126.000852\" y=\"83.294544\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,126.000852,83.294544)\">182</text>\n",
       "  <text x=\"35.294118\" y=\"80.706734\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,80.706734)\">87672</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-6cc71775-fabd-4685-8ff4-d50836140910' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6cc71775-fabd-4685-8ff4-d50836140910' 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>heightAboveGround</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-30074699-9ef9-4e1f-ab46-f80e4e59d682' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30074699-9ef9-4e1f-ab46-f80e4e59d682' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e9e9496-f930-4ac1-b5e0-549561932570' class='xr-var-data-in' type='checkbox'><label for='data-4e9e9496-f930-4ac1-b5e0-549561932570' title='Show/Hide data repr'><svg 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>height above the surface</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>47.01 47.05 47.1 ... 54.92 54.97</div><input id='attrs-8af5c497-0a2a-4e00-a1bf-656f325cf7ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8af5c497-0a2a-4e00-a1bf-656f325cf7ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed12474f-fcac-4062-b586-d9d0936554de' class='xr-var-data-in' type='checkbox'><label for='data-ed12474f-fcac-4062-b586-d9d0936554de' title='Show/Hide data repr'><svg 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([47.010989, 47.054945, 47.098901, 47.142857, 47.186813, 47.230769,\n",
       "       47.274725, 47.318681, 47.362637, 47.406593, 47.450549, 47.494505,\n",
       "       47.538462, 47.582418, 47.626374, 47.67033 , 47.714286, 47.758242,\n",
       "       47.802198, 47.846154, 47.89011 , 47.934066, 47.978022, 48.021978,\n",
       "       48.065934, 48.10989 , 48.153846, 48.197802, 48.241758, 48.285714,\n",
       "       48.32967 , 48.373626, 48.417582, 48.461538, 48.505495, 48.549451,\n",
       "       48.593407, 48.637363, 48.681319, 48.725275, 48.769231, 48.813187,\n",
       "       48.857143, 48.901099, 48.945055, 48.989011, 49.032967, 49.076923,\n",
       "       49.120879, 49.164835, 49.208791, 49.252747, 49.296703, 49.340659,\n",
       "       49.384615, 49.428571, 49.472527, 49.516484, 49.56044 , 49.604396,\n",
       "       49.648352, 49.692308, 49.736264, 49.78022 , 49.824176, 49.868132,\n",
       "       49.912088, 49.956044, 50.      , 50.043956, 50.087912, 50.131868,\n",
       "       50.175824, 50.21978 , 50.263736, 50.307692, 50.351648, 50.395604,\n",
       "       50.43956 , 50.483516, 50.527473, 50.571429, 50.615385, 50.659341,\n",
       "       50.703297, 50.747253, 50.791209, 50.835165, 50.879121, 50.923077,\n",
       "       50.967033, 51.010989, 51.054945, 51.098901, 51.142857, 51.186813,\n",
       "       51.230769, 51.274725, 51.318681, 51.362637, 51.406593, 51.450549,\n",
       "       51.494505, 51.538462, 51.582418, 51.626374, 51.67033 , 51.714286,\n",
       "       51.758242, 51.802198, 51.846154, 51.89011 , 51.934066, 51.978022,\n",
       "       52.021978, 52.065934, 52.10989 , 52.153846, 52.197802, 52.241758,\n",
       "       52.285714, 52.32967 , 52.373626, 52.417582, 52.461538, 52.505495,\n",
       "       52.549451, 52.593407, 52.637363, 52.681319, 52.725275, 52.769231,\n",
       "       52.813187, 52.857143, 52.901099, 52.945055, 52.989011, 53.032967,\n",
       "       53.076923, 53.120879, 53.164835, 53.208791, 53.252747, 53.296703,\n",
       "       53.340659, 53.384615, 53.428571, 53.472527, 53.516484, 53.56044 ,\n",
       "       53.604396, 53.648352, 53.692308, 53.736264, 53.78022 , 53.824176,\n",
       "       53.868132, 53.912088, 53.956044, 54.      , 54.043956, 54.087912,\n",
       "       54.131868, 54.175824, 54.21978 , 54.263736, 54.307692, 54.351648,\n",
       "       54.395604, 54.43956 , 54.483516, 54.527473, 54.571429, 54.615385,\n",
       "       54.659341, 54.703297, 54.747253, 54.791209, 54.835165, 54.879121,\n",
       "       54.923077, 54.967033])</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'>5.01 5.054 5.098 ... 15.95 16.0</div><input id='attrs-789c124f-bfc9-4ee4-bb19-bcb57d22c1b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-789c124f-bfc9-4ee4-bb19-bcb57d22c1b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8807d493-9ad6-4a82-8ce5-8b3152103e29' class='xr-var-data-in' type='checkbox'><label for='data-8807d493-9ad6-4a82-8ce5-8b3152103e29' title='Show/Hide data repr'><svg 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([ 5.009766,  5.053711,  5.097656, ..., 15.908203, 15.952148, 15.996094])</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-6f617b09-8e0b-461c-b324-ff89e26cc46f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f617b09-8e0b-461c-b324-ff89e26cc46f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9965ce7-3fb2-48b4-a46f-926e9e872d4f' class='xr-var-data-in' type='checkbox'><label for='data-d9965ce7-3fb2-48b4-a46f-926e9e872d4f' title='Show/Hide data repr'><svg 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>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-3afecafa-84c8-4ad5-9bda-56c4cbb1b79a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3afecafa-84c8-4ad5-9bda-56c4cbb1b79a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e197634b-ed6c-4247-b0bc-c0d4cfcbd871' class='xr-var-data-in' type='checkbox'><label for='data-e197634b-ed6c-4247-b0bc-c0d4cfcbd871' title='Show/Hide data repr'><svg 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>[1 values with dtype=float64]</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'>2020-01-01 ... 2029-12-31T23:00:00</div><input id='attrs-402b9aeb-c6a4-4e6b-b9de-746e4679aae4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-402b9aeb-c6a4-4e6b-b9de-746e4679aae4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fcc3865-eb5f-42d1-955a-63da5b10982d' class='xr-var-data-in' type='checkbox'><label for='data-0fcc3865-eb5f-42d1-955a-63da5b10982d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-01-01T00:00:00.000000000&#x27;, &#x27;2020-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2020-01-01T02:00:00.000000000&#x27;, ..., &#x27;2029-12-31T21:00:00.000000000&#x27;,\n",
       "       &#x27;2029-12-31T22:00:00.000000000&#x27;, &#x27;2029-12-31T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-10b7f56c-74f0-4d03-aa54-0a9c2c8c595f' class='xr-section-summary-in' type='checkbox'  ><label for='section-10b7f56c-74f0-4d03-aa54-0a9c2c8c595f' 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-9de6b6a7-8c04-4b90-91d5-e494d144557f' class='xr-index-data-in' type='checkbox'/><label for='index-9de6b6a7-8c04-4b90-91d5-e494d144557f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 47.01098901098902,  47.05494505494508,  47.09890109890111,\n",
       "        47.14285714285717,   47.1868131868132, 47.230769230769255,\n",
       "        47.27472527472529,  47.31868131868134,  47.36263736263737,\n",
       "        47.40659340659343,\n",
       "       ...\n",
       "        54.57142857142859,  54.61538461538461,  54.65934065934067,\n",
       "         54.7032967032967,  54.74725274725276,  54.79120879120879,\n",
       "       54.835164835164846, 54.879120879120904, 54.923076923076934,\n",
       "        54.96703296703299],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=182))</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-4c347e39-c15f-437e-ac5b-36c140c2f160' class='xr-index-data-in' type='checkbox'/><label for='index-4c347e39-c15f-437e-ac5b-36c140c2f160' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 5.009765625000001,       5.0537109375,         5.09765625,\n",
       "             5.1416015625,        5.185546875,       5.2294921875,\n",
       "                5.2734375,       5.3173828125,        5.361328125,\n",
       "             5.4052734375,\n",
       "       ...\n",
       "            15.6005859375, 15.644531250000002,      15.6884765625,\n",
       "             15.732421875, 15.776367187499998,         15.8203125,\n",
       "       15.864257812500002,       15.908203125, 15.952148437500002,\n",
       "              15.99609375],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=251))</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-295e8af7-a613-4495-8316-629897a54b78' class='xr-index-data-in' type='checkbox'/><label for='index-295e8af7-a613-4495-8316-629897a54b78' 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;2020-01-01 00:00:00&#x27;, &#x27;2020-01-01 01:00:00&#x27;,\n",
       "               &#x27;2020-01-01 02:00:00&#x27;, &#x27;2020-01-01 03:00:00&#x27;,\n",
       "               &#x27;2020-01-01 04:00:00&#x27;, &#x27;2020-01-01 05:00:00&#x27;,\n",
       "               &#x27;2020-01-01 06:00:00&#x27;, &#x27;2020-01-01 07:00:00&#x27;,\n",
       "               &#x27;2020-01-01 08:00:00&#x27;, &#x27;2020-01-01 09:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2029-12-31 14:00:00&#x27;, &#x27;2029-12-31 15:00:00&#x27;,\n",
       "               &#x27;2029-12-31 16:00:00&#x27;, &#x27;2029-12-31 17:00:00&#x27;,\n",
       "               &#x27;2029-12-31 18:00:00&#x27;, &#x27;2029-12-31 19:00:00&#x27;,\n",
       "               &#x27;2029-12-31 20:00:00&#x27;, &#x27;2029-12-31 21:00:00&#x27;,\n",
       "               &#x27;2029-12-31 22:00:00&#x27;, &#x27;2029-12-31 23:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=87672, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-119562f3-2063-4763-bb7c-c59cb909a0bf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-119562f3-2063-4763-bb7c-c59cb909a0bf' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>C</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 't2m' (time: 87672, latitude: 182, longitude: 251)> Size: 16GB\n",
       "dask.array<getitem, shape=(87672, 182, 251), dtype=float32, chunksize=(48, 182, 251), chunktype=numpy.ndarray>\n",
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       "    heightAboveGround  float64 8B ...\n",
       "  * latitude           (latitude) float64 1kB 47.01 47.05 47.1 ... 54.92 54.97\n",
       "  * longitude          (longitude) float64 2kB 5.01 5.054 5.098 ... 15.95 16.0\n",
       "    step               timedelta64[ns] 8B ...\n",
       "    surface            float64 8B ...\n",
       "  * time               (time) datetime64[ns] 701kB 2020-01-01 ... 2029-12-31T...\n",
       "Attributes:\n",
       "    units:    C"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t2m = data.t2m.astype(\"float32\") - 273.15\n",
    "t2m.attrs[\"units\"] = \"C\"\n",
    "t2m_germany_area = t2m.sel(**{\"latitude\": slice(47, 55), \"longitude\": slice(5, 16)})\n",
    "t2m_germany_area"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
   "id": "33bf3367-d8db-4b52-aa47-028921afa6bd",
   "metadata": {},
   "outputs": [
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       "  <line x1=\"60\" y1=\"50\" x2=\"104\" y2=\"50\" />\n",
       "  <line x1=\"64\" y1=\"54\" x2=\"108\" y2=\"54\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"113\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"117\" y2=\"63\" />\n",
       "  <line x1=\"78\" y1=\"68\" x2=\"122\" y2=\"68\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"124\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"53\" y1=\"0\" x2=\"124\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
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       "\n",
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       "  <line x1=\"80\" y1=\"70\" x2=\"124\" y2=\"70\" style=\"stroke-width:2\" />\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"113\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"124\" y1=\"70\" x2=\"124\" y2=\"113\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 124.51151464520225,70.58823529411765 124.51151464520225,113.40519883973045 80.58823529411765,113.40519883973045\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"102.549875\" y=\"133.405199\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >251</text>\n",
       "  <text x=\"144.511515\" y=\"91.996717\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,144.511515,91.996717)\">182</text>\n",
       "  <text x=\"35.294118\" y=\"98.111081\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,98.111081)\">744</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-6bd17175-768a-4de3-8a2f-b7935a5db520' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6bd17175-768a-4de3-8a2f-b7935a5db520' 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>heightAboveGround</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-b1d425f2-c561-44d2-a110-67adbd2f4b48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1d425f2-c561-44d2-a110-67adbd2f4b48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dadf3701-e33f-4701-8454-0969ea09eaa4' class='xr-var-data-in' type='checkbox'><label for='data-dadf3701-e33f-4701-8454-0969ea09eaa4' title='Show/Hide data repr'><svg 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>height above the surface</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>47.01 47.05 47.1 ... 54.92 54.97</div><input id='attrs-ce55ce60-340e-4b6f-9841-6a05aae9aa97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce55ce60-340e-4b6f-9841-6a05aae9aa97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8069b9ea-70c9-4381-a131-1d82097f89c1' class='xr-var-data-in' type='checkbox'><label for='data-8069b9ea-70c9-4381-a131-1d82097f89c1' title='Show/Hide data repr'><svg 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([47.010989, 47.054945, 47.098901, 47.142857, 47.186813, 47.230769,\n",
       "       47.274725, 47.318681, 47.362637, 47.406593, 47.450549, 47.494505,\n",
       "       47.538462, 47.582418, 47.626374, 47.67033 , 47.714286, 47.758242,\n",
       "       47.802198, 47.846154, 47.89011 , 47.934066, 47.978022, 48.021978,\n",
       "       48.065934, 48.10989 , 48.153846, 48.197802, 48.241758, 48.285714,\n",
       "       48.32967 , 48.373626, 48.417582, 48.461538, 48.505495, 48.549451,\n",
       "       48.593407, 48.637363, 48.681319, 48.725275, 48.769231, 48.813187,\n",
       "       48.857143, 48.901099, 48.945055, 48.989011, 49.032967, 49.076923,\n",
       "       49.120879, 49.164835, 49.208791, 49.252747, 49.296703, 49.340659,\n",
       "       49.384615, 49.428571, 49.472527, 49.516484, 49.56044 , 49.604396,\n",
       "       49.648352, 49.692308, 49.736264, 49.78022 , 49.824176, 49.868132,\n",
       "       49.912088, 49.956044, 50.      , 50.043956, 50.087912, 50.131868,\n",
       "       50.175824, 50.21978 , 50.263736, 50.307692, 50.351648, 50.395604,\n",
       "       50.43956 , 50.483516, 50.527473, 50.571429, 50.615385, 50.659341,\n",
       "       50.703297, 50.747253, 50.791209, 50.835165, 50.879121, 50.923077,\n",
       "       50.967033, 51.010989, 51.054945, 51.098901, 51.142857, 51.186813,\n",
       "       51.230769, 51.274725, 51.318681, 51.362637, 51.406593, 51.450549,\n",
       "       51.494505, 51.538462, 51.582418, 51.626374, 51.67033 , 51.714286,\n",
       "       51.758242, 51.802198, 51.846154, 51.89011 , 51.934066, 51.978022,\n",
       "       52.021978, 52.065934, 52.10989 , 52.153846, 52.197802, 52.241758,\n",
       "       52.285714, 52.32967 , 52.373626, 52.417582, 52.461538, 52.505495,\n",
       "       52.549451, 52.593407, 52.637363, 52.681319, 52.725275, 52.769231,\n",
       "       52.813187, 52.857143, 52.901099, 52.945055, 52.989011, 53.032967,\n",
       "       53.076923, 53.120879, 53.164835, 53.208791, 53.252747, 53.296703,\n",
       "       53.340659, 53.384615, 53.428571, 53.472527, 53.516484, 53.56044 ,\n",
       "       53.604396, 53.648352, 53.692308, 53.736264, 53.78022 , 53.824176,\n",
       "       53.868132, 53.912088, 53.956044, 54.      , 54.043956, 54.087912,\n",
       "       54.131868, 54.175824, 54.21978 , 54.263736, 54.307692, 54.351648,\n",
       "       54.395604, 54.43956 , 54.483516, 54.527473, 54.571429, 54.615385,\n",
       "       54.659341, 54.703297, 54.747253, 54.791209, 54.835165, 54.879121,\n",
       "       54.923077, 54.967033])</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'>5.01 5.054 5.098 ... 15.95 16.0</div><input id='attrs-be1d3c25-07ee-4f33-beba-eaf276bd8e4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be1d3c25-07ee-4f33-beba-eaf276bd8e4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e278a64-5534-41ff-9ad2-c00dfc20a135' class='xr-var-data-in' type='checkbox'><label for='data-4e278a64-5534-41ff-9ad2-c00dfc20a135' title='Show/Hide data repr'><svg 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([ 5.009766,  5.053711,  5.097656, ..., 15.908203, 15.952148, 15.996094])</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-1d2683f9-345b-49a4-beec-16513f33b75a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d2683f9-345b-49a4-beec-16513f33b75a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcee1d3c-3b5a-45be-91eb-168ff07c65c5' class='xr-var-data-in' type='checkbox'><label for='data-fcee1d3c-3b5a-45be-91eb-168ff07c65c5' title='Show/Hide data repr'><svg 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>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-ae6bc250-8986-402e-8481-9d59475f1516' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae6bc250-8986-402e-8481-9d59475f1516' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-244562df-fa15-4a99-b379-c8207169fae3' class='xr-var-data-in' type='checkbox'><label for='data-244562df-fa15-4a99-b379-c8207169fae3' title='Show/Hide data repr'><svg 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>[1 values with dtype=float64]</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'>2028-01-01 ... 2028-01-31T23:00:00</div><input id='attrs-48d8a42f-7ad4-4f79-878b-67c95bfa07f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-48d8a42f-7ad4-4f79-878b-67c95bfa07f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-757838f9-04af-4626-835a-6d4009a31ae1' class='xr-var-data-in' type='checkbox'><label for='data-757838f9-04af-4626-835a-6d4009a31ae1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2028-01-01T00:00:00.000000000&#x27;, &#x27;2028-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2028-01-01T02:00:00.000000000&#x27;, ..., &#x27;2028-01-31T21:00:00.000000000&#x27;,\n",
       "       &#x27;2028-01-31T22:00:00.000000000&#x27;, &#x27;2028-01-31T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a2d3c8c8-a895-4496-962a-0dd6d686bd0b' class='xr-section-summary-in' type='checkbox'  ><label for='section-a2d3c8c8-a895-4496-962a-0dd6d686bd0b' 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-2122f713-a23a-4854-9273-f4035e67fc51' class='xr-index-data-in' type='checkbox'/><label for='index-2122f713-a23a-4854-9273-f4035e67fc51' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 47.01098901098902,  47.05494505494508,  47.09890109890111,\n",
       "        47.14285714285717,   47.1868131868132, 47.230769230769255,\n",
       "        47.27472527472529,  47.31868131868134,  47.36263736263737,\n",
       "        47.40659340659343,\n",
       "       ...\n",
       "        54.57142857142859,  54.61538461538461,  54.65934065934067,\n",
       "         54.7032967032967,  54.74725274725276,  54.79120879120879,\n",
       "       54.835164835164846, 54.879120879120904, 54.923076923076934,\n",
       "        54.96703296703299],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=182))</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-8ca5e1fb-02c3-4ad2-991f-9a2bf6f4f25d' class='xr-index-data-in' type='checkbox'/><label for='index-8ca5e1fb-02c3-4ad2-991f-9a2bf6f4f25d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 5.009765625000001,       5.0537109375,         5.09765625,\n",
       "             5.1416015625,        5.185546875,       5.2294921875,\n",
       "                5.2734375,       5.3173828125,        5.361328125,\n",
       "             5.4052734375,\n",
       "       ...\n",
       "            15.6005859375, 15.644531250000002,      15.6884765625,\n",
       "             15.732421875, 15.776367187499998,         15.8203125,\n",
       "       15.864257812500002,       15.908203125, 15.952148437500002,\n",
       "              15.99609375],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=251))</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-45536891-1469-44f9-9552-242367035659' class='xr-index-data-in' type='checkbox'/><label for='index-45536891-1469-44f9-9552-242367035659' 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;2028-01-01 00:00:00&#x27;, &#x27;2028-01-01 01:00:00&#x27;,\n",
       "               &#x27;2028-01-01 02:00:00&#x27;, &#x27;2028-01-01 03:00:00&#x27;,\n",
       "               &#x27;2028-01-01 04:00:00&#x27;, &#x27;2028-01-01 05:00:00&#x27;,\n",
       "               &#x27;2028-01-01 06:00:00&#x27;, &#x27;2028-01-01 07:00:00&#x27;,\n",
       "               &#x27;2028-01-01 08:00:00&#x27;, &#x27;2028-01-01 09:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2028-01-31 14:00:00&#x27;, &#x27;2028-01-31 15:00:00&#x27;,\n",
       "               &#x27;2028-01-31 16:00:00&#x27;, &#x27;2028-01-31 17:00:00&#x27;,\n",
       "               &#x27;2028-01-31 18:00:00&#x27;, &#x27;2028-01-31 19:00:00&#x27;,\n",
       "               &#x27;2028-01-31 20:00:00&#x27;, &#x27;2028-01-31 21:00:00&#x27;,\n",
       "               &#x27;2028-01-31 22:00:00&#x27;, &#x27;2028-01-31 23:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=744, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-794bfabb-2b4b-4c7b-82c6-a7730212a3c6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-794bfabb-2b4b-4c7b-82c6-a7730212a3c6' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>C</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 't2m' (time: 744, latitude: 182, longitude: 251)> Size: 136MB\n",
       "dask.array<getitem, shape=(744, 182, 251), dtype=float32, chunksize=(48, 182, 251), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "    heightAboveGround  float64 8B ...\n",
       "  * latitude           (latitude) float64 1kB 47.01 47.05 47.1 ... 54.92 54.97\n",
       "  * longitude          (longitude) float64 2kB 5.01 5.054 5.098 ... 15.95 16.0\n",
       "    step               timedelta64[ns] 8B ...\n",
       "    surface            float64 8B ...\n",
       "  * time               (time) datetime64[ns] 6kB 2028-01-01 ... 2028-01-31T23...\n",
       "Attributes:\n",
       "    units:    C"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t2m_germany_area_selection = t2m_germany_area.sel(time=\"2028-01\")\n",
    "t2m_germany_area_selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fe496d38-862b-4184-8557-0d000f9c4aab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.34 s, sys: 703 ms, total: 2.05 s\n",
      "Wall time: 4.15 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "t2m_germany_area_selection = t2m_germany_area_selection.compute()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aefa0482-bb68-4854-b966-f1c75dae25b3",
   "metadata": {},
   "source": [
    "### 2. Data reduction\n",
    "\n",
    "Now that the data is loaded in memory, we can easily compute the monthly mean:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e7e58eb5-eb1a-458a-ba52-b0aaebab2ba1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
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       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
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       "  padding-right: 10px;\n",
       "}\n",
       "\n",
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       "\n",
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       ".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: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;t2m&#x27; (latitude: 182, longitude: 251)&gt; Size: 183kB\n",
       "array([[ 1.2636374,  1.2636374,  1.3567146, ..., -5.102584 , -5.102584 ,\n",
       "        -5.118713 ],\n",
       "       [ 1.2636374,  1.149727 ,  1.2639735, ..., -5.189445 , -5.189445 ,\n",
       "        -5.207086 ],\n",
       "       [ 1.149727 ,  1.0237204,  1.0237204, ..., -5.189445 , -5.161052 ,\n",
       "        -5.207086 ],\n",
       "       ...,\n",
       "       [ 2.8174255,  2.8174255,  2.8140652, ..., -1.6859541, -1.8778229,\n",
       "        -1.8778229],\n",
       "       [ 2.8140652,  2.8140652,  2.8140652, ..., -1.5508729, -1.4137752,\n",
       "        -1.7242607],\n",
       "       [ 2.8066719,  2.8066719,  2.8066719, ..., -1.4137752, -1.4137752,\n",
       "        -1.5723785]], dtype=float32)\n",
       "Coordinates:\n",
       "    heightAboveGround  float64 8B 2.0\n",
       "  * latitude           (latitude) float64 1kB 47.01 47.05 47.1 ... 54.92 54.97\n",
       "  * longitude          (longitude) float64 2kB 5.01 5.054 5.098 ... 15.95 16.0\n",
       "    step               timedelta64[ns] 8B 00:00:00\n",
       "    surface            float64 8B 0.0</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'>'t2m'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>latitude</span>: 182</li><li><span class='xr-has-index'>longitude</span>: 251</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a217649f-0272-45e3-9c0f-c209c0237133' class='xr-array-in' type='checkbox' checked><label for='section-a217649f-0272-45e3-9c0f-c209c0237133' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.264 1.264 1.357 1.264 1.264 ... -1.312 -1.414 -1.414 -1.414 -1.572</span></div><div class='xr-array-data'><pre>array([[ 1.2636374,  1.2636374,  1.3567146, ..., -5.102584 , -5.102584 ,\n",
       "        -5.118713 ],\n",
       "       [ 1.2636374,  1.149727 ,  1.2639735, ..., -5.189445 , -5.189445 ,\n",
       "        -5.207086 ],\n",
       "       [ 1.149727 ,  1.0237204,  1.0237204, ..., -5.189445 , -5.161052 ,\n",
       "        -5.207086 ],\n",
       "       ...,\n",
       "       [ 2.8174255,  2.8174255,  2.8140652, ..., -1.6859541, -1.8778229,\n",
       "        -1.8778229],\n",
       "       [ 2.8140652,  2.8140652,  2.8140652, ..., -1.5508729, -1.4137752,\n",
       "        -1.7242607],\n",
       "       [ 2.8066719,  2.8066719,  2.8066719, ..., -1.4137752, -1.4137752,\n",
       "        -1.5723785]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-ef5ee6e0-545e-473f-80d5-c774f92a1379' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ef5ee6e0-545e-473f-80d5-c774f92a1379' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>heightAboveGround</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-86b54a06-80a2-4896-8120-63499015559b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86b54a06-80a2-4896-8120-63499015559b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2410139e-48e7-4463-abab-dfc66799b993' class='xr-var-data-in' type='checkbox'><label for='data-2410139e-48e7-4463-abab-dfc66799b993' title='Show/Hide data repr'><svg 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>height above the surface</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>47.01 47.05 47.1 ... 54.92 54.97</div><input id='attrs-aa398b63-a3aa-4fde-9215-922e44903390' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa398b63-a3aa-4fde-9215-922e44903390' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79e68488-1a61-405b-a69e-17119f8873df' class='xr-var-data-in' type='checkbox'><label for='data-79e68488-1a61-405b-a69e-17119f8873df' title='Show/Hide data repr'><svg 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([47.010989, 47.054945, 47.098901, 47.142857, 47.186813, 47.230769,\n",
       "       47.274725, 47.318681, 47.362637, 47.406593, 47.450549, 47.494505,\n",
       "       47.538462, 47.582418, 47.626374, 47.67033 , 47.714286, 47.758242,\n",
       "       47.802198, 47.846154, 47.89011 , 47.934066, 47.978022, 48.021978,\n",
       "       48.065934, 48.10989 , 48.153846, 48.197802, 48.241758, 48.285714,\n",
       "       48.32967 , 48.373626, 48.417582, 48.461538, 48.505495, 48.549451,\n",
       "       48.593407, 48.637363, 48.681319, 48.725275, 48.769231, 48.813187,\n",
       "       48.857143, 48.901099, 48.945055, 48.989011, 49.032967, 49.076923,\n",
       "       49.120879, 49.164835, 49.208791, 49.252747, 49.296703, 49.340659,\n",
       "       49.384615, 49.428571, 49.472527, 49.516484, 49.56044 , 49.604396,\n",
       "       49.648352, 49.692308, 49.736264, 49.78022 , 49.824176, 49.868132,\n",
       "       49.912088, 49.956044, 50.      , 50.043956, 50.087912, 50.131868,\n",
       "       50.175824, 50.21978 , 50.263736, 50.307692, 50.351648, 50.395604,\n",
       "       50.43956 , 50.483516, 50.527473, 50.571429, 50.615385, 50.659341,\n",
       "       50.703297, 50.747253, 50.791209, 50.835165, 50.879121, 50.923077,\n",
       "       50.967033, 51.010989, 51.054945, 51.098901, 51.142857, 51.186813,\n",
       "       51.230769, 51.274725, 51.318681, 51.362637, 51.406593, 51.450549,\n",
       "       51.494505, 51.538462, 51.582418, 51.626374, 51.67033 , 51.714286,\n",
       "       51.758242, 51.802198, 51.846154, 51.89011 , 51.934066, 51.978022,\n",
       "       52.021978, 52.065934, 52.10989 , 52.153846, 52.197802, 52.241758,\n",
       "       52.285714, 52.32967 , 52.373626, 52.417582, 52.461538, 52.505495,\n",
       "       52.549451, 52.593407, 52.637363, 52.681319, 52.725275, 52.769231,\n",
       "       52.813187, 52.857143, 52.901099, 52.945055, 52.989011, 53.032967,\n",
       "       53.076923, 53.120879, 53.164835, 53.208791, 53.252747, 53.296703,\n",
       "       53.340659, 53.384615, 53.428571, 53.472527, 53.516484, 53.56044 ,\n",
       "       53.604396, 53.648352, 53.692308, 53.736264, 53.78022 , 53.824176,\n",
       "       53.868132, 53.912088, 53.956044, 54.      , 54.043956, 54.087912,\n",
       "       54.131868, 54.175824, 54.21978 , 54.263736, 54.307692, 54.351648,\n",
       "       54.395604, 54.43956 , 54.483516, 54.527473, 54.571429, 54.615385,\n",
       "       54.659341, 54.703297, 54.747253, 54.791209, 54.835165, 54.879121,\n",
       "       54.923077, 54.967033])</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'>5.01 5.054 5.098 ... 15.95 16.0</div><input id='attrs-8588f2fb-0e51-4fcd-bedf-36ffaa215b08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8588f2fb-0e51-4fcd-bedf-36ffaa215b08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65ae08a9-85f9-4b77-9d98-485041a0e3cd' class='xr-var-data-in' type='checkbox'><label for='data-65ae08a9-85f9-4b77-9d98-485041a0e3cd' title='Show/Hide data repr'><svg 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([ 5.009766,  5.053711,  5.097656, ..., 15.908203, 15.952148, 15.996094])</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'>00:00:00</div><input id='attrs-cbdbebbd-f790-462f-90f5-e91ede0f1a0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbdbebbd-f790-462f-90f5-e91ede0f1a0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63ec2056-62c2-42a8-b352-fd6e0718ef64' class='xr-var-data-in' type='checkbox'><label for='data-63ec2056-62c2-42a8-b352-fd6e0718ef64' title='Show/Hide data repr'><svg 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'>0.0</div><input id='attrs-8f572543-534b-437a-bcca-59b7b5c2cb15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f572543-534b-437a-bcca-59b7b5c2cb15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb204f71-154d-488c-b379-37249559126b' class='xr-var-data-in' type='checkbox'><label for='data-cb204f71-154d-488c-b379-37249559126b' title='Show/Hide data repr'><svg 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></ul></div></li><li class='xr-section-item'><input id='section-b498fd2c-fad3-4af3-bc45-09ed87158e37' class='xr-section-summary-in' type='checkbox'  ><label for='section-b498fd2c-fad3-4af3-bc45-09ed87158e37' 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-1b40ffb9-3588-4680-a26f-b77f7717c04c' class='xr-index-data-in' type='checkbox'/><label for='index-1b40ffb9-3588-4680-a26f-b77f7717c04c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 47.01098901098902,  47.05494505494508,  47.09890109890111,\n",
       "        47.14285714285717,   47.1868131868132, 47.230769230769255,\n",
       "        47.27472527472529,  47.31868131868134,  47.36263736263737,\n",
       "        47.40659340659343,\n",
       "       ...\n",
       "        54.57142857142859,  54.61538461538461,  54.65934065934067,\n",
       "         54.7032967032967,  54.74725274725276,  54.79120879120879,\n",
       "       54.835164835164846, 54.879120879120904, 54.923076923076934,\n",
       "        54.96703296703299],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=182))</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-9f2dd67f-a9aa-4112-86a4-a2f907037766' class='xr-index-data-in' type='checkbox'/><label for='index-9f2dd67f-a9aa-4112-86a4-a2f907037766' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 5.009765625000001,       5.0537109375,         5.09765625,\n",
       "             5.1416015625,        5.185546875,       5.2294921875,\n",
       "                5.2734375,       5.3173828125,        5.361328125,\n",
       "             5.4052734375,\n",
       "       ...\n",
       "            15.6005859375, 15.644531250000002,      15.6884765625,\n",
       "             15.732421875, 15.776367187499998,         15.8203125,\n",
       "       15.864257812500002,       15.908203125, 15.952148437500002,\n",
       "              15.99609375],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=251))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5f2ceba5-17a4-463b-b16a-ac471afdf9e9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5f2ceba5-17a4-463b-b16a-ac471afdf9e9' 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 't2m' (latitude: 182, longitude: 251)> Size: 183kB\n",
       "array([[ 1.2636374,  1.2636374,  1.3567146, ..., -5.102584 , -5.102584 ,\n",
       "        -5.118713 ],\n",
       "       [ 1.2636374,  1.149727 ,  1.2639735, ..., -5.189445 , -5.189445 ,\n",
       "        -5.207086 ],\n",
       "       [ 1.149727 ,  1.0237204,  1.0237204, ..., -5.189445 , -5.161052 ,\n",
       "        -5.207086 ],\n",
       "       ...,\n",
       "       [ 2.8174255,  2.8174255,  2.8140652, ..., -1.6859541, -1.8778229,\n",
       "        -1.8778229],\n",
       "       [ 2.8140652,  2.8140652,  2.8140652, ..., -1.5508729, -1.4137752,\n",
       "        -1.7242607],\n",
       "       [ 2.8066719,  2.8066719,  2.8066719, ..., -1.4137752, -1.4137752,\n",
       "        -1.5723785]], dtype=float32)\n",
       "Coordinates:\n",
       "    heightAboveGround  float64 8B 2.0\n",
       "  * latitude           (latitude) float64 1kB 47.01 47.05 47.1 ... 54.92 54.97\n",
       "  * longitude          (longitude) float64 2kB 5.01 5.054 5.098 ... 15.95 16.0\n",
       "    step               timedelta64[ns] 8B 00:00:00\n",
       "    surface            float64 8B 0.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t2m_germany_area_selection_monthly_mean = t2m_germany_area_selection.mean(dim=\"time\")\n",
    "t2m_germany_area_selection_monthly_mean"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b7a43c9-9a20-4e79-835e-710124326487",
   "metadata": {},
   "source": [
    "## 3. Visualization\n",
    "Finally, we can plot the monthly mean on a map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0cae4185-312a-474d-8e71-faa72706751e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cf\n",
    "\n",
    "ax = plt.axes(projection=ccrs.Mercator())\n",
    "t2m_germany_area_selection_monthly_mean.plot(ax=ax,transform=ccrs.PlateCarree(),cmap=\"YlOrRd\",vmax=None)  \n",
    "plt.title(\"Mean Surface Temperature, Jan 2028\")\n",
    "ax.coastlines()\n",
    "ax.add_feature(cf.BORDERS)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb4f00e1-b4f2-410a-9aa3-300e1a03ac6b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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