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    "# Accessing and analysing Canadian Surface Reanalysis (CaSR) data in the PAVICS JupyterLab\n",
    "\n",
    "This notebook demonstrates how to access, subset, analyse and visualize Canadian Surface Reanalysis (CaSR) datasets.\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Note</b> \n",
    "    The CaSR v3.2 data hosted on PAVICS has been reformated from the original structure to improve its compatibility with <a href=\"https://docs.xarray.dev/en/stable/\">xarray</a> and <a href=\"https://www.dask.org/\">dask</a>. \n",
    "Key changes include:\n",
    "<ul>\n",
    "    <li> Renamed variable and converted units to match <a href=\"https://wcrp-cmip.org/cmip-model-and-experiment-documentation/\">CMIP</a> conventions;</li>\n",
    "    <li> Added the original variable name to variable attribute \"original_variable\";</li>\n",
    "    <li> Modified NetCDF data structure (chunking) to improve performance for typical climate services workflows;</li>\n",
    "    <li> Creation of a daily dataset.</li>\n",
    "</ul>\n",
    "</div>\n",
    "\n",
    "The datasets are stored on the [PAVICS THREDDS server](https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/catalog/birdhouse/eccc/CaSR_v32/catalog.html). You'll find data at both hourly and daily frequencies. Hourly data are stored in individual files for each month and variable. Daily data are stored in files holding three years of data for each variable. \n",
    "\n",
    "For convenience, we provide [*NcML aggregations*](https://docs.unidata.ucar.edu/netcdf-java/current/userguide/ncml_overview.html), that is, single links for the [hourly](https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/catalog/datasets/reanalyses/catalog.html?dataset=datasets/reanalyses/1hr_NAM_GovCan_CaSR_v32_198001-202412.ncml) and [daily](https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/catalog/datasets/reanalyses/catalog.html?dataset=datasets/reanalyses/day_NAM_GovCan_CaSR_v32_1980-2024.ncml) datasets, combining multiple netCDF files (~500 files per variable for hourly data) into a single virtual dataset. The following demonstration uses those NcML aggregations.\n",
    "\n",
    "## Data access\n",
    "\n",
    "Here we start by opening the CaSR daily dataset using OPeNDAP, a data streaming protocol. The dataset holds temperature, precipitation, humidity, and pressure variables. See the attributes of each variable for more details.\n",
    "\n",
    "It's critical here to specify a chunking pattern that makes sense for the analysis to follow. This is important for a couple of reasons. The first is that specifying chunks automatically triggers xarray to use dask, meaning that streaming and compute operations will be split into smaller, digestible chunks. This is need to distribute jobs across workers and threads, but it is also critical because OPeNDAP has limits on the volume of data that can be transferred in a query. Without chunking, chances are that many requests would reach that limit and raise an error."
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2TB\n",
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       "  * rlon          (rlon) float32 3kB -35.4 -35.31 -35.22 ... 27.87 27.96 28.05\n",
       "  * time          (time) datetime64[ns] 131kB 1980-01-01 ... 2024-12-31\n",
       "    rotated_pole  int32 4B ...\n",
       "    lat           (rlat, rlon) float32 2MB dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;\n",
       "    lon           (rlat, rlon) float32 2MB dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;\n",
       "Data variables: (12/49)\n",
       "    orog          (rlat, rlon) float32 2MB dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;\n",
       "    sftgif        (rlat, rlon) float32 2MB dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;\n",
       "    sftlf         (rlat, rlon) float32 2MB dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;\n",
       "    sftlkf        (rlat, rlon) float32 2MB dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;\n",
       "    sftof         (rlat, rlon) float32 2MB dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;\n",
       "    20mWind       (time, rlat, rlon) float32 36GB dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;\n",
       "    ...            ...\n",
       "    tamax         (time, rlat, rlon) float32 36GB dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;\n",
       "    tamin         (time, rlat, rlon) float32 36GB dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;\n",
       "    prfrmod       (time, rlat, rlon) float32 36GB dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;\n",
       "    prramod       (time, rlat, rlon) float32 36GB dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;\n",
       "    prrpmod       (time, rlat, rlon) float32 36GB dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;\n",
       "    prsnmod       (time, rlat, rlon) float32 36GB dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;\n",
       "Attributes: (12/30)\n",
       "    Conventions:             CF-1.8\n",
       "    Remarks:                 Original variable names are following the conven...\n",
       "    contact:                 \n",
       "    doi:                     https://doi.org/10.5194/hess-25-4917-2021\n",
       "    domain:                  NAM\n",
       "    frequency:               day\n",
       "    ...                      ...\n",
       "    history:                 2025-12-16 11:21:02.543093: Created a copy of Ca...\n",
       "    description:             Original data source: https://hpfx.collab.scienc...\n",
       "    institute:               Environment and Climate Change Canada\n",
       "    institute_id:            ECCC\n",
       "    dataset_description:     https://hpfx.collab.science.gc.ca/~scar700/rcas-...\n",
       "    dataset_id:              CaSRv3.2</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-25676a28-f666-481b-9b4f-3c471fc51ec1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-25676a28-f666-481b-9b4f-3c471fc51ec1' 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'>rlat</span>: 778</li><li><span class='xr-has-index'>rlon</span>: 706</li><li><span class='xr-has-index'>time</span>: 16437</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-816a6aa1-3a3c-42c4-902c-8bd90e65050c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-816a6aa1-3a3c-42c4-902c-8bd90e65050c' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rlat</span></div><div class='xr-var-dims'>(rlat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-44.1 -44.01 -43.92 ... 25.74 25.83</div><input id='attrs-71351231-fcfd-46f3-bbb4-29a4e3eda6f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71351231-fcfd-46f3-bbb4-29a4e3eda6f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4fd7375-c3ce-42c6-9cb4-b891016f098e' class='xr-var-data-in' type='checkbox'><label for='data-a4fd7375-c3ce-42c6-9cb4-b891016f098e' title='Show/Hide data repr'><svg 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 in rotated pole grid</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-44.100002, -44.010002, -43.920002, ...,  25.650002,  25.740002,\n",
       "        25.830002], shape=(778,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rlon</span></div><div class='xr-var-dims'>(rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-35.4 -35.31 -35.22 ... 27.96 28.05</div><input id='attrs-15d43080-fe16-4d7a-acc5-e9ff57f9b52a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15d43080-fe16-4d7a-acc5-e9ff57f9b52a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc9b28fc-05d3-443d-8d5d-d9530a769da0' class='xr-var-data-in' type='checkbox'><label for='data-dc9b28fc-05d3-443d-8d5d-d9530a769da0' title='Show/Hide data repr'><svg 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 in rotated pole grid</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-35.397217, -35.30722 , -35.217224, ...,  27.872787,  27.962784,\n",
       "        28.05278 ], shape=(706,), dtype=float32)</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'>1980-01-01 ... 2024-12-31</div><input id='attrs-f9dda6c9-4800-40c5-b777-99013a6baf7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9dda6c9-4800-40c5-b777-99013a6baf7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3318ea80-89ea-499f-80a0-80dfc493312a' class='xr-var-data-in' type='checkbox'><label for='data-3318ea80-89ea-499f-80a0-80dfc493312a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-01T00:00:00.000000000&#x27;, &#x27;1980-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-03T00:00:00.000000000&#x27;, ..., &#x27;2024-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2024-12-30T00:00:00.000000000&#x27;, &#x27;2024-12-31T00:00:00.000000000&#x27;],\n",
       "      shape=(16437,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rotated_pole</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-74d7a6a0-6e7a-4fd0-a140-054ff79d911d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74d7a6a0-6e7a-4fd0-a140-054ff79d911d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c89cde3f-c18c-45cc-8921-2bf675e2a279' class='xr-var-data-in' type='checkbox'><label for='data-c89cde3f-c18c-45cc-8921-2bf675e2a279' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>north_pole_grid_longitude :</span></dt><dd>0.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>31.758312454493154</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>87.59703130293302</dd><dt><span>earth_radius :</span></dt><dd>6370997.0</dd><dt><span>grid_mapping_name :</span></dt><dd>rotated_latitude_longitude</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;</div><input id='attrs-06d63fd9-3aaa-452d-9777-4693450c6c6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06d63fd9-3aaa-452d-9777-4693450c6c6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff979262-d167-4450-9188-349fef1d2f0a' class='xr-var-data-in' type='checkbox'><label for='data-ff979262-d167-4450-9188-349fef1d2f0a' title='Show/Hide data repr'><svg 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>_CoordinateAxisType :</span></dt><dd>Lat</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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.10 MiB </td>\n",
       "                        <td> 9.77 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (778, 706) </td>\n",
       "                        <td> (50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 240 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><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;</div><input id='attrs-7afe6985-4a07-42c2-a885-6bcf821bc6c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7afe6985-4a07-42c2-a885-6bcf821bc6c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8215e4c-daef-466a-93c6-fc11db985f50' class='xr-var-data-in' type='checkbox'><label for='data-f8215e4c-daef-466a-93c6-fc11db985f50' title='Show/Hide data repr'><svg 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>_CoordinateAxisType :</span></dt><dd>Lon</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'><table>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-dabd201d-5b1b-4b77-aef2-40688c80e74b' class='xr-section-summary-in' type='checkbox'  ><label for='section-dabd201d-5b1b-4b77-aef2-40688c80e74b' class='xr-section-summary' >Data variables: <span>(49)</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>orog</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;</div><input id='attrs-ecd398be-f4de-4347-9115-0f98016e7657' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecd398be-f4de-4347-9115-0f98016e7657' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3732d8b-2dd8-47dd-8443-052d417503c9' class='xr-var-data-in' type='checkbox'><label for='data-f3732d8b-2dd8-47dd-8443-052d417503c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface Altitude</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>surface_altitude</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:01:41] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.10 MiB </td>\n",
       "                        <td> 9.77 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (778, 706) </td>\n",
       "                        <td> (50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 240 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><li class='xr-var-item'><div class='xr-var-name'><span>sftgif</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;</div><input id='attrs-32c0aa97-d15d-49e8-a542-fc0995d1eca0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32c0aa97-d15d-49e8-a542-fc0995d1eca0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-478a89e4-5309-424b-99c7-c9edcdaefef3' class='xr-var-data-in' type='checkbox'><label for='data-478a89e4-5309-424b-99c7-c9edcdaefef3' title='Show/Hide data repr'><svg 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>Land Ice Area Fraction</dd><dt><span>description :</span></dt><dd>Fraction of grid cell covered by land ice (ice sheet, ice shelf, ice cap, glacier)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>land_ice_area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:03:58] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.10 MiB </td>\n",
       "                        <td> 9.77 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (778, 706) </td>\n",
       "                        <td> (50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 240 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><li class='xr-var-item'><div class='xr-var-name'><span>sftlf</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;</div><input id='attrs-0674adc6-c6f8-4047-952b-81d1887cff37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0674adc6-c6f8-4047-952b-81d1887cff37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d318e5a8-0a94-4f64-a605-51b07c6e715d' class='xr-var-data-in' type='checkbox'><label for='data-d318e5a8-0a94-4f64-a605-51b07c6e715d' title='Show/Hide data repr'><svg 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>Land Area Fraction including Lakes</dd><dt><span>description :</span></dt><dd>Fraction of the Grid Cell Occupied by Land (Including Lakes)</dd><dt><span>standard_name :</span></dt><dd>land_area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:04:03] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 2.10 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
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       "                        <td> (50, 50) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 240 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftlkf</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;</div><input id='attrs-3dfde13e-b89c-4d2b-9f64-7b33aa5c408c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3dfde13e-b89c-4d2b-9f64-7b33aa5c408c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d91eef53-0730-4e25-8c10-ee5052b39c6e' class='xr-var-data-in' type='checkbox'><label for='data-d91eef53-0730-4e25-8c10-ee5052b39c6e' title='Show/Hide data repr'><svg 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>Lake Area Fraction</dd><dt><span>area_type :</span></dt><dd>lake_and_inland_sea</dd><dt><span>description :</span></dt><dd>Fraction of horizontal land grid cell area occupied by lake.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:04:06] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.10 MiB </td>\n",
       "                        <td> 9.77 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (778, 706) </td>\n",
       "                        <td> (50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 240 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.10 MiB </td>\n",
       "                        <td> 9.77 kiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (50, 50) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 240 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>20mWinddir</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-b14b59f4-04fa-438a-ad28-3d96106376a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b14b59f4-04fa-438a-ad28-3d96106376a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8864d6a-43ac-4a4c-b68e-7e37bdf2780e' class='xr-var-data-in' type='checkbox'><label for='data-a8864d6a-43ac-4a4c-b68e-7e37bdf2780e' title='Show/Hide data repr'><svg 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>Meteorological Wind Direction (20m)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_WDC_09975</dd><dt><span>standard_name :</span></dt><dd>wind_from_direction</dd><dt><span>units :</span></dt><dd>degree</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 10:04:05] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Bytes </th>\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>cfia</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-012a893c-6dc2-470c-a6ad-0d3b3566ff21' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-012a893c-6dc2-470c-a6ad-0d3b3566ff21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3ec906f-7b91-4d0b-9272-e178f064ff55' class='xr-var-data-in' type='checkbox'><label for='data-a3ec906f-7b91-4d0b-9272-e178f064ff55' title='Show/Hide data repr'><svg 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>Analysis: Confidence Index of CaPA 24h Analysis at surface</dd><dt><span>_standard_name :</span></dt><dd></dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>A_CFIA_SFC</dd><dt><span>standard_name :</span></dt><dd>Confidence Index of CaPA 24h Analysis</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 10:19:21] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hur</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-7b3e79bd-7722-4266-bdb1-8652deddbb97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b3e79bd-7722-4266-bdb1-8652deddbb97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e1a6853-ebf8-42a0-87ea-2db61f1f1670' class='xr-var-data-in' type='checkbox'><label for='data-9e1a6853-ebf8-42a0-87ea-2db61f1f1670' title='Show/Hide data repr'><svg 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>20 metre Relative Humidity (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HR_09975</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 10:26:22] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                        <th> Shape </th>\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>hurmax</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-0bdcf28b-e376-4966-8995-3c554493a475' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bdcf28b-e376-4966-8995-3c554493a475' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb0b09a9-a491-439a-896e-d05e4e392376' class='xr-var-data-in' type='checkbox'><label for='data-bb0b09a9-a491-439a-896e-d05e4e392376' title='Show/Hide data repr'><svg 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>20 metre Relative Humidity (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: maximum (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HR_09975</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 10:30:26] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "            <table style=\"border-collapse: collapse;\">\n",
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       "                        <td> </td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1461, 50, 50) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurmin</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-abb7f3a7-689a-4060-a92c-7fa94c95fa02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abb7f3a7-689a-4060-a92c-7fa94c95fa02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f26a3d9a-c16d-4d74-96af-2a75b3df07d2' class='xr-var-data-in' type='checkbox'><label for='data-f26a3d9a-c16d-4d74-96af-2a75b3df07d2' title='Show/Hide data repr'><svg 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>20 metre Relative Humidity (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: minimum (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HR_09975</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:00:29] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-137ecb20-da67-45ea-ba48-8c19fa8aa341' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-137ecb20-da67-45ea-ba48-8c19fa8aa341' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36bbef46-17ce-4eb4-b581-bdae79e976d0' class='xr-var-data-in' type='checkbox'><label for='data-36bbef46-17ce-4eb4-b581-bdae79e976d0' title='Show/Hide data repr'><svg 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>Near-Surface Relative Humidity (1.5m)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HR_1.5m</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:04:47] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hursmax</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-c1a42341-9fed-44bc-9c7f-cda3e375d0d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1a42341-9fed-44bc-9c7f-cda3e375d0d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d07af73-19ae-4b21-9905-7f029d6e95cf' class='xr-var-data-in' type='checkbox'><label for='data-8d07af73-19ae-4b21-9905-7f029d6e95cf' title='Show/Hide data repr'><svg 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>Near-Surface Relative Humidity (1.5m)</dd><dt><span>cell_methods :</span></dt><dd>time: maximum (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HR_1.5m</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:08:49] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hursmin</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-34427004-1af3-4463-b73e-b05c83138a13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34427004-1af3-4463-b73e-b05c83138a13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd9e3d1a-a812-401e-ba44-a7ccfa5786a5' class='xr-var-data-in' type='checkbox'><label for='data-cd9e3d1a-a812-401e-ba44-a7ccfa5786a5' title='Show/Hide data repr'><svg 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>Near-Surface Relative Humidity (1.5m)</dd><dt><span>cell_methods :</span></dt><dd>time: minimum (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HR_1.5m</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:13:01] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hus</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-935a55e6-25f8-43c6-85d1-579b58fc7cb5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-935a55e6-25f8-43c6-85d1-579b58fc7cb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40cbcdae-5137-4584-9e3b-92b21ac4d6fd' class='xr-var-data-in' type='checkbox'><label for='data-40cbcdae-5137-4584-9e3b-92b21ac4d6fd' title='Show/Hide data repr'><svg 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>20 metre Specific Humidity (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HU_09975</dd><dt><span>standard_name :</span></dt><dd>specific_humidity</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:17:50] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>huss</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-825220d3-1927-4bd3-90b1-53a19b485b6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-825220d3-1927-4bd3-90b1-53a19b485b6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0be9c0fc-7aea-445d-9cd4-601609e98c45' class='xr-var-data-in' type='checkbox'><label for='data-0be9c0fc-7aea-445d-9cd4-601609e98c45' title='Show/Hide data repr'><svg 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>Near-Surface Specific Humidity (1.5m)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HU_1.5m</dd><dt><span>standard_name :</span></dt><dd>specific_humidity</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:22:42] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-907a969c-ae41-43d5-9137-f1bc472189d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-907a969c-ae41-43d5-9137-f1bc472189d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51573681-2dd2-434b-90c3-b0f290787cac' class='xr-var-data-in' type='checkbox'><label for='data-51573681-2dd2-434b-90c3-b0f290787cac' title='Show/Hide data repr'><svg 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>Precipitation</dd><dt><span>_corrected_standard_name :</span></dt><dd>lwe_thickness_of_precipitation_amount</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Precipitation using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field was produced by CaPA to improve its representation of observations. This field is different from the sum of prsnmod, prramod, prfrmod and prrpmod, which come directly from the model and which are coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>A_PR0_SFC</dd><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-04 09:51:05] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prmod</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-17d88500-cdea-42cd-ad05-5ae193418309' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17d88500-cdea-42cd-ad05-5ae193418309' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fae935d-791d-4288-a2cb-be90c6e95e5c' class='xr-var-data-in' type='checkbox'><label for='data-1fae935d-791d-4288-a2cb-be90c6e95e5c' title='Show/Hide data repr'><svg 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>Precipitation</dd><dt><span>_corrected_standard_name :</span></dt><dd>lwe_thickness_of_precipitation_amount</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Precipitation using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field differs from the &#x27;pr&#x27; variable. It is the model background field subsequently used by CaPA to produce &#x27;pr&#x27;.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_PR0_SFC</dd><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:33:06] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ps</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-f24f85a2-756f-4fb1-bf1e-c3d841dd429c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f24f85a2-756f-4fb1-bf1e-c3d841dd429c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb0955c7-39d5-4c5a-8327-0ddab15ef774' class='xr-var-data-in' type='checkbox'><label for='data-eb0955c7-39d5-4c5a-8327-0ddab15ef774' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface Air Pressure</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_P0_SFC</dd><dt><span>standard_name :</span></dt><dd>surface_air_pressure</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:42:45] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rsds</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-d3f9c62c-080b-4dfa-83a3-d8269588d787' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3f9c62c-080b-4dfa-83a3-d8269588d787' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-564f738d-65a4-407d-a776-868f8e09c419' class='xr-var-data-in' type='checkbox'><label for='data-564f738d-65a4-407d-a776-868f8e09c419' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface Downwelling Shortwave Radiation</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_FB_SFC</dd><dt><span>standard_name :</span></dt><dd>surface_downwelling_shortwave_flux_in_air</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:53:03] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sfcWind</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-2f0942eb-37c3-48fd-9fe5-29a241f0dcbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f0942eb-37c3-48fd-9fe5-29a241f0dcbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e2c2e5a-a5a9-4425-a2b1-0ed0049b6ac3' class='xr-var-data-in' type='checkbox'><label for='data-9e2c2e5a-a5a9-4425-a2b1-0ed0049b6ac3' title='Show/Hide data repr'><svg 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>Near-Surface Wind Speed (10m)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_UVC_10m</dd><dt><span>standard_name :</span></dt><dd>wind_speed</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:57:51] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sfcWindmax</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-7f60910e-4677-4059-9bc3-72e537c07554' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f60910e-4677-4059-9bc3-72e537c07554' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b045c7b2-96c6-4fe0-a93f-68886f142102' class='xr-var-data-in' type='checkbox'><label for='data-b045c7b2-96c6-4fe0-a93f-68886f142102' title='Show/Hide data repr'><svg 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>Near-Surface Wind Speed (10m)</dd><dt><span>cell_methods :</span></dt><dd>time: maximum (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_UVC_10m</dd><dt><span>standard_name :</span></dt><dd>wind_speed</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:03:08] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "        <td>\n",
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       "                <tbody>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tasmin</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-314f27fa-515e-4dcf-ac4e-7dc0cdd5b86b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-314f27fa-515e-4dcf-ac4e-7dc0cdd5b86b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69da4a04-4f53-4af1-bec3-4b0e91223d0c' class='xr-var-data-in' type='checkbox'><label for='data-69da4a04-4f53-4af1-bec3-4b0e91223d0c' title='Show/Hide data repr'><svg 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>1.5 metre temperature</dd><dt><span>cell_methods :</span></dt><dd>time: minimum (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TT_1.5m</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:17:37] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tdp</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-0f086c0e-db07-4419-8c41-0cee8b51d117' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f086c0e-db07-4419-8c41-0cee8b51d117' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f21a110b-16b3-4b1a-bcc2-04f5227b94c4' class='xr-var-data-in' type='checkbox'><label for='data-f21a110b-16b3-4b1a-bcc2-04f5227b94c4' title='Show/Hide data repr'><svg 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>20 metre dewpoint temperature (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TD_09975</dd><dt><span>standard_name :</span></dt><dd>dew_point_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:21:20] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tdpmax</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-f09bd34e-84da-4dd1-a7ec-c98bc0bd4713' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f09bd34e-84da-4dd1-a7ec-c98bc0bd4713' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-281324f5-300c-426a-a0a6-268a77647d67' class='xr-var-data-in' type='checkbox'><label for='data-281324f5-300c-426a-a0a6-268a77647d67' title='Show/Hide data repr'><svg 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>20 metre dewpoint temperature (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: maximum (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TD_09975</dd><dt><span>standard_name :</span></dt><dd>dew_point_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:25:18] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tdpmin</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-22abb4df-75c6-4c44-9820-cb08c8cbee23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22abb4df-75c6-4c44-9820-cb08c8cbee23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-341f7def-c8c4-4f9b-b7f1-176b297825e5' class='xr-var-data-in' type='checkbox'><label for='data-341f7def-c8c4-4f9b-b7f1-176b297825e5' title='Show/Hide data repr'><svg 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>20 metre dewpoint temperature (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: minimum (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TD_09975</dd><dt><span>standard_name :</span></dt><dd>dew_point_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:28:42] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Bytes </th>\n",
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       "                        <td> 33.63 GiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tdpsmax</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-49afd536-55f5-4d09-9315-bb29a18d2dd5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49afd536-55f5-4d09-9315-bb29a18d2dd5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-770cc949-1ec2-46bb-a5f8-57d52f355462' class='xr-var-data-in' type='checkbox'><label for='data-770cc949-1ec2-46bb-a5f8-57d52f355462' title='Show/Hide data repr'><svg 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>1.5 metre dewpoint temperature</dd><dt><span>cell_methods :</span></dt><dd>time: maximum (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TD_1.5m</dd><dt><span>standard_name :</span></dt><dd>dew_point_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:35:53] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tdpsmin</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-c554d988-8d0c-49b4-a1c8-45f7cc295899' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c554d988-8d0c-49b4-a1c8-45f7cc295899' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ba13a1e-3cc3-4866-b21e-7eb4b41d6bb5' class='xr-var-data-in' type='checkbox'><label for='data-0ba13a1e-3cc3-4866-b21e-7eb4b41d6bb5' title='Show/Hide data repr'><svg 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>1.5 metre dewpoint temperature</dd><dt><span>cell_methods :</span></dt><dd>time: minimum (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TD_1.5m</dd><dt><span>standard_name :</span></dt><dd>dew_point_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:39:30] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ua</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-157787dd-882f-4e86-82af-35cc4f6618f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-157787dd-882f-4e86-82af-35cc4f6618f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-950d8a45-52c6-41d1-b6a2-2690c299b7ec' class='xr-var-data-in' type='checkbox'><label for='data-950d8a45-52c6-41d1-b6a2-2690c299b7ec' title='Show/Hide data repr'><svg 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>Eastward Wind (20m). Height is approximate, see description.</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_UUC_09975</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:43:04] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    \n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
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       "    <tr>\n",
       "        <td>\n",
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       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>va</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-7490bad2-ef39-4caa-9a0c-727e49d81779' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7490bad2-ef39-4caa-9a0c-727e49d81779' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-289cb5f6-24f7-468d-bd27-2f367ffd8e98' class='xr-var-data-in' type='checkbox'><label for='data-289cb5f6-24f7-468d-bd27-2f367ffd8e98' title='Show/Hide data repr'><svg 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>Northward Wind (20m). Height is approximate, see description.</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
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       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>winddir</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-60baf536-00c9-4647-9ae1-361dbbd457cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60baf536-00c9-4647-9ae1-361dbbd457cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb735e09-a1be-4521-bdc2-790e32bd5432' class='xr-var-data-in' type='checkbox'><label for='data-cb735e09-a1be-4521-bdc2-790e32bd5432' title='Show/Hide data repr'><svg 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>Near-Surface Meteorological Wind Direction (10m)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_WDC_10m</dd><dt><span>standard_name :</span></dt><dd>wind_from_direction</dd><dt><span>units :</span></dt><dd>degree</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 13:04:40] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zcrd09975</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-7dd19088-1f42-482e-8714-7b638ac35443' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7dd19088-1f42-482e-8714-7b638ac35443' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf4b1a1d-3b81-4467-a810-019baaa439d9' class='xr-var-data-in' type='checkbox'><label for='data-cf4b1a1d-3b81-4467-a810-019baaa439d9' title='Show/Hide data repr'><svg 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>Model vertical grid coordinate</dd><dt><span>_standard_name :</span></dt><dd></dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>Corresponding coordinate (09975) on the GEM Charney-Phillips vertical grid (https://doi.org/10.1175/MWR-D-13-00255.1). The height of variables with level 0XXXX can be inferred zcrd0XXXX - zcrd10000.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_GZ_09975</dd><dt><span>standard_name :</span></dt><dd>Geopotential height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 13:09:30] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                <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> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1461, 50, 50) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zcrd10000</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-a7d012f3-ccf7-4321-aba2-41ee564aa961' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7d012f3-ccf7-4321-aba2-41ee564aa961' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b528a52-8a65-463d-954c-297abd361fd6' class='xr-var-data-in' type='checkbox'><label for='data-8b528a52-8a65-463d-954c-297abd361fd6' title='Show/Hide data repr'><svg 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>Model vertical grid coordinate at the surface</dd><dt><span>_standard_name :</span></dt><dd></dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>Surface coordinate (10000) on the GEM Charney-Phillips vertical grid (https://doi.org/10.1175/MWR-D-13-00255.1). The height of variables with level 0XXXX can be inferred zcrd0XXXX - zcrd10000.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_GZ_SFC</dd><dt><span>standard_name :</span></dt><dd>Geopotential height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 13:13:20] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</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> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 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",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1461, 50, 50) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snw</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-ac993664-79a0-4793-b7d0-09ec8e72dd4a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac993664-79a0-4793-b7d0-09ec8e72dd4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea3a4b93-b70d-43be-b151-01ab8a6157d4' class='xr-var-data-in' type='checkbox'><label for='data-ea3a4b93-b70d-43be-b151-01ab8a6157d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface Snow Amount</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_SWE_LAND</dd><dt><span>standard_name :</span></dt><dd>surface_snow_amount</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:09:24] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>cell_methods :</span></dt><dd>time: point area: mean where land</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <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> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 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><li class='xr-var-item'><div class='xr-var-name'><span>ta</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-7d662517-2488-40de-8616-fe7bf05cb17e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d662517-2488-40de-8616-fe7bf05cb17e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e08564fc-9654-4caf-a536-f46a3c01d7e2' class='xr-var-data-in' type='checkbox'><label for='data-e08564fc-9654-4caf-a536-f46a3c01d7e2' title='Show/Hide data repr'><svg 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>20 metre Air Temperature (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>Corresponding coordinate (09975) on the GEM Charney-Phillips vertical grid (https://doi.org/10.1175/MWR-D-13-00255.1). The height of variables with level 0XXXX can be inferred zcrd0XXXX - zcrd10000.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TT_09975</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:08:05] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tamax</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-8c83477a-cb88-4f5a-9ed3-233ae4e6e1e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c83477a-cb88-4f5a-9ed3-233ae4e6e1e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ede4b0d-a50e-466b-92f7-25d7b0849ab2' class='xr-var-data-in' type='checkbox'><label for='data-4ede4b0d-a50e-466b-92f7-25d7b0849ab2' title='Show/Hide data repr'><svg 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>20 metre Air Temperature (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: maximum (interval: 1 day)</dd><dt><span>description :</span></dt><dd>Corresponding coordinate (09975) on the GEM Charney-Phillips vertical grid (https://doi.org/10.1175/MWR-D-13-00255.1). The height of variables with level 0XXXX can be inferred zcrd0XXXX - zcrd10000.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TT_09975</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:11:19] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tamin</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-d8573a4e-ced6-4ff0-8da6-19e9deb2c2ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8573a4e-ced6-4ff0-8da6-19e9deb2c2ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a15d77d-511d-46d8-9047-455397a210fa' class='xr-var-data-in' type='checkbox'><label for='data-4a15d77d-511d-46d8-9047-455397a210fa' title='Show/Hide data repr'><svg 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>20 metre Air Temperature (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: minimum (interval: 1 day)</dd><dt><span>description :</span></dt><dd>Corresponding coordinate (09975) on the GEM Charney-Phillips vertical grid (https://doi.org/10.1175/MWR-D-13-00255.1). The height of variables with level 0XXXX can be inferred zcrd0XXXX - zcrd10000.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TT_09975</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:14:39] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <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> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prfrmod</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-1ab41b9b-71b3-4427-96d4-4e888d00388d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ab41b9b-71b3-4427-96d4-4e888d00388d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff8140cc-4e12-4fc7-a817-2c8328a9f131' class='xr-var-data-in' type='checkbox'><label for='data-ff8140cc-4e12-4fc7-a817-2c8328a9f131' title='Show/Hide data repr'><svg 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>Freezing Rain</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Freezing Rain using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field comes from the model background and is coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_FR0_SFC</dd><dt><span>standard_name :</span></dt><dd>freezing_rain</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-03 15:08:12] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <td> 33.63 GiB </td>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prramod</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-0d08ea54-4dba-434b-999e-e378e2b7c9ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d08ea54-4dba-434b-999e-e378e2b7c9ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d95d9a62-ba90-4c29-897b-08dcd4cd3994' class='xr-var-data-in' type='checkbox'><label for='data-d95d9a62-ba90-4c29-897b-08dcd4cd3994' title='Show/Hide data repr'><svg 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>Liquid Precipitation</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Liquid Precipitation using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field comes from the model background and is coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_RN0_SFC</dd><dt><span>standard_name :</span></dt><dd>rainfall_flux</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-03 15:09:36] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</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> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prrpmod</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-c67f6223-6844-47e3-9831-ce9bc92ba72a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c67f6223-6844-47e3-9831-ce9bc92ba72a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f9a5aea-ba95-4296-891f-d19763cbcf61' class='xr-var-data-in' type='checkbox'><label for='data-2f9a5aea-ba95-4296-891f-d19763cbcf61' title='Show/Hide data repr'><svg 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>Refrozen Rain</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Refrozen Rain using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field comes from the model background and is coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_PE0_SFC</dd><dt><span>standard_name :</span></dt><dd>refrozen_rain</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-03 15:11:26] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
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       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2880 chunks in 2 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prsnmod</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-d8737d32-b069-43da-81df-433f795cae74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8737d32-b069-43da-81df-433f795cae74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-851ea661-667e-401d-9300-3fdb014a8f03' class='xr-var-data-in' type='checkbox'><label for='data-851ea661-667e-401d-9300-3fdb014a8f03' title='Show/Hide data repr'><svg 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>Snowfall Flux</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Snow amount using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field comes from the model background and is coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_SN0_SFC</dd><dt><span>standard_name :</span></dt><dd>snowfall_flux</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-03 15:11:51] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 33.63 GiB </td>\n",
       "                        <td> 13.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437, 778, 706) </td>\n",
       "                        <td> (1461, 50, 50) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-dbc33953-1434-4090-bfa5-cc7018361881' class='xr-section-summary-in' type='checkbox'  ><label for='section-dbc33953-1434-4090-bfa5-cc7018361881' class='xr-section-summary' >Attributes: <span>(30)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>Remarks :</span></dt><dd>Original variable names are following the convention &lt;Product&gt;_&lt;Type:A=Analysis,P=Prediction&gt;_&lt;ECCC name&gt;_&lt;Level/Tile/Category&gt;. Variables with level &#x27;10000&#x27; are at surface level. The height [m] of variables with level &#x27;0XXXX&#x27; needs to be inferrred using the corresponding fields of geopotential height (GZ_0XXXX-GZ_10000). The variables UUC, VVC, UVC, and WDC are not modelled but inferred from UU and VV for convenience of the users. Precipitation (PR) is reported as 6-hr accumulations for CaPA_fine and CaPA_coarse. Precipitation (PR) are accumulations since beginning of the forecast for GEPS, GDPS, REPS, RDPS, HRDPS, and CaLDAS. The re-analysis product CaSR_v3.2 contains two variables for precipitation: &#x27;CaSR_v3.2_P_PR0_SFC&#x27; is the model precipitation (trial field used by CaPA) and &#x27;CaSR_v3.2_A_PR0_SFC&#x27; is precipitations adjusted with CaPA 24h precipitation (as in &#x27;RDRS_P_PR0_SFC&#x27;). Please be aware that the baseflow &#x27;O1&#x27; of the current version of WCPS is not reliable during the spring melt period.</dd><dt><span>contact :</span></dt><dd></dd><dt><span>doi :</span></dt><dd>https://doi.org/10.5194/hess-25-4917-2021</dd><dt><span>domain :</span></dt><dd>NAM</dd><dt><span>frequency :</span></dt><dd>day</dd><dt><span>institution :</span></dt><dd>GovCan</dd><dt><span>license :</span></dt><dd>https://open.canada.ca/en/open-government-licence-canada</dd><dt><span>miranda_version :</span></dt><dd>0.6.0-dev.8</dd><dt><span>organisation :</span></dt><dd>ECCC</dd><dt><span>prefix :</span></dt><dd>CaSR_v3.2_</dd><dt><span>processing_level :</span></dt><dd>raw</dd><dt><span>project :</span></dt><dd>casr-v32</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>source :</span></dt><dd>CaSR</dd><dt><span>table_date :</span></dt><dd>2025-02-13</dd><dt><span>table_id :</span></dt><dd>eccc</dd><dt><span>title :</span></dt><dd>Canadian Surface Reanalysis (CaSR v3.2) : daily</dd><dt><span>type :</span></dt><dd>reanalysis</dd><dt><span>version :</span></dt><dd>v3.2</dd><dt><span>intake_esm_vars :</span></dt><dd>orog</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>GovCan_CaSR_NAM.NAM.raw.fx</dd><dt><span>license_type :</span></dt><dd>permissive</dd><dt><span>format :</span></dt><dd>netcdf</dd><dt><span>history :</span></dt><dd>2025-12-16 11:21:02.543093: Created a copy of CaSR v3.1 with lat/lon values from CaSR v3.2. 2025-06-13 13:09:22.368470:Created from the Gem_geophy.fst_706x778 file provided by (ECCC).</dd><dt><span>description :</span></dt><dd>Original data source: https://hpfx.collab.science.gc.ca/~scar700/rcas-casr/</dd><dt><span>institute :</span></dt><dd>Environment and Climate Change Canada</dd><dt><span>institute_id :</span></dt><dd>ECCC</dd><dt><span>dataset_description :</span></dt><dd>https://hpfx.collab.science.gc.ca/~scar700/rcas-casr/</dd><dt><span>dataset_id :</span></dt><dd>CaSRv3.2</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 2TB\n",
       "Dimensions:       (rlat: 778, rlon: 706, time: 16437)\n",
       "Coordinates:\n",
       "  * rlat          (rlat) float32 3kB -44.1 -44.01 -43.92 ... 25.65 25.74 25.83\n",
       "  * rlon          (rlon) float32 3kB -35.4 -35.31 -35.22 ... 27.87 27.96 28.05\n",
       "  * time          (time) datetime64[ns] 131kB 1980-01-01 ... 2024-12-31\n",
       "    rotated_pole  int32 4B ...\n",
       "    lat           (rlat, rlon) float32 2MB dask.array<chunksize=(50, 50), meta=np.ndarray>\n",
       "    lon           (rlat, rlon) float32 2MB dask.array<chunksize=(50, 50), meta=np.ndarray>\n",
       "Data variables: (12/49)\n",
       "    orog          (rlat, rlon) float32 2MB dask.array<chunksize=(50, 50), meta=np.ndarray>\n",
       "    sftgif        (rlat, rlon) float32 2MB dask.array<chunksize=(50, 50), meta=np.ndarray>\n",
       "    sftlf         (rlat, rlon) float32 2MB dask.array<chunksize=(50, 50), meta=np.ndarray>\n",
       "    sftlkf        (rlat, rlon) float32 2MB dask.array<chunksize=(50, 50), meta=np.ndarray>\n",
       "    sftof         (rlat, rlon) float32 2MB dask.array<chunksize=(50, 50), meta=np.ndarray>\n",
       "    20mWind       (time, rlat, rlon) float32 36GB dask.array<chunksize=(1461, 50, 50), meta=np.ndarray>\n",
       "    ...            ...\n",
       "    tamax         (time, rlat, rlon) float32 36GB dask.array<chunksize=(1461, 50, 50), meta=np.ndarray>\n",
       "    tamin         (time, rlat, rlon) float32 36GB dask.array<chunksize=(1461, 50, 50), meta=np.ndarray>\n",
       "    prfrmod       (time, rlat, rlon) float32 36GB dask.array<chunksize=(1461, 50, 50), meta=np.ndarray>\n",
       "    prramod       (time, rlat, rlon) float32 36GB dask.array<chunksize=(1461, 50, 50), meta=np.ndarray>\n",
       "    prrpmod       (time, rlat, rlon) float32 36GB dask.array<chunksize=(1461, 50, 50), meta=np.ndarray>\n",
       "    prsnmod       (time, rlat, rlon) float32 36GB dask.array<chunksize=(1461, 50, 50), meta=np.ndarray>\n",
       "Attributes: (12/30)\n",
       "    Conventions:             CF-1.8\n",
       "    Remarks:                 Original variable names are following the conven...\n",
       "    contact:                 \n",
       "    doi:                     https://doi.org/10.5194/hess-25-4917-2021\n",
       "    domain:                  NAM\n",
       "    frequency:               day\n",
       "    ...                      ...\n",
       "    history:                 2025-12-16 11:21:02.543093: Created a copy of Ca...\n",
       "    description:             Original data source: https://hpfx.collab.scienc...\n",
       "    institute:               Environment and Climate Change Canada\n",
       "    institute_id:            ECCC\n",
       "    dataset_description:     https://hpfx.collab.science.gc.ca/~scar700/rcas-...\n",
       "    dataset_id:              CaSRv3.2"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import xarray as xr\n",
    "\n",
    "url = \"https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/dodsC/datasets/reanalyses/day_NAM_GovCan_CaSR_v32_1980-2024.ncml\"\n",
    "\n",
    "# Open dataset. For hourly data, we suggest using the following chunking pattern: dict(time=1461, rlon=50, rlat=50)  : 4 year chunks in time dim\n",
    "ds = xr.open_dataset(url, chunks=dict(time=1461, rlon=50, rlat=50))\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2",
   "metadata": {},
   "source": [
    "## Data subsetting\n",
    "\n",
    "We then subset the data for a zone and period of interest, namely eastern Canada for the period 1981-2010, using [clisops subset_bbox](https://clisops.readthedocs.io/en/latest/api.html#clisops.core.subset.subset_bbox) function. We also demonstrate how to select a single grid cell according to its longitude and latitude using [clisops subset_gridpoint](https://clisops.readthedocs.io/en/latest/api.html#clisops.core.subset.subset_gridpoint). Note that we can't simply use xarray's `sel` method here because dimensions are in rotated pole coordinates. \n",
    "\n",
    "Other, and more advanced subsetting capabilities are also available. For more information and examples, consult those [subsetting examples](https://pavics.ouranos.ca/climate_analysis.html#b). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 45GB\n",
       "Dimensions:       (rlat: 156, rlon: 150, time: 10957)\n",
       "Coordinates: (6)\n",
       "Data variables: (49)\n",
       "Attributes: (12/30)\n",
       "    Conventions:             CF-1.8\n",
       "    Remarks:                 Original variable names are following the conven...\n",
       "    contact:                 \n",
       "    doi:                     https://doi.org/10.5194/hess-25-4917-2021\n",
       "    domain:                  NAM\n",
       "    frequency:               day\n",
       "    ...                      ...\n",
       "    history:                 2025-12-16 11:21:02.543093: Created a copy of Ca...\n",
       "    description:             Original data source: https://hpfx.collab.scienc...\n",
       "    institute:               Environment and Climate Change Canada\n",
       "    institute_id:            ECCC\n",
       "    dataset_description:     https://hpfx.collab.science.gc.ca/~scar700/rcas-...\n",
       "    dataset_id:              CaSRv3.2</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-99bec313-6e4e-403e-a9f8-541b0e10e844' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-99bec313-6e4e-403e-a9f8-541b0e10e844' 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'>rlat</span>: 156</li><li><span class='xr-has-index'>rlon</span>: 150</li><li><span class='xr-has-index'>time</span>: 10957</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-649c5c37-f597-42f9-a5c5-761fe089114e' class='xr-section-summary-in' type='checkbox'  ><label for='section-649c5c37-f597-42f9-a5c5-761fe089114e' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rlat</span></div><div class='xr-var-dims'>(rlat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-11.52 -11.43 -11.34 ... 2.34 2.43</div><input id='attrs-cfb49cc1-cc70-44f1-9e22-98f70b427964' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfb49cc1-cc70-44f1-9e22-98f70b427964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31760add-28d3-4746-81d0-59973513ebea' class='xr-var-data-in' type='checkbox'><label for='data-31760add-28d3-4746-81d0-59973513ebea' title='Show/Hide data repr'><svg 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 in rotated pole grid</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([-11.52    , -11.43    , -11.34    , -11.25    , -11.160001, -11.070001,\n",
       "       -10.98    , -10.89    , -10.8     , -10.71    , -10.620001, -10.530001,\n",
       "       -10.440001, -10.35    , -10.26    , -10.17    , -10.08    ,  -9.990001,\n",
       "        -9.900001,  -9.81    ,  -9.72    ,  -9.63    ,  -9.54    ,  -9.450001,\n",
       "        -9.360001,  -9.27    ,  -9.18    ,  -9.09    ,  -9.      ,  -8.910001,\n",
       "        -8.820001,  -8.73    ,  -8.64    ,  -8.55    ,  -8.46    ,  -8.37    ,\n",
       "        -8.280001,  -8.190001,  -8.1     ,  -8.01    ,  -7.92    ,  -7.83    ,\n",
       "        -7.74    ,  -7.65    ,  -7.56    ,  -7.47    ,  -7.38    ,  -7.29    ,\n",
       "        -7.2     ,  -7.11    ,  -7.02    ,  -6.93    ,  -6.84    ,  -6.75    ,\n",
       "        -6.66    ,  -6.57    ,  -6.48    ,  -6.39    ,  -6.3     ,  -6.21    ,\n",
       "        -6.12    ,  -6.03    ,  -5.94    ,  -5.85    ,  -5.76    ,  -5.67    ,\n",
       "        -5.58    ,  -5.49    ,  -5.4     ,  -5.31    ,  -5.22    ,  -5.13    ,\n",
       "        -5.04    ,  -4.95    ,  -4.86    ,  -4.77    ,  -4.68    ,  -4.59    ,\n",
       "        -4.5     ,  -4.41    ,  -4.32    ,  -4.23    ,  -4.14    ,  -4.05    ,\n",
       "        -3.96    ,  -3.87    ,  -3.78    ,  -3.69    ,  -3.6     ,  -3.51    ,\n",
       "        -3.42    ,  -3.33    ,  -3.24    ,  -3.15    ,  -3.06    ,  -2.97    ,\n",
       "        -2.88    ,  -2.79    ,  -2.7     ,  -2.61    ,  -2.52    ,  -2.43    ,\n",
       "        -2.34    ,  -2.25    ,  -2.16    ,  -2.07    ,  -1.98    ,  -1.89    ,\n",
       "        -1.8     ,  -1.71    ,  -1.62    ,  -1.53    ,  -1.44    ,  -1.35    ,\n",
       "        -1.26    ,  -1.17    ,  -1.08    ,  -0.99    ,  -0.9     ,  -0.81    ,\n",
       "        -0.72    ,  -0.63    ,  -0.54    ,  -0.45    ,  -0.36    ,  -0.27    ,\n",
       "        -0.18    ,  -0.09    ,   0.      ,   0.09    ,   0.18    ,   0.27    ,\n",
       "         0.36    ,   0.45    ,   0.54    ,   0.63    ,   0.72    ,   0.81    ,\n",
       "         0.9     ,   0.99    ,   1.08    ,   1.17    ,   1.26    ,   1.35    ,\n",
       "         1.44    ,   1.53    ,   1.62    ,   1.71    ,   1.8     ,   1.89    ,\n",
       "         1.98    ,   2.07    ,   2.16    ,   2.25    ,   2.34    ,   2.43    ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rlon</span></div><div class='xr-var-dims'>(rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.66 12.75 12.84 ... 25.98 26.07</div><input id='attrs-88ffd697-206f-4f8a-b830-82795853956f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88ffd697-206f-4f8a-b830-82795853956f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b4422f8-7b8f-44d2-915f-67851f957a56' class='xr-var-data-in' type='checkbox'><label for='data-3b4422f8-7b8f-44d2-915f-67851f957a56' title='Show/Hide data repr'><svg 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 in rotated pole grid</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array([12.662781, 12.752777, 12.842789, 12.932785, 13.022781, 13.112778,\n",
       "       13.202789, 13.292786, 13.382782, 13.472778, 13.56279 , 13.652786,\n",
       "       13.742783, 13.832779, 13.922775, 14.012787, 14.102783, 14.19278 ,\n",
       "       14.282776, 14.372787, 14.462784, 14.55278 , 14.642776, 14.732788,\n",
       "       14.822784, 14.912781, 15.002777, 15.092789, 15.182785, 15.272781,\n",
       "       15.362778, 15.452789, 15.542786, 15.632782, 15.722778, 15.81279 ,\n",
       "       15.902786, 15.992783, 16.082779, 16.172775, 16.262787, 16.352783,\n",
       "       16.44278 , 16.532776, 16.622787, 16.712784, 16.80278 , 16.892776,\n",
       "       16.982788, 17.072784, 17.16278 , 17.252777, 17.342789, 17.432785,\n",
       "       17.522781, 17.612778, 17.70279 , 17.792786, 17.882782, 17.972778,\n",
       "       18.06279 , 18.152786, 18.242783, 18.332779, 18.422775, 18.512787,\n",
       "       18.602783, 18.69278 , 18.782776, 18.872787, 18.962784, 19.05278 ,\n",
       "       19.142776, 19.232788, 19.322784, 19.41278 , 19.502777, 19.592789,\n",
       "       19.682785, 19.772781, 19.862778, 19.95279 , 20.042786, 20.132782,\n",
       "       20.222778, 20.31279 , 20.402786, 20.492783, 20.582779, 20.672775,\n",
       "       20.762787, 20.852783, 20.94278 , 21.032776, 21.122787, 21.212784,\n",
       "       21.30278 , 21.392776, 21.482788, 21.572784, 21.66278 , 21.752777,\n",
       "       21.842789, 21.932785, 22.022781, 22.112778, 22.20279 , 22.292786,\n",
       "       22.382782, 22.472778, 22.56279 , 22.652786, 22.742783, 22.832779,\n",
       "       22.922775, 23.012787, 23.102783, 23.19278 , 23.282776, 23.372787,\n",
       "       23.462784, 23.55278 , 23.642776, 23.732788, 23.822784, 23.91278 ,\n",
       "       24.002777, 24.092789, 24.182785, 24.272781, 24.362778, 24.45279 ,\n",
       "       24.542786, 24.632782, 24.722778, 24.81279 , 24.902786, 24.992783,\n",
       "       25.082779, 25.172775, 25.262787, 25.352783, 25.44278 , 25.532776,\n",
       "       25.622787, 25.712784, 25.80278 , 25.892776, 25.982788, 26.072784],\n",
       "      dtype=float32)</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'>1981-01-01 ... 2010-12-31</div><input id='attrs-42f692b0-2b4f-4860-98f7-1f1f14683e2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42f692b0-2b4f-4860-98f7-1f1f14683e2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5724b3fc-87fa-422a-81aa-de902507ae6c' class='xr-var-data-in' type='checkbox'><label for='data-5724b3fc-87fa-422a-81aa-de902507ae6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1981-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-01-03T00:00:00.000000000&#x27;, ..., &#x27;2010-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2010-12-30T00:00:00.000000000&#x27;, &#x27;2010-12-31T00:00:00.000000000&#x27;],\n",
       "      shape=(10957,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rotated_pole</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-f6e2a70c-368d-4a4d-aabe-6158d0fcf8da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6e2a70c-368d-4a4d-aabe-6158d0fcf8da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbbf3bc9-e9a8-4e18-b474-34e730c3fcdd' class='xr-var-data-in' type='checkbox'><label for='data-fbbf3bc9-e9a8-4e18-b474-34e730c3fcdd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>north_pole_grid_longitude :</span></dt><dd>0.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>31.758312454493154</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>87.59703130293302</dd><dt><span>earth_radius :</span></dt><dd>6370997.0</dd><dt><span>grid_mapping_name :</span></dt><dd>rotated_latitude_longitude</dd></dl></div><div class='xr-var-data'><pre>array(1, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>45.05 45.03 45.01 ... 51.81 51.76</div><input id='attrs-0bd07ba0-b298-496b-8bca-8924f9a78305' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bd07ba0-b298-496b-8bca-8924f9a78305' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-914065b6-c0dd-409c-9dec-518034f2470f' class='xr-var-data-in' type='checkbox'><label for='data-914065b6-c0dd-409c-9dec-518034f2470f' title='Show/Hide data repr'><svg 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>_CoordinateAxisType :</span></dt><dd>Lat</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([[45.05358 , 45.030243, 45.00674 , ..., 40.12034 , 40.07745 ,\n",
       "        40.034466],\n",
       "       [45.140392, 45.117004, 45.09346 , ..., 40.199   , 40.15605 ,\n",
       "        40.11301 ],\n",
       "       [45.227184, 45.203762, 45.180172, ..., 40.277637, 40.234623,\n",
       "        40.191513],\n",
       "       ...,\n",
       "       [58.170254, 58.138374, 58.106293, ..., 51.720062, 51.666084,\n",
       "        51.612026],\n",
       "       [58.25444 , 58.22249 , 58.190334, ..., 51.79207 , 51.738018,\n",
       "        51.68388 ],\n",
       "       [58.33858 , 58.306557, 58.274323, ..., 51.864014, 51.80987 ,\n",
       "        51.755653]], shape=(156, 150), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-74.7 -74.58 ... -47.33 -47.22</div><input id='attrs-277b225a-5192-4969-bf0e-af4b14123244' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-277b225a-5192-4969-bf0e-af4b14123244' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d181347e-f76e-4e5c-a9c8-c27478279692' class='xr-var-data-in' type='checkbox'><label for='data-d181347e-f76e-4e5c-a9c8-c27478279692' title='Show/Hide data repr'><svg 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>_CoordinateAxisType :</span></dt><dd>Lon</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([[-74.70181 , -74.58145 , -74.46118 , ..., -58.377625, -58.276855,\n",
       "        -58.17627 ],\n",
       "       [-74.66815 , -74.54761 , -74.427124, ..., -58.320404, -58.219513,\n",
       "        -58.118805],\n",
       "       [-74.63437 , -74.51361 , -74.392914, ..., -58.26306 , -58.16205 ,\n",
       "        -58.06125 ],\n",
       "       ...,\n",
       "       [-67.862915, -67.70355 , -67.54443 , ..., -47.625427, -47.50934 ,\n",
       "        -47.393555],\n",
       "       [-67.80246 , -67.64279 , -67.48334 , ..., -47.538208, -47.422028,\n",
       "        -47.306183],\n",
       "       [-67.7417  , -67.581726, -67.42197 , ..., -47.450714, -47.334473,\n",
       "        -47.218536]], shape=(156, 150), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-449697aa-c5fb-466b-8347-914dfb4d769c' class='xr-section-summary-in' type='checkbox'  ><label for='section-449697aa-c5fb-466b-8347-914dfb4d769c' class='xr-section-summary' >Data variables: <span>(49)</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>orog</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(38, 16), meta=np.ndarray&gt;</div><input id='attrs-9d8d530a-18f7-427a-8911-4d034243e922' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d8d530a-18f7-427a-8911-4d034243e922' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-024aa3ed-dc8c-4fd0-9f4b-6701c4cddfdf' class='xr-var-data-in' type='checkbox'><label for='data-024aa3ed-dc8c-4fd0-9f4b-6701c4cddfdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface Altitude</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>surface_altitude</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:01:41] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                <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> 91.41 kiB </td>\n",
       "                        <td> 9.77 kiB </td>\n",
       "                    </tr>\n",
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       "                        <th> Shape </th>\n",
       "                        <td> (156, 150) </td>\n",
       "                        <td> (50, 50) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 6 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftgif</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(38, 16), meta=np.ndarray&gt;</div><input id='attrs-52de0b5b-29ac-4580-9de1-717497da9de1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52de0b5b-29ac-4580-9de1-717497da9de1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-646f1b4e-98e3-48a3-a51b-db187ee778de' class='xr-var-data-in' type='checkbox'><label for='data-646f1b4e-98e3-48a3-a51b-db187ee778de' title='Show/Hide data repr'><svg 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>Land Ice Area Fraction</dd><dt><span>description :</span></dt><dd>Fraction of grid cell covered by land ice (ice sheet, ice shelf, ice cap, glacier)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>land_ice_area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:03:58] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 91.41 kiB </td>\n",
       "                        <td> 9.77 kiB </td>\n",
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       "                        <td> (50, 50) </td>\n",
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       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 6 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
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       "        </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftlf</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(38, 16), meta=np.ndarray&gt;</div><input id='attrs-82ac5eb2-dd46-4ed7-af78-1cc3470c0ecb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82ac5eb2-dd46-4ed7-af78-1cc3470c0ecb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c49043f1-6164-4f8e-b778-9a399b5dca98' class='xr-var-data-in' type='checkbox'><label for='data-c49043f1-6164-4f8e-b778-9a399b5dca98' title='Show/Hide data repr'><svg 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>Land Area Fraction including Lakes</dd><dt><span>description :</span></dt><dd>Fraction of the Grid Cell Occupied by Land (Including Lakes)</dd><dt><span>standard_name :</span></dt><dd>land_area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:04:03] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    </tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 91.41 kiB </td>\n",
       "                        <td> 9.77 kiB </td>\n",
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       "                        <td colspan=\"2\"> 16 chunks in 6 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftlkf</span></div><div class='xr-var-dims'>(rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(38, 16), meta=np.ndarray&gt;</div><input id='attrs-71f20022-96f8-4c0a-a81d-f2aaccda6b83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71f20022-96f8-4c0a-a81d-f2aaccda6b83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d080115-b27c-444f-9a51-7f40a5ed20e3' class='xr-var-data-in' type='checkbox'><label for='data-6d080115-b27c-444f-9a51-7f40a5ed20e3' title='Show/Hide data repr'><svg 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>Lake Area Fraction</dd><dt><span>area_type :</span></dt><dd>lake_and_inland_sea</dd><dt><span>description :</span></dt><dd>Fraction of horizontal land grid cell area occupied by lake.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:04:06] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 9.77 kiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurmin</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1095, 38, 16), meta=np.ndarray&gt;</div><input id='attrs-4cc7a6ad-34f2-4425-805a-2dcb64bb33e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4cc7a6ad-34f2-4425-805a-2dcb64bb33e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e9bb230-6d9c-4865-887a-31f5f15535e0' class='xr-var-data-in' type='checkbox'><label for='data-6e9bb230-6d9c-4865-887a-31f5f15535e0' title='Show/Hide data repr'><svg 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>20 metre Relative Humidity (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: minimum (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
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       "                    <tr>\n",
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       "                        <td> 0.96 GiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prrpmod</span></div><div class='xr-var-dims'>(time, rlat, rlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1095, 38, 16), meta=np.ndarray&gt;</div><input id='attrs-29f91dba-54ed-4fab-9d4d-7a43ad198c5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29f91dba-54ed-4fab-9d4d-7a43ad198c5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d66a105c-6e0c-495f-818e-6c81f4b7207e' class='xr-var-data-in' type='checkbox'><label for='data-d66a105c-6e0c-495f-818e-6c81f4b7207e' title='Show/Hide data repr'><svg 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>Refrozen Rain</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Refrozen Rain using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field comes from the model background and is coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_PE0_SFC</dd><dt><span>standard_name :</span></dt><dd>refrozen_rain</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-03 15:11:26] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, #111111)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
       "  );\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "  line-height: 1.6;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-obj-name,\n",
       ".xr-group-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 3MB\n",
       "Dimensions:       (time: 16437)\n",
       "Coordinates: (6)\n",
       "Data variables: (49)\n",
       "Attributes: (12/30)\n",
       "    Conventions:             CF-1.8\n",
       "    Remarks:                 Original variable names are following the conven...\n",
       "    contact:                 \n",
       "    doi:                     https://doi.org/10.5194/hess-25-4917-2021\n",
       "    domain:                  NAM\n",
       "    frequency:               day\n",
       "    ...                      ...\n",
       "    history:                 2025-12-16 11:21:02.543093: Created a copy of Ca...\n",
       "    description:             Original data source: https://hpfx.collab.scienc...\n",
       "    institute:               Environment and Climate Change Canada\n",
       "    institute_id:            ECCC\n",
       "    dataset_description:     https://hpfx.collab.science.gc.ca/~scar700/rcas-...\n",
       "    dataset_id:              CaSRv3.2</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-7b897a4a-20f8-42a6-a8e6-60c43528e25d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7b897a4a-20f8-42a6-a8e6-60c43528e25d' 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>: 16437</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-14040ace-3767-4c35-a1ce-a2104f570c63' class='xr-section-summary-in' type='checkbox'  ><label for='section-14040ace-3767-4c35-a1ce-a2104f570c63' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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'>1980-01-01 ... 2024-12-31</div><input id='attrs-c04dd407-9448-4e43-86e1-24cde107e221' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c04dd407-9448-4e43-86e1-24cde107e221' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c320dec1-790a-4f94-bac9-dc326b3e8297' class='xr-var-data-in' type='checkbox'><label for='data-c320dec1-790a-4f94-bac9-dc326b3e8297' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-01T00:00:00.000000000&#x27;, &#x27;1980-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-03T00:00:00.000000000&#x27;, ..., &#x27;2024-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2024-12-30T00:00:00.000000000&#x27;, &#x27;2024-12-31T00:00:00.000000000&#x27;],\n",
       "      shape=(16437,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rlat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.24</div><input id='attrs-1f0447ff-dbf1-4178-83d6-7597d74db8d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f0447ff-dbf1-4178-83d6-7597d74db8d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04725c78-6e6b-4700-8dc0-ae300a8a7f84' class='xr-var-data-in' type='checkbox'><label for='data-04725c78-6e6b-4700-8dc0-ae300a8a7f84' title='Show/Hide data repr'><svg 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 in rotated pole grid</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array(-12.240001, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rlon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>24.81</div><input id='attrs-f99ec8e9-d384-4339-9402-05204971f895' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f99ec8e9-d384-4339-9402-05204971f895' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34239b9e-d7a7-431e-ae15-46adf61ba1fd' class='xr-var-data-in' type='checkbox'><label for='data-34239b9e-d7a7-431e-ae15-46adf61ba1fd' title='Show/Hide data repr'><svg 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 in rotated pole grid</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>degrees</dd></dl></div><div class='xr-var-data'><pre>array(24.81279, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rotated_pole</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-7de9f141-7a59-440b-8f4f-822c8753cdf3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7de9f141-7a59-440b-8f4f-822c8753cdf3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5147ef9-fe17-494d-95ce-aa538bcd5c96' class='xr-var-data-in' type='checkbox'><label for='data-d5147ef9-fe17-494d-95ce-aa538bcd5c96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>north_pole_grid_longitude :</span></dt><dd>0.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>31.758312454493154</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>87.59703130293302</dd><dt><span>earth_radius :</span></dt><dd>6370997.0</dd><dt><span>grid_mapping_name :</span></dt><dd>rotated_latitude_longitude</dd></dl></div><div class='xr-var-data'><pre>array(1, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>39.99</div><input id='attrs-749acd80-d678-44cf-b251-45ec877080f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-749acd80-d678-44cf-b251-45ec877080f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9d1ed2b-5c31-4e37-b027-e4bbc8155aa7' class='xr-var-data-in' type='checkbox'><label for='data-a9d1ed2b-5c31-4e37-b027-e4bbc8155aa7' title='Show/Hide data repr'><svg 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>_CoordinateAxisType :</span></dt><dd>Lat</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(39.989735, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-60.04</div><input id='attrs-6fd80a4b-93d4-4539-be2d-4862c14d5f8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fd80a4b-93d4-4539-be2d-4862c14d5f8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2b98b3b-f927-489c-8aff-f21e9c8584bd' class='xr-var-data-in' type='checkbox'><label for='data-f2b98b3b-f927-489c-8aff-f21e9c8584bd' title='Show/Hide data repr'><svg 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>_CoordinateAxisType :</span></dt><dd>Lon</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(-60.03961, dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-99109428-3c9b-488c-8e93-a2d7afed7546' class='xr-section-summary-in' type='checkbox'  ><label for='section-99109428-3c9b-488c-8e93-a2d7afed7546' class='xr-section-summary' >Data variables: <span>(49)</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>orog</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-53eb8020-48aa-4b50-993d-664dc240ffc2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53eb8020-48aa-4b50-993d-664dc240ffc2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03363096-2afa-4baa-8b2b-b867d16bd88f' class='xr-var-data-in' type='checkbox'><label for='data-03363096-2afa-4baa-8b2b-b867d16bd88f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface Altitude</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>surface_altitude</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:01:41] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4 B </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftgif</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-7e02930b-b7c7-4fd8-a464-b0c3d23145f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e02930b-b7c7-4fd8-a464-b0c3d23145f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-182d2eeb-b6a6-4ee3-a88a-e6d9a12123b2' class='xr-var-data-in' type='checkbox'><label for='data-182d2eeb-b6a6-4ee3-a88a-e6d9a12123b2' title='Show/Hide data repr'><svg 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>Land Ice Area Fraction</dd><dt><span>description :</span></dt><dd>Fraction of grid cell covered by land ice (ice sheet, ice shelf, ice cap, glacier)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>land_ice_area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:03:58] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4 B </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftlf</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-c1e92ca9-7f3b-4c7b-b8eb-3c7feeb67bf2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1e92ca9-7f3b-4c7b-b8eb-3c7feeb67bf2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e65f33cd-e34d-4400-b529-83fb4323cb77' class='xr-var-data-in' type='checkbox'><label for='data-e65f33cd-e34d-4400-b529-83fb4323cb77' title='Show/Hide data repr'><svg 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>Land Area Fraction including Lakes</dd><dt><span>description :</span></dt><dd>Fraction of the Grid Cell Occupied by Land (Including Lakes)</dd><dt><span>standard_name :</span></dt><dd>land_area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:04:03] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4 B </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftlkf</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-919699a1-513f-4ea9-ad86-99cb99ed8c54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-919699a1-513f-4ea9-ad86-99cb99ed8c54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6aa793cb-9ce9-4b65-8d46-c4a10b27bf6d' class='xr-var-data-in' type='checkbox'><label for='data-6aa793cb-9ce9-4b65-8d46-c4a10b27bf6d' title='Show/Hide data repr'><svg 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>Lake Area Fraction</dd><dt><span>area_type :</span></dt><dd>lake_and_inland_sea</dd><dt><span>description :</span></dt><dd>Fraction of horizontal land grid cell area occupied by lake.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:04:06] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4 B </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sftof</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(), meta=np.ndarray&gt;</div><input id='attrs-19151615-f266-4b90-9273-db299e54e4e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19151615-f266-4b90-9273-db299e54e4e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c379029f-b4ca-4952-8d98-30b635fcff02' class='xr-var-data-in' type='checkbox'><label for='data-c379029f-b4ca-4952-8d98-30b635fcff02' title='Show/Hide data repr'><svg 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>Sea Area Fraction</dd><dt><span>description :</span></dt><dd>Fraction of horizontal area occupied by ocean</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>standard_name :</span></dt><dd>sea_area_fraction</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-21 15:04:09] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4 B </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> () </td>\n",
       "                        <td> () </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 5 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        \n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>20mWind</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-a6262891-e7bb-4f36-b309-b86780b2bf8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6262891-e7bb-4f36-b309-b86780b2bf8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2290917e-d60a-4559-af42-89e84b8ee861' class='xr-var-data-in' type='checkbox'><label for='data-2290917e-d60a-4559-af42-89e84b8ee861' title='Show/Hide data repr'><svg 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>Wind Speed (20m). Height is approximate, see description.</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_UVC_09975</dd><dt><span>standard_name :</span></dt><dd>wind_speed</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 09:58:34] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</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> 64.21 kiB </td>\n",
       "                        <td> 5.71 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437,) </td>\n",
       "                        <td> (1461,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 12 chunks in 5 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurmin</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-4494ff1b-2b0c-46c4-bb43-14ecd0dc585e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4494ff1b-2b0c-46c4-bb43-14ecd0dc585e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e51fb5ca-0236-4684-8985-642cc6d1cd80' class='xr-var-data-in' type='checkbox'><label for='data-e51fb5ca-0236-4684-8985-642cc6d1cd80' title='Show/Hide data repr'><svg 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>20 metre Relative Humidity (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: minimum (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HR_09975</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:00:29] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hus</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-c2c2f2a8-8924-47ff-8306-2e581e49c3d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2c2f2a8-8924-47ff-8306-2e581e49c3d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc067592-638e-47c1-9207-d8ee47574a5a' class='xr-var-data-in' type='checkbox'><label for='data-cc067592-638e-47c1-9207-d8ee47574a5a' title='Show/Hide data repr'><svg 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>20 metre Specific Humidity (height is approximate :  see description)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
       "The true height needs to be inferred using the corresponding fields on the Charney-Phillips vertical grid (zcrd09975 - zcrd1000) (https://doi.org/10.1175/MWR-D-13-00255.1)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HU_09975</dd><dt><span>standard_name :</span></dt><dd>specific_humidity</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:17:50] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                        <td> 64.21 kiB </td>\n",
       "                        <td> 5.71 kiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>huss</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-58a80e10-036f-4814-a74e-8063b075db34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58a80e10-036f-4814-a74e-8063b075db34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-761f61a6-a4b6-4e84-86bd-65185ded2c7c' class='xr-var-data-in' type='checkbox'><label for='data-761f61a6-a4b6-4e84-86bd-65185ded2c7c' title='Show/Hide data repr'><svg 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>Near-Surface Specific Humidity (1.5m)</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_HU_1.5m</dd><dt><span>standard_name :</span></dt><dd>specific_humidity</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:22:42] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-eb4621be-341d-42a8-9bf0-61e84cd25c5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb4621be-341d-42a8-9bf0-61e84cd25c5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70f6c015-918b-46d1-acf5-55728345aebc' class='xr-var-data-in' type='checkbox'><label for='data-70f6c015-918b-46d1-acf5-55728345aebc' title='Show/Hide data repr'><svg 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>Precipitation</dd><dt><span>_corrected_standard_name :</span></dt><dd>lwe_thickness_of_precipitation_amount</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Precipitation using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field was produced by CaPA to improve its representation of observations. This field is different from the sum of prsnmod, prramod, prfrmod and prrpmod, which come directly from the model and which are coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>A_PR0_SFC</dd><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-04 09:51:05] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rlds</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-e05fdebe-b16a-4c13-9a5e-1b1b4c7f382d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e05fdebe-b16a-4c13-9a5e-1b1b4c7f382d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee877307-c6ef-4b1c-8ad7-b2acb26aaa9a' class='xr-var-data-in' type='checkbox'><label for='data-ee877307-c6ef-4b1c-8ad7-b2acb26aaa9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Surface Downwelling Longwave Radiation</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_FI_SFC</dd><dt><span>standard_name :</span></dt><dd>surface_downwelling_longwave_flux_in_air</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 11:48:27] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tdps</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-a5f3dc6c-7d59-42e7-b1c8-d8b027fe99f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5f3dc6c-7d59-42e7-b1c8-d8b027fe99f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-922ee50f-6696-415b-93a5-0f8f4c12f30a' class='xr-var-data-in' type='checkbox'><label for='data-922ee50f-6696-415b-93a5-0f8f4c12f30a' title='Show/Hide data repr'><svg 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>1.5 metre dewpoint temperature</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TD_1.5m</dd><dt><span>standard_name :</span></dt><dd>dew_point_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:32:20] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tdpsmax</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-df159ba8-2e7b-43ef-a615-b81945d5b1d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df159ba8-2e7b-43ef-a615-b81945d5b1d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31551bc8-f42c-45fc-a31d-b816d11cc724' class='xr-var-data-in' type='checkbox'><label for='data-31551bc8-f42c-45fc-a31d-b816d11cc724' title='Show/Hide data repr'><svg 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>1.5 metre dewpoint temperature</dd><dt><span>cell_methods :</span></dt><dd>time: maximum (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TD_1.5m</dd><dt><span>standard_name :</span></dt><dd>dew_point_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:35:53] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tdpsmin</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-9f63d7c2-649f-491e-bcb3-4f50fad0b4ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f63d7c2-649f-491e-bcb3-4f50fad0b4ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ba2dc56-d7ff-4420-af39-b9e1f449d898' class='xr-var-data-in' type='checkbox'><label for='data-8ba2dc56-d7ff-4420-af39-b9e1f449d898' title='Show/Hide data repr'><svg 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>1.5 metre dewpoint temperature</dd><dt><span>cell_methods :</span></dt><dd>time: minimum (interval: 1 day)</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_TD_1.5m</dd><dt><span>standard_name :</span></dt><dd>dew_point_temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>units_metadata :</span></dt><dd>temperature: unknown</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 12:39:30] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ua</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-234e6ff6-6757-459b-a513-ee60d8c99528' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-234e6ff6-6757-459b-a513-ee60d8c99528' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6509593-d310-4ea5-9d73-dcb03c249a86' class='xr-var-data-in' type='checkbox'><label for='data-a6509593-d310-4ea5-9d73-dcb03c249a86' title='Show/Hide data repr'><svg 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>Eastward Wind (20m). Height is approximate, see description.</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>The approximate 20 metre level is more specifically 99.75% of the atmosphere based on pressure elevation, where 100% is the surface. \n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zcrd09975</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-5616d368-abb1-4c58-b27f-e2602836e24a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5616d368-abb1-4c58-b27f-e2602836e24a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cdb319d-c6c8-4e54-a77a-eefad0f71efb' class='xr-var-data-in' type='checkbox'><label for='data-5cdb319d-c6c8-4e54-a77a-eefad0f71efb' title='Show/Hide data repr'><svg 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>Model vertical grid coordinate</dd><dt><span>_standard_name :</span></dt><dd></dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>description :</span></dt><dd>Corresponding coordinate (09975) on the GEM Charney-Phillips vertical grid (https://doi.org/10.1175/MWR-D-13-00255.1). The height of variables with level 0XXXX can be inferred zcrd0XXXX - zcrd10000.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_GZ_09975</dd><dt><span>standard_name :</span></dt><dd>Geopotential height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-01-08 13:09:30] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prramod</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-c5976e58-2393-4713-9a77-bd44900cda4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5976e58-2393-4713-9a77-bd44900cda4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64f007e9-6206-41a0-96aa-9d8c1285e90e' class='xr-var-data-in' type='checkbox'><label for='data-64f007e9-6206-41a0-96aa-9d8c1285e90e' title='Show/Hide data repr'><svg 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>Liquid Precipitation</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Liquid Precipitation using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field comes from the model background and is coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_RN0_SFC</dd><dt><span>standard_name :</span></dt><dd>rainfall_flux</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-03 15:09:36] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 64.21 kiB </td>\n",
       "                        <td> 5.71 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (16437,) </td>\n",
       "                        <td> (1461,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 12 chunks in 5 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prrpmod</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-8e2a7c85-8ca7-4694-b6e4-8b875d79d97c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e2a7c85-8ca7-4694-b6e4-8b875d79d97c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9af1f307-fc2a-4357-847f-02d290fdd79f' class='xr-var-data-in' type='checkbox'><label for='data-9af1f307-fc2a-4357-847f-02d290fdd79f' title='Show/Hide data repr'><svg 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>Refrozen Rain</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Refrozen Rain using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field comes from the model background and is coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_PE0_SFC</dd><dt><span>standard_name :</span></dt><dd>refrozen_rain</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-03 15:11:26] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 5.71 kiB </td>\n",
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       "                    <tr>\n",
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       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 12 chunks in 5 graph layers </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prsnmod</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1461,), meta=np.ndarray&gt;</div><input id='attrs-4922df78-b66c-4f75-aaa2-e8d3288e6a7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4922df78-b66c-4f75-aaa2-e8d3288e6a7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f52b94cc-97aa-4369-9f3c-c2f138354fd7' class='xr-var-data-in' type='checkbox'><label for='data-f52b94cc-97aa-4369-9f3c-c2f138354fd7' title='Show/Hide data repr'><svg 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>Snowfall Flux</dd><dt><span>_units_context :</span></dt><dd>hydro</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 1 day)</dd><dt><span>comments :</span></dt><dd>Converted from Total Snow amount using a density of 1000 kg/m³.</dd><dt><span>description :</span></dt><dd>This field comes from the model background and is coherent with prmod.</dd><dt><span>grid_mapping :</span></dt><dd>rotated_pole</dd><dt><span>original_variable :</span></dt><dd>P_SN0_SFC</dd><dt><span>standard_name :</span></dt><dd>snowfall_flux</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>_QuantizeBitRoundNumberOfSignificantDigits :</span></dt><dd>15</dd><dt><span>history :</span></dt><dd>[2026-03-03 15:11:51] Data compressed with BitRound by keeping 15 bits.</dd><dt><span>_ChunkSizes :</span></dt><dd>[1461   50   50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 64.21 kiB </td>\n",
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       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 12 chunks in 5 graph layers </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-ed68a3fa-40c1-41d0-ab7c-37bf96cc9bc0' class='xr-section-summary-in' type='checkbox'  ><label for='section-ed68a3fa-40c1-41d0-ab7c-37bf96cc9bc0' class='xr-section-summary' >Attributes: <span>(30)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.8</dd><dt><span>Remarks :</span></dt><dd>Original variable names are following the convention &lt;Product&gt;_&lt;Type:A=Analysis,P=Prediction&gt;_&lt;ECCC name&gt;_&lt;Level/Tile/Category&gt;. Variables with level &#x27;10000&#x27; are at surface level. The height [m] of variables with level &#x27;0XXXX&#x27; needs to be inferrred using the corresponding fields of geopotential height (GZ_0XXXX-GZ_10000). The variables UUC, VVC, UVC, and WDC are not modelled but inferred from UU and VV for convenience of the users. Precipitation (PR) is reported as 6-hr accumulations for CaPA_fine and CaPA_coarse. Precipitation (PR) are accumulations since beginning of the forecast for GEPS, GDPS, REPS, RDPS, HRDPS, and CaLDAS. The re-analysis product CaSR_v3.2 contains two variables for precipitation: &#x27;CaSR_v3.2_P_PR0_SFC&#x27; is the model precipitation (trial field used by CaPA) and &#x27;CaSR_v3.2_A_PR0_SFC&#x27; is precipitations adjusted with CaPA 24h precipitation (as in &#x27;RDRS_P_PR0_SFC&#x27;). Please be aware that the baseflow &#x27;O1&#x27; of the current version of WCPS is not reliable during the spring melt period.</dd><dt><span>contact :</span></dt><dd></dd><dt><span>doi :</span></dt><dd>https://doi.org/10.5194/hess-25-4917-2021</dd><dt><span>domain :</span></dt><dd>NAM</dd><dt><span>frequency :</span></dt><dd>day</dd><dt><span>institution :</span></dt><dd>GovCan</dd><dt><span>license :</span></dt><dd>https://open.canada.ca/en/open-government-licence-canada</dd><dt><span>miranda_version :</span></dt><dd>0.6.0-dev.8</dd><dt><span>organisation :</span></dt><dd>ECCC</dd><dt><span>prefix :</span></dt><dd>CaSR_v3.2_</dd><dt><span>processing_level :</span></dt><dd>raw</dd><dt><span>project :</span></dt><dd>casr-v32</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>source :</span></dt><dd>CaSR</dd><dt><span>table_date :</span></dt><dd>2025-02-13</dd><dt><span>table_id :</span></dt><dd>eccc</dd><dt><span>title :</span></dt><dd>Canadian Surface Reanalysis (CaSR v3.2) : daily</dd><dt><span>type :</span></dt><dd>reanalysis</dd><dt><span>version :</span></dt><dd>v3.2</dd><dt><span>intake_esm_vars :</span></dt><dd>orog</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>GovCan_CaSR_NAM.NAM.raw.fx</dd><dt><span>license_type :</span></dt><dd>permissive</dd><dt><span>format :</span></dt><dd>netcdf</dd><dt><span>history :</span></dt><dd>2025-12-16 11:21:02.543093: Created a copy of CaSR v3.1 with lat/lon values from CaSR v3.2. 2025-06-13 13:09:22.368470:Created from the Gem_geophy.fst_706x778 file provided by (ECCC).</dd><dt><span>description :</span></dt><dd>Original data source: https://hpfx.collab.science.gc.ca/~scar700/rcas-casr/</dd><dt><span>institute :</span></dt><dd>Environment and Climate Change Canada</dd><dt><span>institute_id :</span></dt><dd>ECCC</dd><dt><span>dataset_description :</span></dt><dd>https://hpfx.collab.science.gc.ca/~scar700/rcas-casr/</dd><dt><span>dataset_id :</span></dt><dd>CaSRv3.2</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 3MB\n",
       "Dimensions:       (time: 16437)\n",
       "Coordinates: (6)\n",
       "Data variables: (49)\n",
       "Attributes: (12/30)\n",
       "    Conventions:             CF-1.8\n",
       "    Remarks:                 Original variable names are following the conven...\n",
       "    contact:                 \n",
       "    doi:                     https://doi.org/10.5194/hess-25-4917-2021\n",
       "    domain:                  NAM\n",
       "    frequency:               day\n",
       "    ...                      ...\n",
       "    history:                 2025-12-16 11:21:02.543093: Created a copy of Ca...\n",
       "    description:             Original data source: https://hpfx.collab.scienc...\n",
       "    institute:               Environment and Climate Change Canada\n",
       "    institute_id:            ECCC\n",
       "    dataset_description:     https://hpfx.collab.science.gc.ca/~scar700/rcas-...\n",
       "    dataset_id:              CaSRv3.2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from clisops.core import subset\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "# Subset bounding box\n",
    "lon_bnds = [-70, -55]\n",
    "lat_bnds = [44, 55]\n",
    "\n",
    "# Loading the coordinate data speeds up the subsetting process a little\n",
    "for coord in [\"lat\", \"lon\"]:\n",
    "    ds[coord] = ds[coord].load()\n",
    "\n",
    "# Subset bbox\n",
    "bbox = subset.subset_bbox(\n",
    "    ds, lon_bnds=lon_bnds, lat_bnds=lat_bnds, start_date=\"1981\", end_date=\"2010\"\n",
    ")\n",
    "\n",
    "# Subset gridpoint\n",
    "site = subset.subset_gridpoint(ds, lat=40, lon=-60)\n",
    "\n",
    "with xr.set_options(display_expand_data_vars=False, display_expand_coords=False):\n",
    "    display(bbox)\n",
    "    display(site)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4",
   "metadata": {},
   "source": [
    "## Data analysis\n",
    "\n",
    "Here we'll compute the 10-year precipitation average on the eastern Canada subset using dask to parallelize computations. A dictionary of options is given to dask to specify the number of workers, threads per worker, memory limit, etc. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f1cb1dffda0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# NBVAL_IGNORE_OUTPUT\n",
    "\n",
    "import logging\n",
    "\n",
    "from dask.distributed import Client\n",
    "from IPython.display import clear_output\n",
    "\n",
    "# For hourly data, we suggest using the following chunking pattern: dict(time=720, rlon=50, rlat=50)\n",
    "# Compute 10-year precipitation means. This is a lazy operation, no computations are done at this point.\n",
    "pr10y = bbox.pr.resample(time=\"10YS\").mean(dim=\"time\", keep_attrs=True)\n",
    "\n",
    "# Options for dask workers\n",
    "dask_kwargs = dict(\n",
    "    n_workers=8,\n",
    "    threads_per_worker=6,\n",
    "    memory_limit=\"2.5GB\",\n",
    "    local_directory=\"/notebook_dir/writable-workspace/tmp\",\n",
    "    silence_logs=logging.ERROR,\n",
    ")\n",
    "\n",
    "# Actually perform the computation\n",
    "with Client(**dask_kwargs) as c:\n",
    "    clear_output()\n",
    "    display(c)\n",
    "    # Just taking the first 10-year average to speed things up\n",
    "    pr10y = pr10y.isel(time=0).compute()\n",
    "clear_output()\n",
    "pr10y.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6",
   "metadata": {},
   "source": [
    "Note that the graphic axes follow the dimensions of the dataset, namely rotated longitudes and latitudes. The bounding box subset is however performed on longitudes and latitudes, and the areas outside of the bounding box are filled with NaNs, which explain the presence of white areas in the graph. \n",
    "\n",
    "In this second example, we'll use xclim to compute the heat index' annual maxima at the selected site. The heat index accounts for both temperature and relative humidity to describe human perception of heat."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f1c9b235220>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# NBVAL_IGNORE_OUTPUT\n",
    "\n",
    "from xclim import convert\n",
    "\n",
    "# Compute heat index using xclim and find the annual maxima.\n",
    "with Client(**dask_kwargs) as c:\n",
    "    clear_output()\n",
    "    display(c)\n",
    "    hi_max = convert.heat_index(ds=site).resample(time=\"Y\").max()\n",
    "clear_output()\n",
    "\n",
    "# Plot the results\n",
    "hi_max.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8",
   "metadata": {},
   "source": [
    "## Visualization\n",
    "\n",
    "Finally, we show how plot the CaSR data on a map. We need to specify two projections: one for the map, and another for the data. The Cartopy library is then able to connect data coordinates to map coordinates. \n",
    "\n",
    "Here for simplicity we'll use the regular lat-lon projection, called `PlateCarree`. Other choices would be `Orthographic` for a remote sensing view of the Earth, or `LambertConformal`, a projection often used for Canada-wide maps. \n",
    "\n",
    "The details of the data coordinate reference system are stored for convenience within the `rotated_pole` variable' attributes. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, white)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
       "  );\n",
       "}\n",
       "\n",
       "html[theme=\"dark\"],\n",
       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: var(\n",
       "    --jp-content-font-color0,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
       "  );\n",
       "  --xr-font-color2: var(\n",
       "    --jp-content-font-color2,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
       "  );\n",
       "  --xr-font-color3: var(\n",
       "    --jp-content-font-color3,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, #111111)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
       "  );\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "  line-height: 1.6;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-obj-name,\n",
       ".xr-group-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;rotated_pole&#x27; ()&gt; Size: 4B\n",
       "array(1, dtype=int32)\n",
       "Coordinates:\n",
       "    rotated_pole  int32 4B 1\n",
       "Attributes:\n",
       "    north_pole_grid_longitude:  0.0\n",
       "    grid_north_pole_latitude:   31.758312454493154\n",
       "    grid_north_pole_longitude:  87.59703130293302\n",
       "    earth_radius:               6370997.0\n",
       "    grid_mapping_name:          rotated_latitude_longitude</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;rotated_pole&#x27;</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c4f34038-90bb-438f-aa20-172625afbc8c' class='xr-array-in' type='checkbox' checked><label for='section-c4f34038-90bb-438f-aa20-172625afbc8c' 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</span></div><div class='xr-array-data'><pre>array(1, dtype=int32)</pre></div></div></li><li class='xr-section-item'><input id='section-739b20b9-8899-4406-805d-a7e0b61a0ef9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-739b20b9-8899-4406-805d-a7e0b61a0ef9' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>rotated_pole</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-dce81753-aff2-4406-a218-18746c6b4828' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dce81753-aff2-4406-a218-18746c6b4828' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16cf434c-3f8a-49d7-a773-6e3507e176d5' class='xr-var-data-in' type='checkbox'><label for='data-16cf434c-3f8a-49d7-a773-6e3507e176d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>north_pole_grid_longitude :</span></dt><dd>0.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>31.758312454493154</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>87.59703130293302</dd><dt><span>earth_radius :</span></dt><dd>6370997.0</dd><dt><span>grid_mapping_name :</span></dt><dd>rotated_latitude_longitude</dd></dl></div><div class='xr-var-data'><pre>array(1, dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-642c1d9d-6aec-44d4-86bd-134ddb2154a1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-642c1d9d-6aec-44d4-86bd-134ddb2154a1' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>north_pole_grid_longitude :</span></dt><dd>0.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>31.758312454493154</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>87.59703130293302</dd><dt><span>earth_radius :</span></dt><dd>6370997.0</dd><dt><span>grid_mapping_name :</span></dt><dd>rotated_latitude_longitude</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'rotated_pole' ()> Size: 4B\n",
       "array(1, dtype=int32)\n",
       "Coordinates:\n",
       "    rotated_pole  int32 4B 1\n",
       "Attributes:\n",
       "    north_pole_grid_longitude:  0.0\n",
       "    grid_north_pole_latitude:   31.758312454493154\n",
       "    grid_north_pole_longitude:  87.59703130293302\n",
       "    earth_radius:               6370997.0\n",
       "    grid_mapping_name:          rotated_latitude_longitude"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbox.rotated_pole"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "10",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f1c9aebd4f0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cartopy.crs as ccrs\n",
    "\n",
    "# A regular lat-lon projection for the map\n",
    "pc = ccrs.PlateCarree()\n",
    "\n",
    "# The coordinate reference system for the rotated pole data\n",
    "rotp = ccrs.RotatedPole(\n",
    "    pole_longitude=bbox.rotated_pole.grid_north_pole_longitude,\n",
    "    pole_latitude=bbox.rotated_pole.grid_north_pole_latitude,\n",
    ")\n",
    "\n",
    "# Plot rotated pole data on a regular lat lon grid.\n",
    "fig = plt.figure(figsize=(4, 4))\n",
    "\n",
    "# Here we specify the map projection\n",
    "ax = plt.subplot(1, 1, 1, projection=pc)\n",
    "ax.set_extent(lon_bnds + lat_bnds)\n",
    "\n",
    "# Here we specify the transformation required to map data coordinates to map coordinates.\n",
    "m = ax.pcolormesh(pr10y.rlon, pr10y.rlat, pr10y, transform=rotp)\n",
    "\n",
    "# Fine-tuning\n",
    "ax.coastlines()\n",
    "ax.gridlines()\n",
    "plt.colorbar(\n",
    "    m,\n",
    "    orientation=\"horizontal\",\n",
    "    label=f\"{pr10y.long_name} ({pr10y.units})\",\n",
    "    fraction=0.046,\n",
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    ")"
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