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| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "id": "6299c96c-6495-4e79-b2a2-fc018d957530", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "import xarray as xr\n", | |
| "import ndpyramid" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "id": "c05d7c1a-295e-44a2-9d1e-a9452e46fb64", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
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| "text": [ | |
| "/tmp/ipykernel_584/18680365.py:1: FutureWarning: In a future version of xarray decode_timedelta will default to False rather than None. To silence this warning, set decode_timedelta to True, False, or a 'CFTimedeltaCoder' instance.\n", | |
| " ds = xr.open_dataset('/home/anderson/ecmwrf.nc', engine='netcdf4', decode_cf=True, chunks={}, mask_and_scale=False)#.isel(valid_time=slice(5))\n" | |
| ] | |
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| "</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 40GB\n", | |
| "Dimensions: (valid_time: 85, isobaricInhPa: 13, latitude: 721,\n", | |
| " longitude: 1440)\n", | |
| "Coordinates:\n", | |
| " time datetime64[ns] 8B ...\n", | |
| " step (valid_time) timedelta64[ns] 680B dask.array<chunksize=(85,), meta=np.ndarray>\n", | |
| " * isobaricInhPa (isobaricInhPa) float64 104B 1e+03 925.0 ... 100.0 50.0\n", | |
| " * latitude (latitude) float64 6kB 90.0 89.75 89.5 ... -89.75 -90.0\n", | |
| " * longitude (longitude) float64 12kB -180.0 -179.8 ... 179.5 179.8\n", | |
| " * valid_time (valid_time) datetime64[ns] 680B 2025-01-30 ... 2025-0...\n", | |
| " surface float64 8B ...\n", | |
| " heightAboveGround float64 8B ...\n", | |
| " meanSea float64 8B ...\n", | |
| " entireAtmosphere float64 8B ...\n", | |
| "Data variables: (12/17)\n", | |
| " u (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " v (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " r (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " gh (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " t (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " tp (valid_time, latitude, longitude) float32 353MB dask.array<chunksize=(85, 721, 1440), meta=np.ndarray>\n", | |
| " ... ...\n", | |
| " q (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " vo (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " d (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " ro (valid_time, latitude, longitude) float32 353MB dask.array<chunksize=(85, 721, 1440), meta=np.ndarray>\n", | |
| " u10 (valid_time, latitude, longitude) float32 353MB dask.array<chunksize=(85, 721, 1440), meta=np.ndarray>\n", | |
| " v10 (valid_time, latitude, longitude) float32 353MB dask.array<chunksize=(85, 721, 1440), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " GRIB_edition: 2\n", | |
| " GRIB_centre: ecmf\n", | |
| " GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts\n", | |
| " GRIB_subCentre: 0\n", | |
| " Conventions: CF-1.7\n", | |
| " institution: European Centre for Medium-Range Weather Forecasts\n", | |
| " history: 2025-01-30T23:01 GRIB to CDM+CF via cfgrib-0.9.1...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-862300b3-f7ec-4422-a6b0-5a3ea8906997' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-862300b3-f7ec-4422-a6b0-5a3ea8906997' 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'>valid_time</span>: 85</li><li><span class='xr-has-index'>isobaricInhPa</span>: 13</li><li><span class='xr-has-index'>latitude</span>: 721</li><li><span class='xr-has-index'>longitude</span>: 1440</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2d8c1be3-f960-4b45-9361-b2bca7605fe9' class='xr-section-summary-in' type='checkbox' checked><label for='section-2d8c1be3-f960-4b45-9361-b2bca7605fe9' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3076eb6f-4cb6-4666-93bd-8e5b637bf048' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3076eb6f-4cb6-4666-93bd-8e5b637bf048' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f93d2355-2423-499b-9535-8ed7595c3deb' class='xr-var-data-in' type='checkbox'><label for='data-f93d2355-2423-499b-9535-8ed7595c3deb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>(valid_time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85,), meta=np.ndarray></div><input id='attrs-190b4f72-301d-405a-bc1e-96d8939daf10' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-190b4f72-301d-405a-bc1e-96d8939daf10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-622a874f-daab-41fd-9bc3-20bcffd7f92c' class='xr-var-data-in' type='checkbox'><label for='data-622a874f-daab-41fd-9bc3-20bcffd7f92c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><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> 680 B </td>\n", | |
| " <td> 680 B </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85,) </td>\n", | |
| " <td> (85,) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> timedelta64[ns] numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
| " <svg width=\"170\" height=\"76\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"26\" x2=\"120\" y2=\"26\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"26\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"26\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.0,0.0 120.0,0.0 120.0,26.207589997831487 0.0,26.207589997831487\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"60.000000\" y=\"46.207590\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >85</text>\n", | |
| " <text x=\"140.000000\" y=\"13.103795\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,13.103795)\">1</text>\n", | |
| "</svg>\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>isobaricInhPa</span></div><div class='xr-var-dims'>(isobaricInhPa)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e+03 925.0 850.0 ... 100.0 50.0</div><input id='attrs-88e01e55-684e-4e60-93cb-3a3f9358296c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88e01e55-684e-4e60-93cb-3a3f9358296c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6e3bcf2-f88b-4269-897a-d8c49e558f0d' class='xr-var-data-in' type='checkbox'><label for='data-b6e3bcf2-f88b-4269-897a-d8c49e558f0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>long_name :</span></dt><dd>pressure</dd><dt><span>units :</span></dt><dd>hPa</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array([1000., 925., 850., 700., 600., 500., 400., 300., 250., 200.,\n", | |
| " 150., 100., 50.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.75 89.5 ... -89.75 -90.0</div><input id='attrs-4922023c-37f7-4ea5-9fc6-cf985a39e81a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4922023c-37f7-4ea5-9fc6-cf985a39e81a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f81cf72-87f7-4b27-a8d0-ef00aa7cdb4f' class='xr-var-data-in' type='checkbox'><label for='data-3f81cf72-87f7-4b27-a8d0-ef00aa7cdb4f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([ 90. , 89.75, 89.5 , ..., -89.5 , -89.75, -90. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.8 ... 179.5 179.8</div><input id='attrs-a51314ce-0e45-4231-9224-c2ed3e566630' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a51314ce-0e45-4231-9224-c2ed3e566630' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c564bb53-8166-4fed-a086-c62df451e73e' class='xr-var-data-in' type='checkbox'><label for='data-c564bb53-8166-4fed-a086-c62df451e73e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-180. , -179.75, -179.5 , ..., 179.25, 179.5 , 179.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>valid_time</span></div><div class='xr-var-dims'>(valid_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2025-01-30 ... 2025-02-14</div><input id='attrs-64d950e2-9ffa-4b55-ad3b-ccd275fd12a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64d950e2-9ffa-4b55-ad3b-ccd275fd12a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec9c1bb6-d59a-486b-b894-8acd4da369ba' class='xr-var-data-in' type='checkbox'><label for='data-ec9c1bb6-d59a-486b-b894-8acd4da369ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(['2025-01-30T00:00:00.000000000', '2025-01-30T03:00:00.000000000',\n", | |
| " '2025-01-30T06:00:00.000000000', '2025-01-30T09:00:00.000000000',\n", | |
| " '2025-01-30T12:00:00.000000000', '2025-01-30T15:00:00.000000000',\n", | |
| " '2025-01-30T18:00:00.000000000', '2025-01-30T21:00:00.000000000',\n", | |
| " '2025-01-31T00:00:00.000000000', '2025-01-31T03:00:00.000000000',\n", | |
| " '2025-01-31T06:00:00.000000000', '2025-01-31T09:00:00.000000000',\n", | |
| " '2025-01-31T12:00:00.000000000', '2025-01-31T15:00:00.000000000',\n", | |
| " '2025-01-31T18:00:00.000000000', '2025-01-31T21:00:00.000000000',\n", | |
| " '2025-02-01T00:00:00.000000000', '2025-02-01T03:00:00.000000000',\n", | |
| " '2025-02-01T06:00:00.000000000', '2025-02-01T09:00:00.000000000',\n", | |
| " '2025-02-01T12:00:00.000000000', '2025-02-01T15:00:00.000000000',\n", | |
| " '2025-02-01T18:00:00.000000000', '2025-02-01T21:00:00.000000000',\n", | |
| " '2025-02-02T00:00:00.000000000', '2025-02-02T03:00:00.000000000',\n", | |
| " '2025-02-02T06:00:00.000000000', '2025-02-02T09:00:00.000000000',\n", | |
| " '2025-02-02T12:00:00.000000000', '2025-02-02T15:00:00.000000000',\n", | |
| " '2025-02-02T18:00:00.000000000', '2025-02-02T21:00:00.000000000',\n", | |
| " '2025-02-03T00:00:00.000000000', '2025-02-03T03:00:00.000000000',\n", | |
| " '2025-02-03T06:00:00.000000000', '2025-02-03T09:00:00.000000000',\n", | |
| " '2025-02-03T12:00:00.000000000', '2025-02-03T15:00:00.000000000',\n", | |
| " '2025-02-03T18:00:00.000000000', '2025-02-03T21:00:00.000000000',\n", | |
| " '2025-02-04T00:00:00.000000000', '2025-02-04T03:00:00.000000000',\n", | |
| " '2025-02-04T06:00:00.000000000', '2025-02-04T09:00:00.000000000',\n", | |
| " '2025-02-04T12:00:00.000000000', '2025-02-04T15:00:00.000000000',\n", | |
| " '2025-02-04T18:00:00.000000000', '2025-02-04T21:00:00.000000000',\n", | |
| " '2025-02-05T00:00:00.000000000', '2025-02-05T06:00:00.000000000',\n", | |
| " '2025-02-05T12:00:00.000000000', '2025-02-05T18:00:00.000000000',\n", | |
| " '2025-02-06T00:00:00.000000000', '2025-02-06T06:00:00.000000000',\n", | |
| " '2025-02-06T12:00:00.000000000', '2025-02-06T18:00:00.000000000',\n", | |
| " '2025-02-07T00:00:00.000000000', '2025-02-07T06:00:00.000000000',\n", | |
| " '2025-02-07T12:00:00.000000000', '2025-02-07T18:00:00.000000000',\n", | |
| " '2025-02-08T00:00:00.000000000', '2025-02-08T06:00:00.000000000',\n", | |
| " '2025-02-08T12:00:00.000000000', '2025-02-08T18:00:00.000000000',\n", | |
| " '2025-02-09T00:00:00.000000000', '2025-02-09T06:00:00.000000000',\n", | |
| " '2025-02-09T12:00:00.000000000', '2025-02-09T18:00:00.000000000',\n", | |
| " '2025-02-10T00:00:00.000000000', '2025-02-10T06:00:00.000000000',\n", | |
| " '2025-02-10T12:00:00.000000000', '2025-02-10T18:00:00.000000000',\n", | |
| " '2025-02-11T00:00:00.000000000', '2025-02-11T06:00:00.000000000',\n", | |
| " '2025-02-11T12:00:00.000000000', '2025-02-11T18:00:00.000000000',\n", | |
| " '2025-02-12T00:00:00.000000000', '2025-02-12T06:00:00.000000000',\n", | |
| " '2025-02-12T12:00:00.000000000', '2025-02-12T18:00:00.000000000',\n", | |
| " '2025-02-13T00:00:00.000000000', '2025-02-13T06:00:00.000000000',\n", | |
| " '2025-02-13T12:00:00.000000000', '2025-02-13T18:00:00.000000000',\n", | |
| " '2025-02-14T00:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b0e4f2b1-466d-4e53-8b54-ea051e0fe3ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0e4f2b1-466d-4e53-8b54-ea051e0fe3ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e296a36e-98e0-4661-b109-19dd1e8627ed' class='xr-var-data-in' type='checkbox'><label for='data-e296a36e-98e0-4661-b109-19dd1e8627ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(surface)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heightAboveGround</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-462d3b38-64e4-413f-861b-57c682f9b496' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-462d3b38-64e4-413f-861b-57c682f9b496' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3773edb-4dfc-4956-86f6-96aa88e398d9' class='xr-var-data-in' type='checkbox'><label for='data-f3773edb-4dfc-4956-86f6-96aa88e398d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>long_name :</span></dt><dd>height above the surface</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>meanSea</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd324411-b73e-4ddb-8b09-bf39430ce433' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd324411-b73e-4ddb-8b09-bf39430ce433' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de3312e0-a80b-435b-9d69-05a5dc4a7d3b' class='xr-var-data-in' type='checkbox'><label for='data-de3312e0-a80b-435b-9d69-05a5dc4a7d3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(meanSea)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>entireAtmosphere</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b70eb457-52c8-456b-9220-295f86f740cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b70eb457-52c8-456b-9220-295f86f740cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0b1bbf2-8fb6-4bd6-b2a6-8ed6525c821d' class='xr-var-data-in' type='checkbox'><label for='data-a0b1bbf2-8fb6-4bd6-b2a6-8ed6525c821d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(entireAtmosphere)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e9bc9059-8a1c-4e0d-b847-94b06dd92a95' class='xr-section-summary-in' type='checkbox' ><label for='section-e9bc9059-8a1c-4e0d-b847-94b06dd92a95' class='xr-section-summary' >Data variables: <span>(17)</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>u</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray></div><input id='attrs-6223ebd9-130e-4bcf-a1a4-bcb043235435' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6223ebd9-130e-4bcf-a1a4-bcb043235435' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2714fb03-7a76-416e-ae05-2e9453db7081' class='xr-var-data-in' type='checkbox'><label for='data-2714fb03-7a76-416e-ae05-2e9453db7081' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>131</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>eastward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>u</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>U component of wind</dd><dt><span>GRIB_shortName :</span></dt><dd>u</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</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> 4.27 GiB </td>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray></div><input id='attrs-7bc11135-e1a7-4523-8c13-29289cbe4d5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bc11135-e1a7-4523-8c13-29289cbe4d5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b7caecc-2a8d-464c-a506-5add664a0610' class='xr-var-data-in' type='checkbox'><label for='data-6b7caecc-2a8d-464c-a506-5add664a0610' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>132</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>northward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>v</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>V component of wind</dd><dt><span>GRIB_shortName :</span></dt><dd>v</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>V component of wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>northward_wind</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> 4.27 GiB </td>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>r</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray></div><input id='attrs-3df241e9-753c-4e21-b463-b1d81c82c298' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3df241e9-753c-4e21-b463-b1d81c82c298' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1da12190-2c49-4af7-a92f-06badb8bb9a9' class='xr-var-data-in' type='checkbox'><label for='data-1da12190-2c49-4af7-a92f-06badb8bb9a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>157</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>relative_humidity</dd><dt><span>GRIB_cfVarName :</span></dt><dd>r</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Relative humidity</dd><dt><span>GRIB_shortName :</span></dt><dd>r</dd><dt><span>GRIB_units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Relative humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gh</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray></div><input id='attrs-7d6c5bd8-e378-4cde-9060-8e4ac3a9f720' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d6c5bd8-e378-4cde-9060-8e4ac3a9f720' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1bae141-dcae-4c84-87a9-c7cec5ebe733' class='xr-var-data-in' type='checkbox'><label for='data-b1bae141-dcae-4c84-87a9-c7cec5ebe733' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>156</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>geopotential_height</dd><dt><span>GRIB_cfVarName :</span></dt><dd>gh</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Geopotential height</dd><dt><span>GRIB_shortName :</span></dt><dd>gh</dd><dt><span>GRIB_units :</span></dt><dd>gpm</dd><dt><span>long_name :</span></dt><dd>Geopotential height</dd><dt><span>units :</span></dt><dd>gpm</dd><dt><span>standard_name :</span></dt><dd>geopotential_height</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> 4.27 GiB </td>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray></div><input id='attrs-687de181-f49a-4582-9030-b965c9ea7f07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-687de181-f49a-4582-9030-b965c9ea7f07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4c5fdcb-ad72-4786-a3f4-1d656fc8c5f7' class='xr-var-data-in' type='checkbox'><label for='data-d4c5fdcb-ad72-4786-a3f4-1d656fc8c5f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>130</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>air_temperature</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>t</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>air_temperature</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> 4.27 GiB </td>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
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| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
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| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " <tr>\n", | |
| " <td>\n", | |
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| " <tr>\n", | |
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| " <th> Chunk </th>\n", | |
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| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 336.65 MiB </td>\n", | |
| " <td> 336.65 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 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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| " <tr>\n", | |
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| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 336.65 MiB </td>\n", | |
| " <td> 336.65 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " <td> (85, 721, 1440) </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>t2m</span></div><div class='xr-var-dims'>(valid_time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 721, 1440), meta=np.ndarray></div><input id='attrs-e626b0cb-3408-4631-aed7-6505bd04be94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e626b0cb-3408-4631-aed7-6505bd04be94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88124744-3416-4652-b049-da953a5b408a' class='xr-var-data-in' type='checkbox'><label for='data-88124744-3416-4652-b049-da953a5b408a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>air_temperature</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
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| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 336.65 MiB </td>\n", | |
| " <td> 336.65 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
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| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
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| " <th> Chunk </th>\n", | |
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| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 336.65 MiB </td>\n", | |
| " <td> 336.65 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 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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| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
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| " <th> Chunk </th>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 336.65 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
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| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
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| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " </tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcwv</span></div><div class='xr-var-dims'>(valid_time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 721, 1440), meta=np.ndarray></div><input id='attrs-9581d747-4bf0-452c-919f-2b4e5a0b39d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9581d747-4bf0-452c-919f-2b4e5a0b39d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66ec65bb-de9d-430c-92a2-1a96dad5f463' class='xr-var-data-in' type='checkbox'><label for='data-66ec65bb-de9d-430c-92a2-1a96dad5f463' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>137</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>entireAtmosphere</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>lwe_thickness_of_atmosphere_mass_content_of_water_vapor</dd><dt><span>GRIB_cfVarName :</span></dt><dd>tcwv</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total column vertically-integrated water vapour</dd><dt><span>GRIB_shortName :</span></dt><dd>tcwv</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total column vertically-integrated water vapour</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>standard_name :</span></dt><dd>lwe_thickness_of_atmosphere_mass_content_of_water_vapor</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> 336.65 MiB </td>\n", | |
| " <td> 336.65 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>q</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray></div><input id='attrs-dfcc9cb8-f5c7-4c8d-bc1d-71bd411f20a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dfcc9cb8-f5c7-4c8d-bc1d-71bd411f20a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88a59530-6740-480b-9034-9a05f391efbc' class='xr-var-data-in' type='checkbox'><label for='data-88a59530-6740-480b-9034-9a05f391efbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>133</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>specific_humidity</dd><dt><span>GRIB_cfVarName :</span></dt><dd>q</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Specific humidity</dd><dt><span>GRIB_shortName :</span></dt><dd>q</dd><dt><span>GRIB_units :</span></dt><dd>kg kg**-1</dd><dt><span>long_name :</span></dt><dd>Specific humidity</dd><dt><span>units :</span></dt><dd>kg kg**-1</dd><dt><span>standard_name :</span></dt><dd>specific_humidity</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " </tbody>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vo</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray></div><input id='attrs-9d79e881-60c3-4873-a15a-35e2d1ce05a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d79e881-60c3-4873-a15a-35e2d1ce05a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b21a8632-78cf-41a4-84b3-8391a361ca19' class='xr-var-data-in' type='checkbox'><label for='data-b21a8632-78cf-41a4-84b3-8391a361ca19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>138</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>atmosphere_relative_vorticity</dd><dt><span>GRIB_cfVarName :</span></dt><dd>vo</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Vorticity (relative)</dd><dt><span>GRIB_shortName :</span></dt><dd>vo</dd><dt><span>GRIB_units :</span></dt><dd>s**-1</dd><dt><span>long_name :</span></dt><dd>Vorticity (relative)</dd><dt><span>units :</span></dt><dd>s**-1</dd><dt><span>standard_name :</span></dt><dd>atmosphere_relative_vorticity</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> 4.27 GiB </td>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " </tbody>\n", | |
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| " </td>\n", | |
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| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " <td> 4.27 GiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " <td> (85, 13, 721, 1440) </td>\n", | |
| " </tr>\n", | |
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| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 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", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
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| " <tr>\n", | |
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| " <th> Chunk </th>\n", | |
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| " <tbody>\n", | |
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| " <tr>\n", | |
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| " <td> 336.65 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
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| " <tr>\n", | |
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| " <text x=\"10.445162\" y=\"90.528495\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,10.445162,90.528495)\">85</text>\n", | |
| "</svg>\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u10</span></div><div class='xr-var-dims'>(valid_time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 721, 1440), meta=np.ndarray></div><input id='attrs-d1a34b90-71d2-4f0a-b00c-574d14e0b0ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1a34b90-71d2-4f0a-b00c-574d14e0b0ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ad3f54b-e95d-415c-b051-eadb4475b151' class='xr-var-data-in' type='checkbox'><label for='data-5ad3f54b-e95d-415c-b051-eadb4475b151' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>165</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>eastward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>u10</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>10 metre U wind component</dd><dt><span>GRIB_shortName :</span></dt><dd>10u</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>10 metre U wind component</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</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> 336.65 MiB </td>\n", | |
| " <td> 336.65 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
| " <svg width=\"200\" height=\"130\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"30\" y2=\"20\" style=\"stroke-width:2\" />\n", | |
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| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" style=\"stroke-width:2\" />\n", | |
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| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
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| "\n", | |
| " <!-- Horizontal lines -->\n", | |
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| "\n", | |
| " <!-- Vertical lines -->\n", | |
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| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"30\" y1=\"20\" x2=\"150\" y2=\"20\" style=\"stroke-width:2\" />\n", | |
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| " <!-- Vertical lines -->\n", | |
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| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"90.890324\" y=\"100.973657\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n", | |
| " <text x=\"170.890324\" y=\"50.931991\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,170.890324,50.931991)\">721</text>\n", | |
| " <text x=\"10.445162\" y=\"90.528495\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,10.445162,90.528495)\">85</text>\n", | |
| "</svg>\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v10</span></div><div class='xr-var-dims'>(valid_time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 721, 1440), meta=np.ndarray></div><input id='attrs-005a53c0-461c-44e1-ab52-8c05921a53a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-005a53c0-461c-44e1-ab52-8c05921a53a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adbd62bc-98e8-437c-a121-828925001e4c' class='xr-var-data-in' type='checkbox'><label for='data-adbd62bc-98e8-437c-a121-828925001e4c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>nan</dd><dt><span>GRIB_paramId :</span></dt><dd>166</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>northward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>v10</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>10 metre V wind component</dd><dt><span>GRIB_shortName :</span></dt><dd>10v</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>10 metre V wind component</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>northward_wind</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> 336.65 MiB </td>\n", | |
| " <td> 336.65 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " <td> (85, 721, 1440) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
| " <svg width=\"200\" height=\"130\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"30\" y2=\"20\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"10\" y1=\"60\" x2=\"30\" y2=\"80\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"60\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"30\" y1=\"20\" x2=\"30\" y2=\"80\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"10.0,0.0 30.890324101119315,20.890324101119315 30.890324101119315,80.97365743445265 10.0,60.083333333333336\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
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| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"10\" y1=\"0\" x2=\"30\" y2=\"20\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"130\" y1=\"0\" x2=\"150\" y2=\"20\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
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| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"30\" y1=\"20\" x2=\"150\" y2=\"20\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"30\" y1=\"80\" x2=\"150\" y2=\"80\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"30\" y1=\"20\" x2=\"30\" y2=\"80\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"150\" y1=\"20\" x2=\"150\" y2=\"80\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"30.890324101119315,20.890324101119315 150.89032410111932,20.890324101119315 150.89032410111932,80.97365743445265 30.890324101119315,80.97365743445265\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"90.890324\" y=\"100.973657\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n", | |
| " <text x=\"170.890324\" y=\"50.931991\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,170.890324,50.931991)\">721</text>\n", | |
| " <text x=\"10.445162\" y=\"90.528495\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,10.445162,90.528495)\">85</text>\n", | |
| "</svg>\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-55c661a3-daf3-4cd3-bb32-efe63d361245' class='xr-section-summary-in' type='checkbox' ><label for='section-55c661a3-daf3-4cd3-bb32-efe63d361245' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>isobaricInhPa</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-a80cb7be-3c11-4414-9508-e6b59328dc91' class='xr-index-data-in' type='checkbox'/><label for='index-a80cb7be-3c11-4414-9508-e6b59328dc91' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1000.0, 925.0, 850.0, 700.0, 600.0, 500.0, 400.0, 300.0, 250.0,\n", | |
| " 200.0, 150.0, 100.0, 50.0],\n", | |
| " dtype='float64', name='isobaricInhPa'))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-718c7aee-f625-4832-84b3-baf30c66144e' class='xr-index-data-in' type='checkbox'/><label for='index-718c7aee-f625-4832-84b3-baf30c66144e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 90.0, 89.75, 89.5, 89.25, 89.0, 88.75, 88.5, 88.25, 88.0,\n", | |
| " 87.75,\n", | |
| " ...\n", | |
| " -87.75, -88.0, -88.25, -88.5, -88.75, -89.0, -89.25, -89.5, -89.75,\n", | |
| " -90.0],\n", | |
| " dtype='float64', name='latitude', length=721))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-ac59af91-3b38-42f1-9ff1-78dd8d60c995' class='xr-index-data-in' type='checkbox'/><label for='index-ac59af91-3b38-42f1-9ff1-78dd8d60c995' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -180.0, -179.75, -179.5, -179.25, -179.0, -178.75, -178.5, -178.25,\n", | |
| " -178.0, -177.75,\n", | |
| " ...\n", | |
| " 177.5, 177.75, 178.0, 178.25, 178.5, 178.75, 179.0, 179.25,\n", | |
| " 179.5, 179.75],\n", | |
| " dtype='float64', name='longitude', length=1440))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>valid_time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b72b2da7-8877-4c83-bf74-8665c9d523b9' class='xr-index-data-in' type='checkbox'/><label for='index-b72b2da7-8877-4c83-bf74-8665c9d523b9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2025-01-30 00:00:00', '2025-01-30 03:00:00',\n", | |
| " '2025-01-30 06:00:00', '2025-01-30 09:00:00',\n", | |
| " '2025-01-30 12:00:00', '2025-01-30 15:00:00',\n", | |
| " '2025-01-30 18:00:00', '2025-01-30 21:00:00',\n", | |
| " '2025-01-31 00:00:00', '2025-01-31 03:00:00',\n", | |
| " '2025-01-31 06:00:00', '2025-01-31 09:00:00',\n", | |
| " '2025-01-31 12:00:00', '2025-01-31 15:00:00',\n", | |
| " '2025-01-31 18:00:00', '2025-01-31 21:00:00',\n", | |
| " '2025-02-01 00:00:00', '2025-02-01 03:00:00',\n", | |
| " '2025-02-01 06:00:00', '2025-02-01 09:00:00',\n", | |
| " '2025-02-01 12:00:00', '2025-02-01 15:00:00',\n", | |
| " '2025-02-01 18:00:00', '2025-02-01 21:00:00',\n", | |
| " '2025-02-02 00:00:00', '2025-02-02 03:00:00',\n", | |
| " '2025-02-02 06:00:00', '2025-02-02 09:00:00',\n", | |
| " '2025-02-02 12:00:00', '2025-02-02 15:00:00',\n", | |
| " '2025-02-02 18:00:00', '2025-02-02 21:00:00',\n", | |
| " '2025-02-03 00:00:00', '2025-02-03 03:00:00',\n", | |
| " '2025-02-03 06:00:00', '2025-02-03 09:00:00',\n", | |
| " '2025-02-03 12:00:00', '2025-02-03 15:00:00',\n", | |
| " '2025-02-03 18:00:00', '2025-02-03 21:00:00',\n", | |
| " '2025-02-04 00:00:00', '2025-02-04 03:00:00',\n", | |
| " '2025-02-04 06:00:00', '2025-02-04 09:00:00',\n", | |
| " '2025-02-04 12:00:00', '2025-02-04 15:00:00',\n", | |
| " '2025-02-04 18:00:00', '2025-02-04 21:00:00',\n", | |
| " '2025-02-05 00:00:00', '2025-02-05 06:00:00',\n", | |
| " '2025-02-05 12:00:00', '2025-02-05 18:00:00',\n", | |
| " '2025-02-06 00:00:00', '2025-02-06 06:00:00',\n", | |
| " '2025-02-06 12:00:00', '2025-02-06 18:00:00',\n", | |
| " '2025-02-07 00:00:00', '2025-02-07 06:00:00',\n", | |
| " '2025-02-07 12:00:00', '2025-02-07 18:00:00',\n", | |
| " '2025-02-08 00:00:00', '2025-02-08 06:00:00',\n", | |
| " '2025-02-08 12:00:00', '2025-02-08 18:00:00',\n", | |
| " '2025-02-09 00:00:00', '2025-02-09 06:00:00',\n", | |
| " '2025-02-09 12:00:00', '2025-02-09 18:00:00',\n", | |
| " '2025-02-10 00:00:00', '2025-02-10 06:00:00',\n", | |
| " '2025-02-10 12:00:00', '2025-02-10 18:00:00',\n", | |
| " '2025-02-11 00:00:00', '2025-02-11 06:00:00',\n", | |
| " '2025-02-11 12:00:00', '2025-02-11 18:00:00',\n", | |
| " '2025-02-12 00:00:00', '2025-02-12 06:00:00',\n", | |
| " '2025-02-12 12:00:00', '2025-02-12 18:00:00',\n", | |
| " '2025-02-13 00:00:00', '2025-02-13 06:00:00',\n", | |
| " '2025-02-13 12:00:00', '2025-02-13 18:00:00',\n", | |
| " '2025-02-14 00:00:00'],\n", | |
| " dtype='datetime64[ns]', name='valid_time', freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1bba3bca-8286-492f-97f9-e83cfd2bfd1b' class='xr-section-summary-in' type='checkbox' checked><label for='section-1bba3bca-8286-492f-97f9-e83cfd2bfd1b' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2025-01-30T23:01 GRIB to CDM+CF via cfgrib-0.9.14.1/ecCodes-2.38.3 with {"source": "20250130000000-0h-oper-fc.grib2", "filter_by_keys": {"cfVarName": "u"}, "encode_cf": ["parameter", "time", "geography", "vertical"]}</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.Dataset> Size: 40GB\n", | |
| "Dimensions: (valid_time: 85, isobaricInhPa: 13, latitude: 721,\n", | |
| " longitude: 1440)\n", | |
| "Coordinates:\n", | |
| " time datetime64[ns] 8B ...\n", | |
| " step (valid_time) timedelta64[ns] 680B dask.array<chunksize=(85,), meta=np.ndarray>\n", | |
| " * isobaricInhPa (isobaricInhPa) float64 104B 1e+03 925.0 ... 100.0 50.0\n", | |
| " * latitude (latitude) float64 6kB 90.0 89.75 89.5 ... -89.75 -90.0\n", | |
| " * longitude (longitude) float64 12kB -180.0 -179.8 ... 179.5 179.8\n", | |
| " * valid_time (valid_time) datetime64[ns] 680B 2025-01-30 ... 2025-0...\n", | |
| " surface float64 8B ...\n", | |
| " heightAboveGround float64 8B ...\n", | |
| " meanSea float64 8B ...\n", | |
| " entireAtmosphere float64 8B ...\n", | |
| "Data variables: (12/17)\n", | |
| " u (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " v (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " r (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " gh (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " t (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " tp (valid_time, latitude, longitude) float32 353MB dask.array<chunksize=(85, 721, 1440), meta=np.ndarray>\n", | |
| " ... ...\n", | |
| " q (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " vo (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " d (valid_time, isobaricInhPa, latitude, longitude) float32 5GB dask.array<chunksize=(85, 13, 721, 1440), meta=np.ndarray>\n", | |
| " ro (valid_time, latitude, longitude) float32 353MB dask.array<chunksize=(85, 721, 1440), meta=np.ndarray>\n", | |
| " u10 (valid_time, latitude, longitude) float32 353MB dask.array<chunksize=(85, 721, 1440), meta=np.ndarray>\n", | |
| " v10 (valid_time, latitude, longitude) float32 353MB dask.array<chunksize=(85, 721, 1440), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " GRIB_edition: 2\n", | |
| " GRIB_centre: ecmf\n", | |
| " GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts\n", | |
| " GRIB_subCentre: 0\n", | |
| " Conventions: CF-1.7\n", | |
| " institution: European Centre for Medium-Range Weather Forecasts\n", | |
| " history: 2025-01-30T23:01 GRIB to CDM+CF via cfgrib-0.9.1..." | |
| ] | |
| }, | |
| "execution_count": 2, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "ds = xr.open_dataset('/home/anderson/ecmwrf.nc', engine='netcdf4', decode_cf=True, chunks={}, mask_and_scale=False)#.isel(valid_time=slice(5))\n", | |
| "ds" | |
| ] | |
| }, | |
| { | |
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| "execution_count": 3, | |
| "id": "9f5ed1b9-e2a0-4ebe-9677-a2dcbe0294fc", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "ds = ds.rio.write_crs('EPSG:4326')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "id": "670d47df-99c7-4744-93e3-fd64d367b3af", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "pyramid = ndpyramid.pyramid_reproject(ds, levels=1, extra_dim=\"valid_time\")" | |
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| "execution_count": 5, | |
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| ".xr-attrs,\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data,\n", | |
| ".xr-index-data {\n", | |
| " grid-column: 1 / -1;\n", | |
| "}\n", | |
| "\n", | |
| "dl.xr-attrs {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 125px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt,\n", | |
| ".xr-attrs dd {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " float: left;\n", | |
| " padding-right: 10px;\n", | |
| " width: auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt {\n", | |
| " font-weight: normal;\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt:hover span {\n", | |
| " display: inline-block;\n", | |
| " background: var(--xr-background-color);\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dd {\n", | |
| " grid-column: 2;\n", | |
| " white-space: pre-wrap;\n", | |
| " word-break: break-all;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-icon-database,\n", | |
| ".xr-icon-file-text2,\n", | |
| ".xr-no-icon {\n", | |
| " display: inline-block;\n", | |
| " vertical-align: middle;\n", | |
| " width: 1em;\n", | |
| " height: 1.5em !important;\n", | |
| " stroke-width: 0;\n", | |
| " stroke: currentColor;\n", | |
| " fill: currentColor;\n", | |
| "}\n", | |
| "</style><pre class='xr-text-repr-fallback'><xarray.DatasetView> Size: 0B\n", | |
| "Dimensions: ()\n", | |
| "Data variables:\n", | |
| " *empty*\n", | |
| "Attributes:\n", | |
| " multiscales: [{'datasets': [{'path': '0', 'level': 0, 'crs': 'EPSG:3857'...\n", | |
| " title: multiscale data pyramid\n", | |
| " version: 0.4.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataTree</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-869b0582-c43a-40b2-9442-7de09c9e8860' class='xr-section-summary-in' type='checkbox' ><label for='section-869b0582-c43a-40b2-9442-7de09c9e8860' class='xr-section-summary' >Groups: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'><div style='display: inline-grid; grid-template-columns: 0px 20px auto; width: 100%;'><div style='grid-column-start: 1;border-right: 0.2em solid;border-color: var(--xr-border-color);height: 1.2em;width: 0px;'></div><div style='grid-column-start: 2;grid-row-start: 1;height: 1em;width: 20px;border-bottom: 0.2em solid;border-color: var(--xr-border-color);'></div><div style='grid-column-start: 3;'><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", | |
| "<defs>\n", | |
| "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n", | |
| "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n", | |
| "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", | |
| "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", | |
| "</symbol>\n", | |
| "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n", | |
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| "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n", | |
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| "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n", | |
| "</symbol>\n", | |
| "</defs>\n", | |
| "</svg>\n", | |
| "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n", | |
| " *\n", | |
| " */\n", | |
| "\n", | |
| ":root {\n", | |
| " --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n", | |
| " --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n", | |
| " --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n", | |
| " --xr-border-color: var(--jp-border-color2, #e0e0e0);\n", | |
| " --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n", | |
| " --xr-background-color: var(--jp-layout-color0, white);\n", | |
| " --xr-background-color-row-even: var(--jp-layout-color1, white);\n", | |
| " --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n", | |
| "}\n", | |
| "\n", | |
| "html[theme=\"dark\"],\n", | |
| "html[data-theme=\"dark\"],\n", | |
| "body[data-theme=\"dark\"],\n", | |
| "body.vscode-dark {\n", | |
| " --xr-font-color0: rgba(255, 255, 255, 1);\n", | |
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| " --xr-font-color3: rgba(255, 255, 255, 0.38);\n", | |
| " --xr-border-color: #1f1f1f;\n", | |
| " --xr-disabled-color: #515151;\n", | |
| " --xr-background-color: #111111;\n", | |
| " --xr-background-color-row-even: #111111;\n", | |
| " --xr-background-color-row-odd: #313131;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-wrap {\n", | |
| " display: block !important;\n", | |
| " min-width: 300px;\n", | |
| " max-width: 700px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-text-repr-fallback {\n", | |
| " /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n", | |
| " display: none;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-header {\n", | |
| " padding-top: 6px;\n", | |
| " padding-bottom: 6px;\n", | |
| " margin-bottom: 4px;\n", | |
| " border-bottom: solid 1px var(--xr-border-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-header > div,\n", | |
| ".xr-header > ul {\n", | |
| " display: inline;\n", | |
| " margin-top: 0;\n", | |
| " margin-bottom: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-obj-type,\n", | |
| ".xr-array-name {\n", | |
| " margin-left: 2px;\n", | |
| " margin-right: 10px;\n", | |
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| "\n", | |
| ".xr-obj-type {\n", | |
| " color: var(--xr-font-color2);\n", | |
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| "\n", | |
| ".xr-sections {\n", | |
| " padding-left: 0 !important;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\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", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input + label {\n", | |
| " color: var(--xr-disabled-color);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input:enabled + label {\n", | |
| " cursor: pointer;\n", | |
| " color: var(--xr-font-color2);\n", | |
| "}\n", | |
| "\n", | |
| ".xr-section-item input:focus + label {\n", | |
| " border: 2px solid var(--xr-font-color0);\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", | |
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| "\n", | |
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| " display: inline-block;\n", | |
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| " font-size: 11px;\n", | |
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| "\n", | |
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| " 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", | |
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| "\n", | |
| ".xr-section-summary,\n", | |
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| " padding-top: 4px;\n", | |
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| "\n", | |
| ".xr-section-inline-details {\n", | |
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| "\n", | |
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| "\n", | |
| ".xr-section-summary-in:checked ~ .xr-section-details {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-wrap {\n", | |
| " grid-column: 1 / -1;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 20px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-array-wrap > label {\n", | |
| " grid-column: 1;\n", | |
| " vertical-align: top;\n", | |
| "}\n", | |
| "\n", | |
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| " 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", | |
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| "\n", | |
| ".xr-dim-list {\n", | |
| " display: inline-block !important;\n", | |
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| "\n", | |
| ".xr-dim-list li {\n", | |
| " display: inline-block;\n", | |
| " padding: 0;\n", | |
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| "\n", | |
| ".xr-dim-list:before {\n", | |
| " content: \"(\";\n", | |
| "}\n", | |
| "\n", | |
| ".xr-dim-list:after {\n", | |
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| "}\n", | |
| "\n", | |
| ".xr-has-index {\n", | |
| " font-weight: bold;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list,\n", | |
| ".xr-var-item {\n", | |
| " display: contents;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > div,\n", | |
| ".xr-var-item label,\n", | |
| ".xr-var-item > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-even);\n", | |
| " margin-bottom: 0;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-item > .xr-var-name:hover span {\n", | |
| " padding-right: 5px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-list > li:nth-child(odd) > div,\n", | |
| ".xr-var-list > li:nth-child(odd) > label,\n", | |
| ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n", | |
| " background-color: var(--xr-background-color-row-odd);\n", | |
| "}\n", | |
| "\n", | |
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| "\n", | |
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| " grid-column: 2 / 5;\n", | |
| " color: var(--xr-font-color2);\n", | |
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| ".xr-var-name:hover,\n", | |
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| "\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data,\n", | |
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| " display: none;\n", | |
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| "}\n", | |
| "\n", | |
| ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n", | |
| ".xr-var-data-in:checked ~ .xr-var-data,\n", | |
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| "\n", | |
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| " float: right;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-var-name span,\n", | |
| ".xr-var-data,\n", | |
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| " padding-left: 25px !important;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs,\n", | |
| ".xr-var-attrs,\n", | |
| ".xr-var-data,\n", | |
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| "\n", | |
| "dl.xr-attrs {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " display: grid;\n", | |
| " grid-template-columns: 125px auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt,\n", | |
| ".xr-attrs dd {\n", | |
| " padding: 0;\n", | |
| " margin: 0;\n", | |
| " float: left;\n", | |
| " padding-right: 10px;\n", | |
| " width: auto;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt {\n", | |
| " font-weight: normal;\n", | |
| " grid-column: 1;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dt:hover span {\n", | |
| " display: inline-block;\n", | |
| " background: var(--xr-background-color);\n", | |
| " padding-right: 10px;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-attrs dd {\n", | |
| " grid-column: 2;\n", | |
| " white-space: pre-wrap;\n", | |
| " word-break: break-all;\n", | |
| "}\n", | |
| "\n", | |
| ".xr-icon-database,\n", | |
| ".xr-icon-file-text2,\n", | |
| ".xr-no-icon {\n", | |
| " display: inline-block;\n", | |
| " vertical-align: middle;\n", | |
| " width: 1em;\n", | |
| " height: 1.5em !important;\n", | |
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| " stroke: currentColor;\n", | |
| " fill: currentColor;\n", | |
| "}\n", | |
| "</style><pre class='xr-text-repr-fallback'><xarray.DatasetView> Size: 629MB\n", | |
| "Dimensions: (valid_time: 85, isobaricInhPa: 13, y: 128, x: 128)\n", | |
| "Coordinates:\n", | |
| " * x (x) float32 512B -1.988e+07 -1.957e+07 ... 1.988e+07\n", | |
| " * y (y) float32 512B 1.988e+07 1.957e+07 ... -1.988e+07\n", | |
| " * valid_time (valid_time) datetime64[ns] 680B 2025-01-30 ... 2025-0...\n", | |
| " time datetime64[ns] 8B 2025-01-30\n", | |
| " step (valid_time) int32 340B dask.array<chunksize=(85,), meta=np.ndarray>\n", | |
| " meanSea float32 4B 0.0\n", | |
| " surface float32 4B 0.0\n", | |
| " * isobaricInhPa (isobaricInhPa) float32 52B 1e+03 925.0 ... 100.0 50.0\n", | |
| " heightAboveGround float32 4B 2.0\n", | |
| " entireAtmosphere float32 4B 0.0\n", | |
| " spatial_ref int32 4B 0\n", | |
| "Data variables: (12/17)\n", | |
| " u (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " v (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " r (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " gh (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " t (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " tp (valid_time, y, x) float32 6MB dask.array<chunksize=(85, 128, 128), meta=np.ndarray>\n", | |
| " ... ...\n", | |
| " q (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " vo (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " d (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " ro (valid_time, y, x) float32 6MB dask.array<chunksize=(85, 128, 128), meta=np.ndarray>\n", | |
| " u10 (valid_time, y, x) float32 6MB dask.array<chunksize=(85, 128, 128), meta=np.ndarray>\n", | |
| " v10 (valid_time, y, x) float32 6MB dask.array<chunksize=(85, 128, 128), meta=np.ndarray>\n", | |
| "Attributes:\n", | |
| " GRIB_edition: 2\n", | |
| " GRIB_centre: ecmf\n", | |
| " GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts\n", | |
| " GRIB_subCentre: 0\n", | |
| " Conventions: CF-1.7\n", | |
| " institution: European Centre for Medium-Range Weather Forecasts\n", | |
| " history: 2025-01-30T23:01 GRIB to CDM+CF via cfgrib-0.9.1...\n", | |
| " multiscales: [{'datasets': [{'path': '.', 'level': 0, 'crs': ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>0</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7f472c44-b459-468f-a404-7a3a4e3ad058' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7f472c44-b459-468f-a404-7a3a4e3ad058' class='xr-section-summary' title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'></div></div></li><li class='xr-section-item'><input id='section-acd2ebdb-f1a5-4862-8a3f-c912c2578137' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-acd2ebdb-f1a5-4862-8a3f-c912c2578137' 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'>valid_time</span>: 85</li><li><span class='xr-has-index'>isobaricInhPa</span>: 13</li><li><span class='xr-has-index'>y</span>: 128</li><li><span class='xr-has-index'>x</span>: 128</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-72f8adbc-afe2-4cb8-9340-d2fc369d973f' class='xr-section-summary-in' type='checkbox' checked><label for='section-72f8adbc-afe2-4cb8-9340-d2fc369d973f' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.988e+07 -1.957e+07 ... 1.988e+07</div><input id='attrs-4a9dd3d3-dfab-4a09-9b6d-de08a20cd929' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a9dd3d3-dfab-4a09-9b6d-de08a20cd929' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7dfa317-b420-465c-ade4-1709a9d4c9a7' class='xr-var-data-in' type='checkbox'><label for='data-a7dfa317-b420-465c-ade4-1709a9d4c9a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([-19880966. , -19567880. , -19254794. , -18941708. , -18628622. ,\n", | |
| " -18315534. , -18002448. , -17689362. , -17376276. , -17063190. ,\n", | |
| " -16750105. , -16437019. , -16123932. , -15810846. , -15497760. ,\n", | |
| " -15184674. , -14871588. , -14558502. , -14245416. , -13932330. ,\n", | |
| " -13619244. , -13306158. , -12993072. , -12679986. , -12366900. ,\n", | |
| " -12053814. , -11740728. , -11427641. , -11114555. , -10801469. ,\n", | |
| " -10488383. , -10175297. , -9862211. , -9549125. , -9236039. ,\n", | |
| " -8922953. , -8609867. , -8296781. , -7983694.5 , -7670608.5 ,\n", | |
| " -7357522.5 , -7044436.5 , -6731350.5 , -6418264.5 , -6105178.5 ,\n", | |
| " -5792092.5 , -5479006. , -5165920. , -4852834. , -4539748. ,\n", | |
| " -4226662. , -3913575.8 , -3600489.8 , -3287403.8 , -2974317.8 ,\n", | |
| " -2661231.5 , -2348145.5 , -2035059.5 , -1721973.4 , -1408887.2 ,\n", | |
| " -1095801.2 , -782715.2 , -469629.1 , -156543.03, 156543.03,\n", | |
| " 469629.1 , 782715.2 , 1095801.2 , 1408887.2 , 1721973.4 ,\n", | |
| " 2035059.5 , 2348145.5 , 2661231.5 , 2974317.8 , 3287403.8 ,\n", | |
| " 3600489.8 , 3913575.8 , 4226662. , 4539748. , 4852834. ,\n", | |
| " 5165920. , 5479006. , 5792092.5 , 6105178.5 , 6418264.5 ,\n", | |
| " 6731350.5 , 7044436.5 , 7357522.5 , 7670608.5 , 7983694.5 ,\n", | |
| " 8296781. , 8609867. , 8922953. , 9236039. , 9549125. ,\n", | |
| " 9862211. , 10175297. , 10488383. , 10801469. , 11114555. ,\n", | |
| " 11427641. , 11740728. , 12053814. , 12366900. , 12679986. ,\n", | |
| " 12993072. , 13306158. , 13619244. , 13932330. , 14245416. ,\n", | |
| " 14558502. , 14871588. , 15184674. , 15497760. , 15810846. ,\n", | |
| " 16123932. , 16437019. , 16750105. , 17063190. , 17376276. ,\n", | |
| " 17689362. , 18002448. , 18315534. , 18628622. , 18941708. ,\n", | |
| " 19254794. , 19567880. , 19880966. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.988e+07 1.957e+07 ... -1.988e+07</div><input id='attrs-439f7190-60ce-4120-a85a-40ac44162f6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-439f7190-60ce-4120-a85a-40ac44162f6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ea565d2-5edd-484f-989b-45b196a92a9d' class='xr-var-data-in' type='checkbox'><label for='data-2ea565d2-5edd-484f-989b-45b196a92a9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd></dl></div><div class='xr-var-data'><pre>array([ 19880966. , 19567880. , 19254794. , 18941708. , 18628622. ,\n", | |
| " 18315534. , 18002448. , 17689362. , 17376276. , 17063190. ,\n", | |
| " 16750105. , 16437019. , 16123932. , 15810846. , 15497760. ,\n", | |
| " 15184674. , 14871588. , 14558502. , 14245416. , 13932330. ,\n", | |
| " 13619244. , 13306158. , 12993072. , 12679986. , 12366900. ,\n", | |
| " 12053814. , 11740728. , 11427641. , 11114555. , 10801469. ,\n", | |
| " 10488383. , 10175297. , 9862211. , 9549125. , 9236039. ,\n", | |
| " 8922953. , 8609867. , 8296781. , 7983694.5 , 7670608.5 ,\n", | |
| " 7357522.5 , 7044436.5 , 6731350.5 , 6418264.5 , 6105178.5 ,\n", | |
| " 5792092.5 , 5479006. , 5165920. , 4852834. , 4539748. ,\n", | |
| " 4226662. , 3913575.8 , 3600489.8 , 3287403.8 , 2974317.8 ,\n", | |
| " 2661231.5 , 2348145.5 , 2035059.5 , 1721973.4 , 1408887.2 ,\n", | |
| " 1095801.2 , 782715.2 , 469629.1 , 156543.03, -156543.03,\n", | |
| " -469629.1 , -782715.2 , -1095801.2 , -1408887.2 , -1721973.4 ,\n", | |
| " -2035059.5 , -2348145.5 , -2661231.5 , -2974317.8 , -3287403.8 ,\n", | |
| " -3600489.8 , -3913575.8 , -4226662. , -4539748. , -4852834. ,\n", | |
| " -5165920. , -5479006. , -5792092.5 , -6105178.5 , -6418264.5 ,\n", | |
| " -6731350.5 , -7044436.5 , -7357522.5 , -7670608.5 , -7983694.5 ,\n", | |
| " -8296781. , -8609867. , -8922953. , -9236039. , -9549125. ,\n", | |
| " -9862211. , -10175297. , -10488383. , -10801469. , -11114555. ,\n", | |
| " -11427641. , -11740728. , -12053814. , -12366900. , -12679986. ,\n", | |
| " -12993072. , -13306158. , -13619244. , -13932330. , -14245416. ,\n", | |
| " -14558502. , -14871588. , -15184674. , -15497760. , -15810846. ,\n", | |
| " -16123932. , -16437019. , -16750105. , -17063190. , -17376276. ,\n", | |
| " -17689362. , -18002448. , -18315534. , -18628622. , -18941708. ,\n", | |
| " -19254794. , -19567880. , -19880966. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>valid_time</span></div><div class='xr-var-dims'>(valid_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2025-01-30 ... 2025-02-14</div><input id='attrs-24777444-f76b-4813-8da8-29d54b1b9cc0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24777444-f76b-4813-8da8-29d54b1b9cc0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f978334f-7d5d-4585-8e12-3bcaef5fa5de' class='xr-var-data-in' type='checkbox'><label for='data-f978334f-7d5d-4585-8e12-3bcaef5fa5de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(['2025-01-30T00:00:00.000000000', '2025-01-30T03:00:00.000000000',\n", | |
| " '2025-01-30T06:00:00.000000000', '2025-01-30T09:00:00.000000000',\n", | |
| " '2025-01-30T12:00:00.000000000', '2025-01-30T15:00:00.000000000',\n", | |
| " '2025-01-30T18:00:00.000000000', '2025-01-30T21:00:00.000000000',\n", | |
| " '2025-01-31T00:00:00.000000000', '2025-01-31T03:00:00.000000000',\n", | |
| " '2025-01-31T06:00:00.000000000', '2025-01-31T09:00:00.000000000',\n", | |
| " '2025-01-31T12:00:00.000000000', '2025-01-31T15:00:00.000000000',\n", | |
| " '2025-01-31T18:00:00.000000000', '2025-01-31T21:00:00.000000000',\n", | |
| " '2025-02-01T00:00:00.000000000', '2025-02-01T03:00:00.000000000',\n", | |
| " '2025-02-01T06:00:00.000000000', '2025-02-01T09:00:00.000000000',\n", | |
| " '2025-02-01T12:00:00.000000000', '2025-02-01T15:00:00.000000000',\n", | |
| " '2025-02-01T18:00:00.000000000', '2025-02-01T21:00:00.000000000',\n", | |
| " '2025-02-02T00:00:00.000000000', '2025-02-02T03:00:00.000000000',\n", | |
| " '2025-02-02T06:00:00.000000000', '2025-02-02T09:00:00.000000000',\n", | |
| " '2025-02-02T12:00:00.000000000', '2025-02-02T15:00:00.000000000',\n", | |
| " '2025-02-02T18:00:00.000000000', '2025-02-02T21:00:00.000000000',\n", | |
| " '2025-02-03T00:00:00.000000000', '2025-02-03T03:00:00.000000000',\n", | |
| " '2025-02-03T06:00:00.000000000', '2025-02-03T09:00:00.000000000',\n", | |
| " '2025-02-03T12:00:00.000000000', '2025-02-03T15:00:00.000000000',\n", | |
| " '2025-02-03T18:00:00.000000000', '2025-02-03T21:00:00.000000000',\n", | |
| " '2025-02-04T00:00:00.000000000', '2025-02-04T03:00:00.000000000',\n", | |
| " '2025-02-04T06:00:00.000000000', '2025-02-04T09:00:00.000000000',\n", | |
| " '2025-02-04T12:00:00.000000000', '2025-02-04T15:00:00.000000000',\n", | |
| " '2025-02-04T18:00:00.000000000', '2025-02-04T21:00:00.000000000',\n", | |
| " '2025-02-05T00:00:00.000000000', '2025-02-05T06:00:00.000000000',\n", | |
| " '2025-02-05T12:00:00.000000000', '2025-02-05T18:00:00.000000000',\n", | |
| " '2025-02-06T00:00:00.000000000', '2025-02-06T06:00:00.000000000',\n", | |
| " '2025-02-06T12:00:00.000000000', '2025-02-06T18:00:00.000000000',\n", | |
| " '2025-02-07T00:00:00.000000000', '2025-02-07T06:00:00.000000000',\n", | |
| " '2025-02-07T12:00:00.000000000', '2025-02-07T18:00:00.000000000',\n", | |
| " '2025-02-08T00:00:00.000000000', '2025-02-08T06:00:00.000000000',\n", | |
| " '2025-02-08T12:00:00.000000000', '2025-02-08T18:00:00.000000000',\n", | |
| " '2025-02-09T00:00:00.000000000', '2025-02-09T06:00:00.000000000',\n", | |
| " '2025-02-09T12:00:00.000000000', '2025-02-09T18:00:00.000000000',\n", | |
| " '2025-02-10T00:00:00.000000000', '2025-02-10T06:00:00.000000000',\n", | |
| " '2025-02-10T12:00:00.000000000', '2025-02-10T18:00:00.000000000',\n", | |
| " '2025-02-11T00:00:00.000000000', '2025-02-11T06:00:00.000000000',\n", | |
| " '2025-02-11T12:00:00.000000000', '2025-02-11T18:00:00.000000000',\n", | |
| " '2025-02-12T00:00:00.000000000', '2025-02-12T06:00:00.000000000',\n", | |
| " '2025-02-12T12:00:00.000000000', '2025-02-12T18:00:00.000000000',\n", | |
| " '2025-02-13T00:00:00.000000000', '2025-02-13T06:00:00.000000000',\n", | |
| " '2025-02-13T12:00:00.000000000', '2025-02-13T18:00:00.000000000',\n", | |
| " '2025-02-14T00:00:00.000000000'], dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2025-01-30</div><input id='attrs-b4f094e0-bd20-4d33-bab9-914a9d6a28b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4f094e0-bd20-4d33-bab9-914a9d6a28b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28c5fb80-6034-4cf0-8d8c-b3289472d702' class='xr-var-data-in' type='checkbox'><label for='data-28c5fb80-6034-4cf0-8d8c-b3289472d702' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array('2025-01-30T00:00:00.000000000', dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>(valid_time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85,), meta=np.ndarray></div><input id='attrs-87d95f4c-f0e3-4278-a359-7a624a6d75b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87d95f4c-f0e3-4278-a359-7a624a6d75b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3129818f-f629-42e8-ad4b-733c547baedd' class='xr-var-data-in' type='checkbox'><label for='data-3129818f-f629-42e8-ad4b-733c547baedd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><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> 340 B </td>\n", | |
| " <td> 340 B </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85,) </td>\n", | |
| " <td> (85,) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> int32 numpy.ndarray </td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| " </table>\n", | |
| " </td>\n", | |
| " <td>\n", | |
| " <svg width=\"170\" height=\"76\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"26\" x2=\"120\" y2=\"26\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"26\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"26\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.0,0.0 120.0,0.0 120.0,26.207589997831487 0.0,26.207589997831487\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"60.000000\" y=\"46.207590\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >85</text>\n", | |
| " <text x=\"140.000000\" y=\"13.103795\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,13.103795)\">1</text>\n", | |
| "</svg>\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>meanSea</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-d3cb84a8-3a0b-4501-89ee-8af6d3309611' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3cb84a8-3a0b-4501-89ee-8af6d3309611' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-932e7244-1818-4a07-a7a4-a97d973f847f' class='xr-var-data-in' type='checkbox'><label for='data-932e7244-1818-4a07-a7a4-a97d973f847f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(meanSea)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(0., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-327ddf7c-19ff-426c-80b1-e98215531842' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-327ddf7c-19ff-426c-80b1-e98215531842' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfc79651-274e-44fe-8981-e9a49229db0a' class='xr-var-data-in' type='checkbox'><label for='data-cfc79651-274e-44fe-8981-e9a49229db0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(surface)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(0., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>isobaricInhPa</span></div><div class='xr-var-dims'>(isobaricInhPa)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1e+03 925.0 850.0 ... 100.0 50.0</div><input id='attrs-4453313a-c540-445d-9491-0fd227c31c00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4453313a-c540-445d-9491-0fd227c31c00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2adfc1ac-e0c7-4b7c-9ea6-514a1592b0d8' class='xr-var-data-in' type='checkbox'><label for='data-2adfc1ac-e0c7-4b7c-9ea6-514a1592b0d8' title='Show/Hide data repr'><svg 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>pressure</dd><dt><span>units :</span></dt><dd>hPa</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><pre>array([1000., 925., 850., 700., 600., 500., 400., 300., 250., 200.,\n", | |
| " 150., 100., 50.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heightAboveGround</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-311a5b93-def7-4b08-9c11-8f4209f3b790' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-311a5b93-def7-4b08-9c11-8f4209f3b790' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef1bc322-addd-4620-b081-1c71c714e461' class='xr-var-data-in' type='checkbox'><label for='data-ef1bc322-addd-4620-b081-1c71c714e461' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>height above the surface</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>entireAtmosphere</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-cbee7e07-5dd7-4eb4-9de5-9f8165ee1089' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbee7e07-5dd7-4eb4-9de5-9f8165ee1089' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a01f68f-1f3e-44e4-bc7d-d54f2b724659' class='xr-var-data-in' type='checkbox'><label for='data-1a01f68f-1f3e-44e4-bc7d-d54f2b724659' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(entireAtmosphere)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array(0., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-acc591b8-f2a9-4fa6-9b85-c66c8e8d1323' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acc591b8-f2a9-4fa6-9b85-c66c8e8d1323' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f99237a-7da7-43de-9902-e84e624126a1' class='xr-var-data-in' type='checkbox'><label for='data-5f99237a-7da7-43de-9902-e84e624126a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS["WGS 84 / Pseudo-Mercator",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Mercator_1SP"],PARAMETER["central_meridian",0],PARAMETER["scale_factor",1],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],EXTENSION["PROJ4","+proj=merc +a=6378137 +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null +wktext +no_defs"],AUTHORITY["EPSG","3857"]]</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS["WGS 84 / Pseudo-Mercator",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Mercator_1SP"],PARAMETER["central_meridian",0],PARAMETER["scale_factor",1],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],EXTENSION["PROJ4","+proj=merc +a=6378137 +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null +wktext +no_defs"],AUTHORITY["EPSG","3857"]]</dd><dt><span>GeoTransform :</span></dt><dd>-20037508.342789244 313086.06785608194 0.0 20037508.342789248 0.0 -313086.067856082</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a9ee0b93-fde0-483b-9e07-c9eb88a5ff6e' class='xr-section-summary-in' type='checkbox' ><label for='section-a9ee0b93-fde0-483b-9e07-c9eb88a5ff6e' class='xr-section-summary' >Data variables: <span>(17)</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>u</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray></div><input id='attrs-6a8b570a-664f-4729-95fe-276186ec35d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a8b570a-664f-4729-95fe-276186ec35d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e275b89-7362-4ac4-a2d0-c81681b2cd9a' class='xr-var-data-in' type='checkbox'><label for='data-6e275b89-7362-4ac4-a2d0-c81681b2cd9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>131</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>eastward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>u</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>U component of wind</dd><dt><span>GRIB_shortName :</span></dt><dd>u</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</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> 69.06 MiB </td>\n", | |
| " <td> 69.06 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 128, 128) </td>\n", | |
| " <td> (85, 13, 128, 128) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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=\"490\" height=\"192\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"79\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"0\" y1=\"25\" x2=\"79\" y2=\"25\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"79\" y1=\"0\" x2=\"79\" y2=\"25\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"0.0,0.0 79.6875,0.0 79.6875,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"39.843750\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >85</text>\n", | |
| " <text x=\"99.687500\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,99.687500,12.706308)\">1</text>\n", | |
| "\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"149\" y1=\"0\" x2=\"171\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"149\" y1=\"120\" x2=\"171\" y2=\"142\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"149\" y1=\"0\" x2=\"149\" y2=\"120\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"171\" y1=\"22\" x2=\"171\" y2=\"142\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"149.0,0.0 171.75447671348599,22.754476713485992 171.75447671348599,142.75447671348599 149.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"149\" y1=\"0\" x2=\"269\" y2=\"0\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"171\" y1=\"22\" x2=\"291\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"149\" y1=\"0\" x2=\"171\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"269\" y1=\"0\" x2=\"291\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"149.0,0.0 269.0,0.0 291.754476713486,22.754476713485992 171.75447671348599,22.754476713485992\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Horizontal lines -->\n", | |
| " <line x1=\"171\" y1=\"22\" x2=\"291\" y2=\"22\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"171\" y1=\"142\" x2=\"291\" y2=\"142\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Vertical lines -->\n", | |
| " <line x1=\"171\" y1=\"22\" x2=\"171\" y2=\"142\" style=\"stroke-width:2\" />\n", | |
| " <line x1=\"291\" y1=\"22\" x2=\"291\" y2=\"142\" style=\"stroke-width:2\" />\n", | |
| "\n", | |
| " <!-- Colored Rectangle -->\n", | |
| " <polygon points=\"171.75447671348599,22.754476713485992 291.754476713486,22.754476713485992 291.754476713486,142.75447671348599 171.75447671348599,142.75447671348599\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", | |
| "\n", | |
| " <!-- Text -->\n", | |
| " <text x=\"231.754477\" y=\"162.754477\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >128</text>\n", | |
| " <text x=\"311.754477\" y=\"82.754477\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,311.754477,82.754477)\">128</text>\n", | |
| " <text x=\"150.377238\" y=\"151.377238\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,150.377238,151.377238)\">13</text>\n", | |
| "</svg>\n", | |
| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray></div><input id='attrs-47833d47-a46f-4654-b809-6469d59fbf5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47833d47-a46f-4654-b809-6469d59fbf5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14336da8-4bcc-4745-96a0-e997d3bd8c73' class='xr-var-data-in' type='checkbox'><label for='data-14336da8-4bcc-4745-96a0-e997d3bd8c73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>132</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>northward_wind</dd><dt><span>GRIB_cfVarName :</span></dt><dd>v</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>V component of wind</dd><dt><span>GRIB_shortName :</span></dt><dd>v</dd><dt><span>GRIB_units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>V component of wind</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>standard_name :</span></dt><dd>northward_wind</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> 69.06 MiB </td>\n", | |
| " <td> 69.06 MiB </td>\n", | |
| " </tr>\n", | |
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| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 128, 128) </td>\n", | |
| " <td> (85, 13, 128, 128) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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>r</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray></div><input id='attrs-71333a5b-af28-47d1-af91-d7d2b72bad5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71333a5b-af28-47d1-af91-d7d2b72bad5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a005a25-3abf-4cf8-9593-a69c63a94e16' class='xr-var-data-in' type='checkbox'><label for='data-8a005a25-3abf-4cf8-9593-a69c63a94e16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>157</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>relative_humidity</dd><dt><span>GRIB_cfVarName :</span></dt><dd>r</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Relative humidity</dd><dt><span>GRIB_shortName :</span></dt><dd>r</dd><dt><span>GRIB_units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Relative humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>standard_name :</span></dt><dd>relative_humidity</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 69.06 MiB </td>\n", | |
| " <td> 69.06 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 128, 128) </td>\n", | |
| " <td> (85, 13, 128, 128) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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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| " </tbody>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gh</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray></div><input id='attrs-598514a3-793a-4c9a-9eca-26af14bae897' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-598514a3-793a-4c9a-9eca-26af14bae897' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d3c550c-376d-4612-8c92-f9f3cf7587ec' class='xr-var-data-in' type='checkbox'><label for='data-2d3c550c-376d-4612-8c92-f9f3cf7587ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>156</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>geopotential_height</dd><dt><span>GRIB_cfVarName :</span></dt><dd>gh</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Geopotential height</dd><dt><span>GRIB_shortName :</span></dt><dd>gh</dd><dt><span>GRIB_units :</span></dt><dd>gpm</dd><dt><span>long_name :</span></dt><dd>Geopotential height</dd><dt><span>units :</span></dt><dd>gpm</dd><dt><span>standard_name :</span></dt><dd>geopotential_height</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> 69.06 MiB </td>\n", | |
| " <td> 69.06 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
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| " <td> (85, 13, 128, 128) </td>\n", | |
| " <td> (85, 13, 128, 128) </td>\n", | |
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| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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>t</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray></div><input id='attrs-abe346d4-83b4-4158-bfe9-65f8150b9859' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abe346d4-83b4-4158-bfe9-65f8150b9859' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6f72579-7615-4c73-807f-81071ed22fd2' class='xr-var-data-in' type='checkbox'><label for='data-d6f72579-7615-4c73-807f-81071ed22fd2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>130</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>air_temperature</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>t</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>air_temperature</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> 69.06 MiB </td>\n", | |
| " <td> 69.06 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 13, 128, 128) </td>\n", | |
| " <td> (85, 13, 128, 128) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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>tp</span></div><div class='xr-var-dims'>(valid_time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 128, 128), meta=np.ndarray></div><input id='attrs-3212681c-03c6-46b8-bc70-88c20f6b1fb0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3212681c-03c6-46b8-bc70-88c20f6b1fb0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6995f594-92d4-43c1-b851-33a3657aaa5e' class='xr-var-data-in' type='checkbox'><label for='data-6995f594-92d4-43c1-b851-33a3657aaa5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>228</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>tp</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><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> 5.31 MiB </td>\n", | |
| " <td> 5.31 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " </tbody>\n", | |
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| "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>skt</span></div><div class='xr-var-dims'>(valid_time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 128, 128), meta=np.ndarray></div><input id='attrs-b4d8e479-c456-45cd-96d1-830b25f53012' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4d8e479-c456-45cd-96d1-830b25f53012' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20f8d689-4abd-4bb2-8dab-dd56ef1de5b7' class='xr-var-data-in' type='checkbox'><label for='data-20f8d689-4abd-4bb2-8dab-dd56ef1de5b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>235</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>skt</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Skin temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>skt</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Skin temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><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> 5.31 MiB </td>\n", | |
| " <td> 5.31 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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>t2m</span></div><div class='xr-var-dims'>(valid_time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 128, 128), meta=np.ndarray></div><input id='attrs-dd3f95b5-9a81-4d23-a4b2-b6bd6d447f3c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd3f95b5-9a81-4d23-a4b2-b6bd6d447f3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98c583c3-78be-40f1-aa6c-e23c8a693184' class='xr-var-data-in' type='checkbox'><label for='data-98c583c3-78be-40f1-aa6c-e23c8a693184' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>air_temperature</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
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| " <tr>\n", | |
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| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 5.31 MiB </td>\n", | |
| " <td> 5.31 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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>sp</span></div><div class='xr-var-dims'>(valid_time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 128, 128), meta=np.ndarray></div><input id='attrs-45816330-017c-4117-9ca4-ee98393e9974' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45816330-017c-4117-9ca4-ee98393e9974' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f076a798-87a5-42fd-aa8d-69de60210e7c' class='xr-var-data-in' type='checkbox'><label for='data-f076a798-87a5-42fd-aa8d-69de60210e7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>134</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>surface_air_pressure</dd><dt><span>GRIB_cfVarName :</span></dt><dd>sp</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Surface pressure</dd><dt><span>GRIB_shortName :</span></dt><dd>sp</dd><dt><span>GRIB_units :</span></dt><dd>Pa</dd><dt><span>long_name :</span></dt><dd>Surface pressure</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>standard_name :</span></dt><dd>surface_air_pressure</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 5.31 MiB </td>\n", | |
| " <td> 5.31 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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>msl</span></div><div class='xr-var-dims'>(valid_time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 128, 128), meta=np.ndarray></div><input id='attrs-58ce868b-d634-4710-ac16-2fe5e2fb2c7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58ce868b-d634-4710-ac16-2fe5e2fb2c7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0f9ab43-9835-4721-94c3-6c137c5f708f' class='xr-var-data-in' type='checkbox'><label for='data-c0f9ab43-9835-4721-94c3-6c137c5f708f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>151</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>air_pressure_at_mean_sea_level</dd><dt><span>GRIB_cfVarName :</span></dt><dd>msl</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Mean sea level pressure</dd><dt><span>GRIB_shortName :</span></dt><dd>msl</dd><dt><span>GRIB_units :</span></dt><dd>Pa</dd><dt><span>long_name :</span></dt><dd>Mean sea level pressure</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>standard_name :</span></dt><dd>air_pressure_at_mean_sea_level</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> 5.31 MiB </td>\n", | |
| " <td> 5.31 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </td>\n", | |
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| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 5.31 MiB </td>\n", | |
| " <td> 5.31 MiB </td>\n", | |
| " </tr>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
| " <td> (85, 128, 128) </td>\n", | |
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| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th> Data type </th>\n", | |
| " <td colspan=\"2\"> float32 numpy.ndarray </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>vo</span></div><div class='xr-var-dims'>(valid_time, isobaricInhPa, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray></div><input id='attrs-566e2b50-95c6-4b9d-b2ea-306018ef3357' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-566e2b50-95c6-4b9d-b2ea-306018ef3357' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e340bf7-1cd3-4a92-a16e-2445d6a4e2b6' class='xr-var-data-in' type='checkbox'><label for='data-1e340bf7-1cd3-4a92-a16e-2445d6a4e2b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>138</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>atmosphere_relative_vorticity</dd><dt><span>GRIB_cfVarName :</span></dt><dd>vo</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>180.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>179.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Vorticity (relative)</dd><dt><span>GRIB_shortName :</span></dt><dd>vo</dd><dt><span>GRIB_units :</span></dt><dd>s**-1</dd><dt><span>long_name :</span></dt><dd>Vorticity (relative)</dd><dt><span>units :</span></dt><dd>s**-1</dd><dt><span>standard_name :</span></dt><dd>atmosphere_relative_vorticity</dd></dl></div><div class='xr-var-data'><table>\n", | |
| " <tr>\n", | |
| " <td>\n", | |
| " <table style=\"border-collapse: collapse;\">\n", | |
| " <thead>\n", | |
| " <tr>\n", | |
| " <td> </td>\n", | |
| " <th> Array </th>\n", | |
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| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 69.06 MiB </td>\n", | |
| " <td> 69.06 MiB </td>\n", | |
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| " <tr>\n", | |
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| " <td> (85, 13, 128, 128) </td>\n", | |
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| " <tr>\n", | |
| " <th> Dask graph </th>\n", | |
| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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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| " <thead>\n", | |
| " <tr>\n", | |
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| " <th> Array </th>\n", | |
| " <th> Chunk </th>\n", | |
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| " </thead>\n", | |
| " <tbody>\n", | |
| " \n", | |
| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
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| " <td> 69.06 MiB </td>\n", | |
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| " <td> (85, 13, 128, 128) </td>\n", | |
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| " <td colspan=\"2\"> 1 chunks in 1 graph layer </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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| " <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> 5.31 MiB </td>\n", | |
| " <td> 5.31 MiB </td>\n", | |
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| " \n", | |
| " <tr>\n", | |
| " <th> Shape </th>\n", | |
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| " <td> (85, 128, 128) </td>\n", | |
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| " <tr>\n", | |
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| " <tr>\n", | |
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| " <tr>\n", | |
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| " <tbody>\n", | |
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| " <tr>\n", | |
| " <th> Bytes </th>\n", | |
| " <td> 5.31 MiB </td>\n", | |
| " <td> 5.31 MiB </td>\n", | |
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| " <tr>\n", | |
| " <th> Shape </th>\n", | |
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| " <td> (85, 128, 128) </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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| " <tr>\n", | |
| " <td>\n", | |
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| " <tr>\n", | |
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| " <tbody>\n", | |
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| " <tr>\n", | |
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| " <td> 5.31 MiB </td>\n", | |
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| " </td>\n", | |
| " </tr>\n", | |
| "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-dcc6833a-cfef-426a-acc8-6b6a67a18c57' class='xr-section-summary-in' type='checkbox' checked><label for='section-dcc6833a-cfef-426a-acc8-6b6a67a18c57' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2025-01-30T23:01 GRIB to CDM+CF via cfgrib-0.9.14.1/ecCodes-2.38.3 with {"source": "20250130000000-0h-oper-fc.grib2", "filter_by_keys": {"cfVarName": "u"}, "encode_cf": ["parameter", "time", "geography", "vertical"]}</dd><dt><span>multiscales :</span></dt><dd>[{'datasets': [{'path': '.', 'level': 0, 'crs': 'EPSG:3857'}], 'type': 'reduce', 'metadata': {'method': 'pyramid_reproject', 'version': '0.4.0', 'args': [], 'kwargs': {'level': 0, 'pixels_per_tile': 128, 'projection': 'web-mercator', 'resampling': 'average', 'extra_dim': 'valid_time', 'clear_attrs': False}}}]</dd></dl></div></li></ul></div></div></div></div></div></div></li><li class='xr-section-item'><input id='section-8f4572c8-3937-43ac-a6c4-d9f2397daeb1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8f4572c8-3937-43ac-a6c4-d9f2397daeb1' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-83d8d834-892d-4802-afa0-b9bf6643e19d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-83d8d834-892d-4802-afa0-b9bf6643e19d' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-1f52f37b-1992-4c6d-bd08-cfa3a1dfc9da' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1f52f37b-1992-4c6d-bd08-cfa3a1dfc9da' class='xr-section-summary' title='Expand/collapse section'>Inherited coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-292c8cdb-1811-4aa4-8b3d-d85d1c3712f8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-292c8cdb-1811-4aa4-8b3d-d85d1c3712f8' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-b1866505-bef8-4ad5-8187-4a8c282e93cf' class='xr-section-summary-in' type='checkbox' checked><label for='section-b1866505-bef8-4ad5-8187-4a8c282e93cf' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>multiscales :</span></dt><dd>[{'datasets': [{'path': '0', 'level': 0, 'crs': 'EPSG:3857', 'pixels_per_tile': 128}], 'type': 'reduce', 'metadata': {'method': 'pyramid_reproject', 'version': '0.4.0', 'args': [], 'kwargs': {'levels': 1, 'pixels_per_tile': 128, 'projection': 'web-mercator', 'other_chunks': None, 'resampling': 'average', 'extra_dim': 'valid_time', 'clear_attrs': False}}}]</dd><dt><span>title :</span></dt><dd>multiscale data pyramid</dd><dt><span>version :</span></dt><dd>0.4.0</dd></dl></div></li></ul></div></div>" | |
| ], | |
| "text/plain": [ | |
| "<xarray.DataTree>\n", | |
| "Group: /\n", | |
| "│ Attributes:\n", | |
| "│ multiscales: [{'datasets': [{'path': '0', 'level': 0, 'crs': 'EPSG:3857'...\n", | |
| "│ title: multiscale data pyramid\n", | |
| "│ version: 0.4.0\n", | |
| "└── Group: /0\n", | |
| " Dimensions: (valid_time: 85, isobaricInhPa: 13, y: 128, x: 128)\n", | |
| " Coordinates:\n", | |
| " * x (x) float32 512B -1.988e+07 -1.957e+07 ... 1.988e+07\n", | |
| " * y (y) float32 512B 1.988e+07 1.957e+07 ... -1.988e+07\n", | |
| " * valid_time (valid_time) datetime64[ns] 680B 2025-01-30 ... 2025-0...\n", | |
| " time datetime64[ns] 8B 2025-01-30\n", | |
| " step (valid_time) int32 340B dask.array<chunksize=(85,), meta=np.ndarray>\n", | |
| " meanSea float32 4B 0.0\n", | |
| " surface float32 4B 0.0\n", | |
| " * isobaricInhPa (isobaricInhPa) float32 52B 1e+03 925.0 ... 100.0 50.0\n", | |
| " heightAboveGround float32 4B 2.0\n", | |
| " entireAtmosphere float32 4B 0.0\n", | |
| " spatial_ref int32 4B 0\n", | |
| " Data variables: (12/17)\n", | |
| " u (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " v (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " r (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " gh (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " t (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " tp (valid_time, y, x) float32 6MB dask.array<chunksize=(85, 128, 128), meta=np.ndarray>\n", | |
| " ... ...\n", | |
| " q (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " vo (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " d (valid_time, isobaricInhPa, y, x) float32 72MB dask.array<chunksize=(85, 13, 128, 128), meta=np.ndarray>\n", | |
| " ro (valid_time, y, x) float32 6MB dask.array<chunksize=(85, 128, 128), meta=np.ndarray>\n", | |
| " u10 (valid_time, y, x) float32 6MB dask.array<chunksize=(85, 128, 128), meta=np.ndarray>\n", | |
| " v10 (valid_time, y, x) float32 6MB dask.array<chunksize=(85, 128, 128), meta=np.ndarray>\n", | |
| " Attributes:\n", | |
| " GRIB_edition: 2\n", | |
| " GRIB_centre: ecmf\n", | |
| " GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts\n", | |
| " GRIB_subCentre: 0\n", | |
| " Conventions: CF-1.7\n", | |
| " institution: European Centre for Medium-Range Weather Forecasts\n", | |
| " history: 2025-01-30T23:01 GRIB to CDM+CF via cfgrib-0.9.1...\n", | |
| " multiscales: [{'datasets': [{'path': '.', 'level': 0, 'crs': ..." | |
| ] | |
| }, | |
| "execution_count": 5, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "pyramid" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "id": "14e7e024-81dc-4130-9f27-b86ca0e49f35", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "pyramid.to_zarr('/tmp/ecmwf_pyramid.zarr', consolidated=True, mode='w')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 7, | |
| "id": "c4f500ba-2d1a-4905-918f-8d80b8879343", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "\n", | |
| "INSTALLED VERSIONS\n", | |
| "------------------\n", | |
| "commit: None\n", | |
| "python: 3.13.2 | packaged by conda-forge | (main, Feb 17 2025, 14:10:22) [GCC 13.3.0]\n", | |
| "python-bits: 64\n", | |
| "OS: Linux\n", | |
| "OS-release: 5.10.219-208.866.amzn2.x86_64\n", | |
| "machine: x86_64\n", | |
| "processor: x86_64\n", | |
| "byteorder: little\n", | |
| "LC_ALL: C.UTF-8\n", | |
| "LANG: C.UTF-8\n", | |
| "LOCALE: ('C', 'UTF-8')\n", | |
| "libhdf5: 1.14.4\n", | |
| "libnetcdf: 4.9.2\n", | |
| "\n", | |
| "xarray: 2025.1.2\n", | |
| "pandas: 2.2.3\n", | |
| "numpy: 2.1.3\n", | |
| "scipy: 1.15.2\n", | |
| "netCDF4: 1.7.2\n", | |
| "pydap: None\n", | |
| "h5netcdf: None\n", | |
| "h5py: None\n", | |
| "zarr: 2.18.4\n", | |
| "cftime: 1.6.4\n", | |
| "nc_time_axis: 1.4.1\n", | |
| "iris: None\n", | |
| "bottleneck: None\n", | |
| "dask: 2025.2.0\n", | |
| "distributed: 2025.2.0\n", | |
| "matplotlib: 3.10.1\n", | |
| "cartopy: 0.24.0\n", | |
| "seaborn: None\n", | |
| "numbagg: None\n", | |
| "fsspec: 2025.3.0\n", | |
| "cupy: None\n", | |
| "pint: None\n", | |
| "sparse: 0.15.5\n", | |
| "flox: None\n", | |
| "numpy_groupies: None\n", | |
| "setuptools: 75.8.2\n", | |
| "pip: None\n", | |
| "conda: None\n", | |
| "pytest: None\n", | |
| "mypy: None\n", | |
| "IPython: 9.0.2\n", | |
| "sphinx: None\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "xr.show_versions()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "id": "e4bd8702-fb57-4299-9574-7c237057f830", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<xarray.plot.facetgrid.FacetGrid at 0x7f48459c9590>" | |
| ] | |
| }, | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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