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Pangeo Cloud CESM2 example
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max_grover_CESM_example.ipynb
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"cells": [
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"cell_type": "code",
"execution_count": 1,
"id": "gothic-azerbaijan",
"metadata": {},
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"source": [
"import intake\n",
"\n",
"col = intake.open_esm_datastore(\"https://storage.googleapis.com/cmip6/pangeo-cmip6.json\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "stylish-cologne",
"metadata": {},
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"text": [
"\n",
"--> The keys in the returned dictionary of datasets are constructed as follows:\n",
"\t'activity_id.institution_id.source_id.experiment_id.table_id.grid_label'\n"
]
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (d2: 2, lev: 60, member_id: 1, nlat: 384, nlon: 320, time: 1980, vertices: 4)\n",
"Coordinates:\n",
" lat (nlat, nlon) float64 dask.array&lt;chunksize=(384, 320), meta=np.ndarray&gt;\n",
" lat_bnds (nlat, nlon, vertices) float32 dask.array&lt;chunksize=(384, 320, 4), meta=np.ndarray&gt;\n",
" * lev (lev) float64 500.0 1.5e+03 2.5e+03 ... 5.125e+05 5.375e+05\n",
" lev_bnds (lev, d2) float32 dask.array&lt;chunksize=(60, 2), meta=np.ndarray&gt;\n",
" lon (nlat, nlon) float64 dask.array&lt;chunksize=(384, 320), meta=np.ndarray&gt;\n",
" lon_bnds (nlat, nlon, vertices) float32 dask.array&lt;chunksize=(384, 320, 4), meta=np.ndarray&gt;\n",
" * nlat (nlat) int32 1 2 3 4 5 6 7 8 ... 377 378 379 380 381 382 383 384\n",
" * nlon (nlon) int32 1 2 3 4 5 6 7 8 ... 313 314 315 316 317 318 319 320\n",
" * time (time) object 1850-01-15 12:59:59.999997 ... 2014-12-15 12:00:00\n",
" time_bnds (time, d2) object dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
" * member_id (member_id) &lt;U8 &#x27;r1i1p1f1&#x27;\n",
"Dimensions without coordinates: d2, vertices\n",
"Data variables:\n",
" thetao (member_id, time, lev, nlat, nlon) float32 dask.array&lt;chunksize=(1, 8, 60, 384, 320), meta=np.ndarray&gt;\n",
"Attributes:\n",
" Conventions: CF-1.7 CMIP-6.2\n",
" activity_id: CMIP\n",
" branch_method: standard\n",
" branch_time_in_child: 674885.0\n",
" branch_time_in_parent: 219000.0\n",
" case_id: 15\n",
" cesm_casename: b.e21.BHIST.f09_g17.CMIP6-historical.001\n",
" contact: [email protected]\n",
" creation_date: 2019-01-16T22:01:19Z\n",
" data_specs_version: 01.00.29\n",
" experiment: all-forcing simulation of the recent past\n",
" experiment_id: historical\n",
" external_variables: areacello volcello\n",
" forcing_index: 1\n",
" frequency: mon\n",
" further_info_url: https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2....\n",
" grid: native gx1v7 displaced pole grid (384x320 latxlon)\n",
" grid_label: gn\n",
" initialization_index: 1\n",
" institution: National Center for Atmospheric Research, Climat...\n",
" institution_id: NCAR\n",
" license: CMIP6 model data produced by &lt;The National Cente...\n",
" mip_era: CMIP6\n",
" model_doi_url: https://doi.org/10.5065/D67H1H0V\n",
" nominal_resolution: 100 km\n",
" parent_activity_id: CMIP\n",
" parent_experiment_id: piControl\n",
" parent_mip_era: CMIP6\n",
" parent_source_id: CESM2\n",
" parent_time_units: days since 0001-01-01 00:00:00\n",
" parent_variant_label: r1i1p1f1\n",
" physics_index: 1\n",
" product: model-output\n",
" realization_index: 1\n",
" realm: ocean\n",
" source: CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite ...\n",
" source_id: CESM2\n",
" source_type: AOGCM BGC\n",
" sub_experiment: none\n",
" sub_experiment_id: none\n",
" table_id: Omon\n",
" tracking_id: hdl:21.14100/672d35cd-e662-4807-8dee-7d7d5e1d4d1c\n",
" variable_id: thetao\n",
" variant_info: CMIP6 20th century experiments (1850-2014) with ...\n",
" variant_label: r1i1p1f1\n",
" status: 2019-10-25;created;by [email protected]\n",
" netcdf_tracking_ids: hdl:21.14100/672d35cd-e662-4807-8dee-7d7d5e1d4d1c\n",
" version_id: v20190308\n",
" intake_esm_varname: [&#x27;thetao&#x27;]\n",
" intake_esm_dataset_key: CMIP.NCAR.CESM2.historical.Omon.gn</pre><div class='xr-wrap' hidden><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-d5bde86a-b697-4492-9c6b-a1ec8e3bb12f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d5bde86a-b697-4492-9c6b-a1ec8e3bb12f' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>d2</span>: 2</li><li><span class='xr-has-index'>lev</span>: 60</li><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>nlat</span>: 384</li><li><span class='xr-has-index'>nlon</span>: 320</li><li><span class='xr-has-index'>time</span>: 1980</li><li><span>vertices</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2acd88f3-ccd1-4e7a-af80-7ce9fdde58a5' class='xr-section-summary-in' type='checkbox' checked><label for='section-2acd88f3-ccd1-4e7a-af80-7ce9fdde58a5' 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>lat</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(384, 320), meta=np.ndarray&gt;</div><input id='attrs-660421f8-c8ae-4329-bb90-30777b5fbcfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-660421f8-c8ae-4329-bb90-30777b5fbcfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bafa503-15dd-47eb-abcb-11e0a62911a3' class='xr-var-data-in' type='checkbox'><label for='data-7bafa503-15dd-47eb-abcb-11e0a62911a3' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>title :</span></dt><dd>Latitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><table>\n",
"<tr>\n",
"<td>\n",
"<table>\n",
" <thead>\n",
" <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr><th> Bytes </th><td> 983.04 kB </td> <td> 983.04 kB </td></tr>\n",
" <tr><th> Shape </th><td> (384, 320) </td> <td> (384, 320) </td></tr>\n",
" <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
" <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
" </tbody>\n",
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"</td>\n",
"<td>\n",
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"</tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(nlat, nlon, vertices)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(384, 320, 4), meta=np.ndarray&gt;</div><input id='attrs-8f14fd14-4405-4870-b12e-f760cec3696c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f14fd14-4405-4870-b12e-f760cec3696c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-700a2b26-d11b-4642-abb5-314d3808fd03' class='xr-var-data-in' type='checkbox'><label for='data-700a2b26-d11b-4642-abb5-314d3808fd03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
"<tr>\n",
"<td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>500.0 1.5e+03 ... 5.375e+05</div><input id='attrs-3bfd2578-095e-4db9-917c-6970f7ef4f10' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bfd2578-095e-4db9-917c-6970f7ef4f10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e763cc99-1e62-4040-ad91-a4ad369bf8a7' class='xr-var-data-in' type='checkbox'><label for='data-e763cc99-1e62-4040-ad91-a4ad369bf8a7' 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>Z</dd><dt><span>bounds :</span></dt><dd>lev_bnds</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>olevel</dd><dt><span>title :</span></dt><dd>ocean model level</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>centimeters</dd></dl></div><div class='xr-var-data'><pre>array([5.000000e+02, 1.500000e+03, 2.500000e+03, 3.500000e+03, 4.500000e+03,\n",
" 5.500000e+03, 6.500000e+03, 7.500000e+03, 8.500000e+03, 9.500000e+03,\n",
" 1.050000e+04, 1.150000e+04, 1.250000e+04, 1.350000e+04, 1.450000e+04,\n",
" 1.550000e+04, 1.650984e+04, 1.754790e+04, 1.862913e+04, 1.976603e+04,\n",
" 2.097114e+04, 2.225783e+04, 2.364088e+04, 2.513702e+04, 2.676542e+04,\n",
" 2.854837e+04, 3.051192e+04, 3.268680e+04, 3.510935e+04, 3.782276e+04,\n",
" 4.087846e+04, 4.433777e+04, 4.827367e+04, 5.277280e+04, 5.793729e+04,\n",
" 6.388626e+04, 7.075633e+04, 7.870025e+04, 8.788252e+04, 9.847059e+04,\n",
" 1.106204e+05, 1.244567e+05, 1.400497e+05, 1.573946e+05, 1.764003e+05,\n",
" 1.968944e+05, 2.186457e+05, 2.413972e+05, 2.649001e+05, 2.889385e+05,\n",
" 3.133405e+05, 3.379793e+05, 3.627670e+05, 3.876452e+05, 4.125768e+05,\n",
" 4.375392e+05, 4.625190e+05, 4.875083e+05, 5.125028e+05, 5.375000e+05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bnds</span></div><div class='xr-var-dims'>(lev, d2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60, 2), meta=np.ndarray&gt;</div><input id='attrs-190bcd92-dea9-4dc4-b104-53d3297859c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-190bcd92-dea9-4dc4-b104-53d3297859c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e97a3da8-269c-4d3e-b173-383d86fdcb6a' class='xr-var-data-in' type='checkbox'><label for='data-e97a3da8-269c-4d3e-b173-383d86fdcb6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
"<tr>\n",
"<td>\n",
"<table>\n",
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" <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
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" <tbody>\n",
" <tr><th> Bytes </th><td> 480 B </td> <td> 480 B </td></tr>\n",
" <tr><th> Shape </th><td> (60, 2) </td> <td> (60, 2) </td></tr>\n",
" <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
" <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(nlat, nlon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(384, 320), meta=np.ndarray&gt;</div><input id='attrs-1e2a7565-be74-41c8-bf54-fbae9198356f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e2a7565-be74-41c8-bf54-fbae9198356f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f94befb8-e95c-478a-9861-d86386da9cde' class='xr-var-data-in' type='checkbox'><label for='data-f94befb8-e95c-478a-9861-d86386da9cde' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>title :</span></dt><dd>Longitude</dd><dt><span>type :</span></dt><dd>double</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><table>\n",
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"<td>\n",
"<table>\n",
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" <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
" </thead>\n",
" <tbody>\n",
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" <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
" <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(nlat, nlon, vertices)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(384, 320, 4), meta=np.ndarray&gt;</div><input id='attrs-edffc863-24ad-4599-9659-ec424a238531' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edffc863-24ad-4599-9659-ec424a238531' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a50cdfde-2327-42f3-877e-ad89942723b8' class='xr-var-data-in' type='checkbox'><label for='data-a50cdfde-2327-42f3-877e-ad89942723b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nlat</span></div><div class='xr-var-dims'>(nlat)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 ... 380 381 382 383 384</div><input id='attrs-78363a42-c4c7-41e7-ae0f-a98317c35390' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78363a42-c4c7-41e7-ae0f-a98317c35390' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0eefb6c6-7f6d-4f12-b905-05b7d39fa216' class='xr-var-data-in' type='checkbox'><label for='data-0eefb6c6-7f6d-4f12-b905-05b7d39fa216' 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>cell index along second dimension</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([ 1, 2, 3, ..., 382, 383, 384], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nlon</span></div><div class='xr-var-dims'>(nlon)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 ... 316 317 318 319 320</div><input id='attrs-26ffa65e-002d-4c2c-a4c5-15628caa46cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26ffa65e-002d-4c2c-a4c5-15628caa46cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ec1c411-ea69-4cb6-bb18-abde43ed6e1c' class='xr-var-data-in' type='checkbox'><label for='data-4ec1c411-ea69-4cb6-bb18-abde43ed6e1c' 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>cell index along first dimension</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([ 1, 2, 3, ..., 318, 319, 320], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-15 12:59:59.999997 ... 2...</div><input id='attrs-ae854e02-e646-49c9-a791-79cfef886815' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae854e02-e646-49c9-a791-79cfef886815' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c16a27e-443b-479b-aed8-01d30a25b9aa' class='xr-var-data-in' type='checkbox'><label for='data-3c16a27e-443b-479b-aed8-01d30a25b9aa' 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>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 15, 12, 59, 59, 999997),\n",
" cftime.DatetimeNoLeap(1850, 2, 14, 0, 0, 0, 0),\n",
" cftime.DatetimeNoLeap(1850, 3, 15, 12, 0, 0, 0), ...,\n",
" cftime.DatetimeNoLeap(2014, 10, 15, 12, 0, 0, 0),\n",
" cftime.DatetimeNoLeap(2014, 11, 15, 0, 0, 0, 0),\n",
" cftime.DatetimeNoLeap(2014, 12, 15, 12, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, d2)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-059af49c-90c4-4f4d-8bcf-2009de985c0e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-059af49c-90c4-4f4d-8bcf-2009de985c0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f35aad3b-1be9-4786-9b72-e633de97d2d2' class='xr-var-data-in' type='checkbox'><label for='data-f35aad3b-1be9-4786-9b72-e633de97d2d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>&lt;U8</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-f90fccc6-87d6-4a73-a02f-f1cf408fe175' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f90fccc6-87d6-4a73-a02f-f1cf408fe175' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75399193-111a-422d-b2ba-d0e160d5389f' class='xr-var-data-in' type='checkbox'><label for='data-75399193-111a-422d-b2ba-d0e160d5389f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=&#x27;&lt;U8&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-815fb2bb-1de4-4645-8dc8-d7ffa0284496' class='xr-section-summary-in' type='checkbox' checked><label for='section-815fb2bb-1de4-4645-8dc8-d7ffa0284496' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>thetao</span></div><div class='xr-var-dims'>(member_id, time, lev, nlat, nlon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 8, 60, 384, 320), meta=np.ndarray&gt;</div><input id='attrs-a057344a-0e71-465f-a057-c307bb1fa8d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a057344a-0e71-465f-a057-c307bb1fa8d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-406eb27c-149f-49f4-9955-18b75596a05a' class='xr-var-data-in' type='checkbox'><label for='data-406eb27c-149f-49f4-9955-18b75596a05a' 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>cell_measures :</span></dt><dd>area: areacello volume: volcello</dd><dt><span>cell_methods :</span></dt><dd>area: mean where sea time: mean</dd><dt><span>comment :</span></dt><dd>Diagnostic should be contributed even for models using conservative temperature as prognostic field.</dd><dt><span>description :</span></dt><dd>Diagnostic should be contributed even for models using conservative temperature as prognostic field.</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>thetao</dd><dt><span>long_name :</span></dt><dd>Sea Water Potential Temperature</dd><dt><span>mipTable :</span></dt><dd>Omon</dd><dt><span>out_name :</span></dt><dd>thetao</dd><dt><span>prov :</span></dt><dd>Omon ((isd.003))</dd><dt><span>realm :</span></dt><dd>ocean</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Sea Water Potential Temperature</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>variable_id :</span></dt><dd>thetao</dd></dl></div><div class='xr-var-data'><table>\n",
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-9d4228eb-67a1-4316-9333-9ef92e448237' class='xr-section-summary-in' type='checkbox' ><label for='section-9d4228eb-67a1-4316-9333-9ef92e448237' class='xr-section-summary' >Attributes: <span>(50)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>219000.0</dd><dt><span>case_id :</span></dt><dd>15</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.001</dd><dt><span>contact :</span></dt><dd>[email protected]</dd><dt><span>creation_date :</span></dt><dd>2019-01-16T22:01:19Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.29</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacello volcello</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native gx1v7 displaced pole grid (384x320 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; is licensed under a Creative Commons Attribution-[]ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file)[]. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CESM2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>ocean</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Omon</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/672d35cd-e662-4807-8dee-7d7d5e1d4d1c</dd><dt><span>variable_id :</span></dt><dd>thetao</dd><dt><span>variant_info :</span></dt><dd>CMIP6 20th century experiments (1850-2014) with CAM6, interactive land (CLM5), coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1)\r\n",
"</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by [email protected]</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/672d35cd-e662-4807-8dee-7d7d5e1d4d1c</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_varname :</span></dt><dd>[&#x27;thetao&#x27;]</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2.historical.Omon.gn</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (d2: 2, lev: 60, member_id: 1, nlat: 384, nlon: 320, time: 1980, vertices: 4)\n",
"Coordinates:\n",
" lat (nlat, nlon) float64 dask.array<chunksize=(384, 320), meta=np.ndarray>\n",
" lat_bnds (nlat, nlon, vertices) float32 dask.array<chunksize=(384, 320, 4), meta=np.ndarray>\n",
" * lev (lev) float64 500.0 1.5e+03 2.5e+03 ... 5.125e+05 5.375e+05\n",
" lev_bnds (lev, d2) float32 dask.array<chunksize=(60, 2), meta=np.ndarray>\n",
" lon (nlat, nlon) float64 dask.array<chunksize=(384, 320), meta=np.ndarray>\n",
" lon_bnds (nlat, nlon, vertices) float32 dask.array<chunksize=(384, 320, 4), meta=np.ndarray>\n",
" * nlat (nlat) int32 1 2 3 4 5 6 7 8 ... 377 378 379 380 381 382 383 384\n",
" * nlon (nlon) int32 1 2 3 4 5 6 7 8 ... 313 314 315 316 317 318 319 320\n",
" * time (time) object 1850-01-15 12:59:59.999997 ... 2014-12-15 12:00:00\n",
" time_bnds (time, d2) object dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
" * member_id (member_id) <U8 'r1i1p1f1'\n",
"Dimensions without coordinates: d2, vertices\n",
"Data variables:\n",
" thetao (member_id, time, lev, nlat, nlon) float32 dask.array<chunksize=(1, 8, 60, 384, 320), meta=np.ndarray>\n",
"Attributes:\n",
" Conventions: CF-1.7 CMIP-6.2\n",
" activity_id: CMIP\n",
" branch_method: standard\n",
" branch_time_in_child: 674885.0\n",
" branch_time_in_parent: 219000.0\n",
" case_id: 15\n",
" cesm_casename: b.e21.BHIST.f09_g17.CMIP6-historical.001\n",
" contact: [email protected]\n",
" creation_date: 2019-01-16T22:01:19Z\n",
" data_specs_version: 01.00.29\n",
" experiment: all-forcing simulation of the recent past\n",
" experiment_id: historical\n",
" external_variables: areacello volcello\n",
" forcing_index: 1\n",
" frequency: mon\n",
" further_info_url: https://furtherinfo.es-doc.org/CMIP6.NCAR.CESM2....\n",
" grid: native gx1v7 displaced pole grid (384x320 latxlon)\n",
" grid_label: gn\n",
" initialization_index: 1\n",
" institution: National Center for Atmospheric Research, Climat...\n",
" institution_id: NCAR\n",
" license: CMIP6 model data produced by <The National Cente...\n",
" mip_era: CMIP6\n",
" model_doi_url: https://doi.org/10.5065/D67H1H0V\n",
" nominal_resolution: 100 km\n",
" parent_activity_id: CMIP\n",
" parent_experiment_id: piControl\n",
" parent_mip_era: CMIP6\n",
" parent_source_id: CESM2\n",
" parent_time_units: days since 0001-01-01 00:00:00\n",
" parent_variant_label: r1i1p1f1\n",
" physics_index: 1\n",
" product: model-output\n",
" realization_index: 1\n",
" realm: ocean\n",
" source: CESM2 (2017): atmosphere: CAM6 (0.9x1.25 finite ...\n",
" source_id: CESM2\n",
" source_type: AOGCM BGC\n",
" sub_experiment: none\n",
" sub_experiment_id: none\n",
" table_id: Omon\n",
" tracking_id: hdl:21.14100/672d35cd-e662-4807-8dee-7d7d5e1d4d1c\n",
" variable_id: thetao\n",
" variant_info: CMIP6 20th century experiments (1850-2014) with ...\n",
" variant_label: r1i1p1f1\n",
" status: 2019-10-25;created;by [email protected]\n",
" netcdf_tracking_ids: hdl:21.14100/672d35cd-e662-4807-8dee-7d7d5e1d4d1c\n",
" version_id: v20190308\n",
" intake_esm_varname: ['thetao']\n",
" intake_esm_dataset_key: CMIP.NCAR.CESM2.historical.Omon.gn"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cat = col.search(source_id='CESM2', variable_id='thetao', grid_label='gn', member_id='r1i1p1f1', experiment_id='historical')\n",
"ddict = cat.to_dataset_dict(zarr_kwargs={'consolidated':True, 'use_cftime':True})\n",
"_, ds = ddict.popitem()\n",
"ds"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "harmful-equation",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "labeled-alexandria",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:notebook] *",
"language": "python",
"name": "conda-env-notebook-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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