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July 7, 2021 17:59
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CMIP6 unit example
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 26, | |
"id": "immune-consensus", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"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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" /* gets rid of default border in Firefox and Opera. */\n", | |
" border: none;\n", | |
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n", | |
" background-size: auto;\n", | |
" }\n", | |
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n", | |
" background: #F44336;\n", | |
" }\n", | |
" </style>\n", | |
" <progress value='1' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n", | |
" 100.00% [1/1 00:00<00:00]\n", | |
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"<IPython.core.display.HTML object>" | |
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], | |
"source": [ | |
"import intake\n", | |
"import numpy as np\n", | |
"\n", | |
"col = intake.open_esm_datastore(\n", | |
" \"https://storage.googleapis.com/cmip6/pangeo-cmip6.json\"\n", | |
")\n", | |
"cat = col.search(\n", | |
" source_id=\"CESM2\",\n", | |
" variable_id=\"thetao\",\n", | |
" experiment_id=\"historical\",\n", | |
" member_id=\"r3i1p1f1\",\n", | |
" table_id=\"Omon\",\n", | |
" grid_label=\"gn\",\n", | |
")\n", | |
"dset_dict = cat.to_dataset_dict(zarr_kwargs={\"consolidated\": True, \"use_cftime\": True})" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 27, | |
"id": "incorporated-utility", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
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" --xr-background-color: var(--jp-layout-color0, white);\n", | |
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" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n", | |
"}\n", | |
"\n", | |
"html[theme=dark],\n", | |
"body.vscode-dark {\n", | |
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".xr-header {\n", | |
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"}\n", | |
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".xr-header > div,\n", | |
".xr-header > ul {\n", | |
" display: inline;\n", | |
" margin-top: 0;\n", | |
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"\n", | |
".xr-obj-type,\n", | |
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".xr-section-summary-in:disabled + label:before {\n", | |
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".xr-section-inline-details {\n", | |
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".xr-section-details {\n", | |
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"\n", | |
".xr-section-summary-in:checked ~ .xr-section-details {\n", | |
" display: contents;\n", | |
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" display: grid;\n", | |
" grid-template-columns: 20px auto;\n", | |
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".xr-array-wrap > label {\n", | |
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".xr-var-item > .xr-var-name span {\n", | |
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".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", | |
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"</style><pre class='xr-text-repr-fallback'><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 'r3i1p1f1'\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: 240900.0\n", | |
" case_id: 17\n", | |
" cesm_casename: b.e21.BHIST.f09_g17.CMIP6-historical.003\n", | |
" contact: [email protected]\n", | |
" creation_date: 2019-01-18T17:55:35Z\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: 3\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:21.14100/4de9dbef-9c0f-4bbb-8d4a-b1e9a1e2a193\n", | |
" variable_id: thetao\n", | |
" variant_info: CMIP6 20th century experiments (1850-2014) with ...\n", | |
" variant_label: r3i1p1f1\n", | |
" status: 2019-10-25;created;by [email protected]\n", | |
" netcdf_tracking_ids: hdl:21.14100/4de9dbef-9c0f-4bbb-8d4a-b1e9a1e2a193\n", | |
" version_id: v20190308\n", | |
" intake_esm_varname: ['thetao']\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-2ccdb7c6-08a6-449b-b1ae-f9100e27d2c7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2ccdb7c6-08a6-449b-b1ae-f9100e27d2c7' 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-d25de59b-0c8c-4418-91bf-675044d31c47' class='xr-section-summary-in' type='checkbox' checked><label for='section-d25de59b-0c8c-4418-91bf-675044d31c47' 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<chunksize=(384, 320), meta=np.ndarray></div><input id='attrs-556d441e-b908-4b97-a5ff-47b202ed0309' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-556d441e-b908-4b97-a5ff-47b202ed0309' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76c5080f-1a70-46e3-bc3e-61b704f67b3d' class='xr-var-data-in' type='checkbox'><label for='data-76c5080f-1a70-46e3-bc3e-61b704f67b3d' 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", | |
"</table>\n", | |
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"</svg>\n", | |
"</td>\n", | |
"</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<chunksize=(384, 320, 4), meta=np.ndarray></div><input id='attrs-34e88519-b35b-4c4f-a997-bb298bc642a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34e88519-b35b-4c4f-a997-bb298bc642a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b963cfa1-15ca-4760-b041-3419d5eb753c' class='xr-var-data-in' type='checkbox'><label for='data-b963cfa1-15ca-4760-b041-3419d5eb753c' 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", | |
"<table>\n", | |
" <thead>\n", | |
" <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr><th> Bytes </th><td> 1.97 MB </td> <td> 1.97 MB </td></tr>\n", | |
" <tr><th> Shape </th><td> (384, 320, 4) </td> <td> (384, 320, 4) </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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"</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-ca6d29c8-002a-44d7-aa1a-1f0e32e5cf31' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca6d29c8-002a-44d7-aa1a-1f0e32e5cf31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7081e921-cabd-42ec-a903-249d48bf2d4c' class='xr-var-data-in' type='checkbox'><label for='data-7081e921-cabd-42ec-a903-249d48bf2d4c' 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<chunksize=(60, 2), meta=np.ndarray></div><input id='attrs-455f26dc-c922-4cc8-a099-734208197df7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-455f26dc-c922-4cc8-a099-734208197df7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed6e7645-3a0f-4e64-8372-a4a8e8a0d11e' class='xr-var-data-in' type='checkbox'><label for='data-ed6e7645-3a0f-4e64-8372-a4a8e8a0d11e' 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", | |
" <thead>\n", | |
" <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
" </thead>\n", | |
" <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", | |
" </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>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<chunksize=(384, 320), meta=np.ndarray></div><input id='attrs-713d4c00-6c63-4367-b969-6d8d43564231' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-713d4c00-6c63-4367-b969-6d8d43564231' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bca8a44f-f310-4848-a837-a035a51664e3' class='xr-var-data-in' type='checkbox'><label for='data-bca8a44f-f310-4848-a837-a035a51664e3' 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", | |
"<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", | |
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"</table>\n", | |
"</td>\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<chunksize=(384, 320, 4), meta=np.ndarray></div><input id='attrs-e48a5795-ae12-495e-bffb-2da3657f9ba1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e48a5795-ae12-495e-bffb-2da3657f9ba1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-883b5991-a26e-4bf7-b199-e69f6a074b71' class='xr-var-data-in' type='checkbox'><label for='data-883b5991-a26e-4bf7-b199-e69f6a074b71' 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", | |
"<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> 1.97 MB </td> <td> 1.97 MB </td></tr>\n", | |
" <tr><th> Shape </th><td> (384, 320, 4) </td> <td> (384, 320, 4) </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 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-7de1ec95-1a15-4d8a-a3a5-d236e612733d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7de1ec95-1a15-4d8a-a3a5-d236e612733d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9358ec0b-f5a2-4c5e-b2a7-2a5073260f29' class='xr-var-data-in' type='checkbox'><label for='data-9358ec0b-f5a2-4c5e-b2a7-2a5073260f29' 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-c65a8d46-09ef-4980-9ecd-6f92bf445a5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c65a8d46-09ef-4980-9ecd-6f92bf445a5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c7a5523-2af4-423e-8e7a-5a9b4befa903' class='xr-var-data-in' type='checkbox'><label for='data-3c7a5523-2af4-423e-8e7a-5a9b4befa903' 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-af21608d-8dc2-40ac-b903-512afc908537' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af21608d-8dc2-40ac-b903-512afc908537' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e37a2ab-d072-463d-9aac-6094c72ecda6' class='xr-var-data-in' type='checkbox'><label for='data-3e37a2ab-d072-463d-9aac-6094c72ecda6' 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<chunksize=(1980, 2), meta=np.ndarray></div><input id='attrs-66fc3f32-27e2-4e6c-9fd4-c890debbdd5e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-66fc3f32-27e2-4e6c-9fd4-c890debbdd5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92e69607-b1e3-46b6-902d-a4db092bf12b' class='xr-var-data-in' type='checkbox'><label for='data-92e69607-b1e3-46b6-902d-a4db092bf12b' 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", | |
"<tr>\n", | |
"<td>\n", | |
"<table>\n", | |
" <thead>\n", | |
" <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n", | |
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" <tbody>\n", | |
" <tr><th> Bytes </th><td> 31.68 kB </td> <td> 31.68 kB </td></tr>\n", | |
" <tr><th> Shape </th><td> (1980, 2) </td> <td> (1980, 2) </td></tr>\n", | |
" <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n", | |
" <tr><th> Type </th><td> object </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 class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'><U8</div><div class='xr-var-preview xr-preview'>'r3i1p1f1'</div><input id='attrs-e67f84c8-af03-4077-9b51-44fb2d2b1ecc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e67f84c8-af03-4077-9b51-44fb2d2b1ecc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cc747a8-2ca4-4441-a16a-841d19829d3e' class='xr-var-data-in' type='checkbox'><label for='data-6cc747a8-2ca4-4441-a16a-841d19829d3e' 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(['r3i1p1f1'], dtype='<U8')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-07a4ec94-9eb1-4583-9e15-e1adb40f303f' class='xr-section-summary-in' type='checkbox' checked><label for='section-07a4ec94-9eb1-4583-9e15-e1adb40f303f' 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<chunksize=(1, 8, 60, 384, 320), meta=np.ndarray></div><input id='attrs-d878bc07-8462-4a2a-8a3e-be9a337b879e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d878bc07-8462-4a2a-8a3e-be9a337b879e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-778fe04c-8bde-41a9-b880-f38ca1a44762' class='xr-var-data-in' type='checkbox'><label for='data-778fe04c-8bde-41a9-b880-f38ca1a44762' 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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" <tr><th> Bytes </th><td> 58.39 GB </td> <td> 235.93 MB </td></tr>\n", | |
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-bcc2e86c-4580-4a56-9733-78b6a683e170' class='xr-section-summary-in' type='checkbox' ><label for='section-bcc2e86c-4580-4a56-9733-78b6a683e170' 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>240900.0</dd><dt><span>case_id :</span></dt><dd>17</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f09_g17.CMIP6-historical.003</dd><dt><span>contact :</span></dt><dd>[email protected]</dd><dt><span>creation_date :</span></dt><dd>2019-01-18T17:55:35Z</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.r3i1p1f1</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 <The National Center for Atmospheric Research> 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>3</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:21.14100/4de9dbef-9c0f-4bbb-8d4a-b1e9a1e2a193</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>r3i1p1f1</dd><dt><span>status :</span></dt><dd>2019-10-25;created;by [email protected]</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/4de9dbef-9c0f-4bbb-8d4a-b1e9a1e2a193</dd><dt><span>version_id :</span></dt><dd>v20190308</dd><dt><span>intake_esm_varname :</span></dt><dd>['thetao']</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 'r3i1p1f1'\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: 240900.0\n", | |
" case_id: 17\n", | |
" cesm_casename: b.e21.BHIST.f09_g17.CMIP6-historical.003\n", | |
" contact: [email protected]\n", | |
" creation_date: 2019-01-18T17:55:35Z\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: 3\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:21.14100/4de9dbef-9c0f-4bbb-8d4a-b1e9a1e2a193\n", | |
" variable_id: thetao\n", | |
" variant_info: CMIP6 20th century experiments (1850-2014) with ...\n", | |
" variant_label: r3i1p1f1\n", | |
" status: 2019-10-25;created;by [email protected]\n", | |
" netcdf_tracking_ids: hdl:21.14100/4de9dbef-9c0f-4bbb-8d4a-b1e9a1e2a193\n", | |
" version_id: v20190308\n", | |
" intake_esm_varname: ['thetao']\n", | |
" intake_esm_dataset_key: CMIP.NCAR.CESM2.historical.Omon.gn" | |
] | |
}, | |
"execution_count": 27, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"ds = dset_dict['CMIP.NCAR.CESM2.historical.Omon.gn']\n", | |
"ds" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 28, | |
"id": "nominated-equity", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
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"\n", | |
".xr-var-attrs,\n", | |
".xr-var-data {\n", | |
" display: none;\n", | |
" background-color: var(--xr-background-color) !important;\n", | |
" padding-bottom: 5px !important;\n", | |
"}\n", | |
"\n", | |
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n", | |
".xr-var-data-in:checked ~ .xr-var-data {\n", | |
" display: block;\n", | |
"}\n", | |
"\n", | |
".xr-var-data > table {\n", | |
" float: right;\n", | |
"}\n", | |
"\n", | |
".xr-var-name span,\n", | |
".xr-var-data,\n", | |
".xr-attrs {\n", | |
" padding-left: 25px !important;\n", | |
"}\n", | |
"\n", | |
".xr-attrs,\n", | |
".xr-var-attrs,\n", | |
".xr-var-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", | |
" 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.DataArray 'lev' (lev: 60)>\n", | |
"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])\n", | |
"Coordinates:\n", | |
" * lev (lev) float64 500.0 1.5e+03 2.5e+03 ... 5.125e+05 5.375e+05\n", | |
"Attributes:\n", | |
" axis: Z\n", | |
" bounds: lev_bnds\n", | |
" positive: down\n", | |
" standard_name: olevel\n", | |
" title: ocean model level\n", | |
" type: double\n", | |
" units: centimeters</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'lev'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lev</span>: 60</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-26632aa1-ebf9-4cde-85e4-34232bf08203' class='xr-array-in' type='checkbox' checked><label for='section-26632aa1-ebf9-4cde-85e4-34232bf08203' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>500.0 1.5e+03 2.5e+03 3.5e+03 ... 4.875e+05 5.125e+05 5.375e+05</span></div><div class='xr-array-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></div></li><li class='xr-section-item'><input id='section-caeb899e-1302-4f23-a63f-218ad9ab07e6' class='xr-section-summary-in' type='checkbox' checked><label for='section-caeb899e-1302-4f23-a63f-218ad9ab07e6' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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-1a2d8027-e371-41c0-8648-6fb652e32871' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a2d8027-e371-41c0-8648-6fb652e32871' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a395405-ff3c-4260-86f9-3bb19967b2d5' class='xr-var-data-in' type='checkbox'><label for='data-7a395405-ff3c-4260-86f9-3bb19967b2d5' 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></ul></div></li><li class='xr-section-item'><input id='section-ce56ade8-e417-4032-863a-9694d68d3a79' class='xr-section-summary-in' type='checkbox' checked><label for='section-ce56ade8-e417-4032-863a-9694d68d3a79' 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>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></li></ul></div></div>" | |
], | |
"text/plain": [ | |
"<xarray.DataArray 'lev' (lev: 60)>\n", | |
"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])\n", | |
"Coordinates:\n", | |
" * lev (lev) float64 500.0 1.5e+03 2.5e+03 ... 5.125e+05 5.375e+05\n", | |
"Attributes:\n", | |
" axis: Z\n", | |
" bounds: lev_bnds\n", | |
" positive: down\n", | |
" standard_name: olevel\n", | |
" title: ocean model level\n", | |
" type: double\n", | |
" units: centimeters" | |
] | |
}, | |
"execution_count": 28, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"ds.lev" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "furnished-relative", | |
"metadata": {}, | |
"source": [ | |
"How can I easily convert this to m with pint-xarray?" | |
] | |
} | |
], | |
"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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