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navidcy/cookbook-with-daskclient-spits-warnings.ipynb

Created February 27, 2024 11:46
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cookbook-with-daskclient-spits-warnings notebook
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cookbook-with-daskclient-spits-warnings.ipynb
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;u&#x27; (time: 48, st_ocean: 50, yu_ocean: 1080, xu_ocean: 1440)&gt; Size: 15GB\n",
"dask.array&lt;concatenate, shape=(48, 50, 1080, 1440), dtype=float32, chunksize=(1, 25, 108, 120), chunktype=numpy.ndarray&gt;\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 384B 1980-01-14T12:00:00 ... 1983-12-14T1...\n",
" * st_ocean (st_ocean) float64 400B 1.152 3.649 6.565 ... 5.034e+03 5.254e+03\n",
" * xu_ocean (xu_ocean) float64 12kB -279.8 -279.5 -279.2 ... 79.5 79.75 80.0\n",
" * yu_ocean (yu_ocean) float64 9kB -81.02 -80.92 -80.81 ... 89.79 89.89 90.0\n",
"Attributes: (12/13)\n",
" long_name: i-current\n",
" units: m/sec\n",
" valid_range: [-10. 10.]\n",
" cell_methods: time: mean\n",
" time_avg_info: average_T1,average_T2,average_DT\n",
" standard_name: sea_water_x_velocity\n",
" ... ...\n",
" contact: Ryan Holmes\n",
" email: [email protected]\n",
" created: 2020-11-03\n",
" description: Cycle 6/6 of 0.25 degree ACCESS-OM2 physics-only global c...\n",
" notes: Output diagnostics are extensive based on the CMIP6 OMIP ...\n",
" url: https://github.com/rmholmes/025deg_jra55_iaf/tree/omip_am...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'u'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 48</li><li><span class='xr-has-index'>st_ocean</span>: 50</li><li><span class='xr-has-index'>yu_ocean</span>: 1080</li><li><span class='xr-has-index'>xu_ocean</span>: 1440</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-514a5628-36de-489d-a0ce-6ab665eb67f6' class='xr-array-in' type='checkbox' checked><label for='section-514a5628-36de-489d-a0ce-6ab665eb67f6' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 25, 108, 120), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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" <line x1=\"120\" y1=\"18\" x2=\"120\" y2=\"108\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"102.0,0.0 120.98330170562053,18.983301705620537 120.98330170562053,108.98330170562053 102.0,90.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"102\" y1=\"0\" x2=\"222\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"111\" y1=\"9\" x2=\"231\" y2=\"9\" />\n",
" <line x1=\"120\" y1=\"18\" x2=\"240\" y2=\"18\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"102\" y1=\"0\" x2=\"120\" y2=\"18\" style=\"stroke-width:2\" />\n",
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" <line x1=\"122\" y1=\"0\" x2=\"140\" y2=\"18\" />\n",
" <line x1=\"132\" y1=\"0\" x2=\"150\" y2=\"18\" />\n",
" <line x1=\"142\" y1=\"0\" x2=\"160\" y2=\"18\" />\n",
" <line x1=\"152\" y1=\"0\" x2=\"170\" y2=\"18\" />\n",
" <line x1=\"162\" y1=\"0\" x2=\"180\" y2=\"18\" />\n",
" <line x1=\"172\" y1=\"0\" x2=\"190\" y2=\"18\" />\n",
" <line x1=\"182\" y1=\"0\" x2=\"200\" y2=\"18\" />\n",
" <line x1=\"192\" y1=\"0\" x2=\"210\" y2=\"18\" />\n",
" <line x1=\"202\" y1=\"0\" x2=\"220\" y2=\"18\" />\n",
" <line x1=\"212\" y1=\"0\" x2=\"230\" y2=\"18\" />\n",
" <line x1=\"222\" y1=\"0\" x2=\"240\" y2=\"18\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"102.0,0.0 222.0,0.0 240.98330170562053,18.983301705620537 120.98330170562053,18.983301705620537\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"120\" y1=\"18\" x2=\"240\" y2=\"18\" style=\"stroke-width:2\" />\n",
" <line x1=\"120\" y1=\"27\" x2=\"240\" y2=\"27\" />\n",
" <line x1=\"120\" y1=\"36\" x2=\"240\" y2=\"36\" />\n",
" <line x1=\"120\" y1=\"45\" x2=\"240\" y2=\"45\" />\n",
" <line x1=\"120\" y1=\"54\" x2=\"240\" y2=\"54\" />\n",
" <line x1=\"120\" y1=\"63\" x2=\"240\" y2=\"63\" />\n",
" <line x1=\"120\" y1=\"72\" x2=\"240\" y2=\"72\" />\n",
" <line x1=\"120\" y1=\"81\" x2=\"240\" y2=\"81\" />\n",
" <line x1=\"120\" y1=\"90\" x2=\"240\" y2=\"90\" />\n",
" <line x1=\"120\" y1=\"99\" x2=\"240\" y2=\"99\" />\n",
" <line x1=\"120\" y1=\"108\" x2=\"240\" y2=\"108\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"120\" y1=\"18\" x2=\"120\" y2=\"108\" style=\"stroke-width:2\" />\n",
" <line x1=\"130\" y1=\"18\" x2=\"130\" y2=\"108\" />\n",
" <line x1=\"140\" y1=\"18\" x2=\"140\" y2=\"108\" />\n",
" <line x1=\"150\" y1=\"18\" x2=\"150\" y2=\"108\" />\n",
" <line x1=\"160\" y1=\"18\" x2=\"160\" y2=\"108\" />\n",
" <line x1=\"170\" y1=\"18\" x2=\"170\" y2=\"108\" />\n",
" <line x1=\"180\" y1=\"18\" x2=\"180\" y2=\"108\" />\n",
" <line x1=\"190\" y1=\"18\" x2=\"190\" y2=\"108\" />\n",
" <line x1=\"200\" y1=\"18\" x2=\"200\" y2=\"108\" />\n",
" <line x1=\"210\" y1=\"18\" x2=\"210\" y2=\"108\" />\n",
" <line x1=\"220\" y1=\"18\" x2=\"220\" y2=\"108\" />\n",
" <line x1=\"230\" y1=\"18\" x2=\"230\" y2=\"108\" />\n",
" <line x1=\"240\" y1=\"18\" x2=\"240\" y2=\"108\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"120.98330170562053,18.983301705620537 240.98330170562053,18.983301705620537 240.98330170562053,108.98330170562053 120.98330170562053,108.98330170562053\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
"\n",
" <!-- Text -->\n",
" <text x=\"180.983302\" y=\"128.983302\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
" <text x=\"260.983302\" y=\"63.983302\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,260.983302,63.983302)\">1080</text>\n",
" <text x=\"101.491651\" y=\"119.491651\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,101.491651,119.491651)\">50</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></div></li><li class='xr-section-item'><input id='section-7022b374-a35e-4fda-8097-e33674c0b62f' class='xr-section-summary-in' type='checkbox' checked><label for='section-7022b374-a35e-4fda-8097-e33674c0b62f' class='xr-section-summary' >Coordinates: <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-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1980-01-14T12:00:00 ... 1983-12-...</div><input id='attrs-1a568f7e-dc20-4982-ac12-80e72c792366' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a568f7e-dc20-4982-ac12-80e72c792366' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f73f6bab-17e2-4e91-be1f-61b2c6b22949' class='xr-var-data-in' type='checkbox'><label for='data-f73f6bab-17e2-4e91-be1f-61b2c6b22949' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>GREGORIAN</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-14T12:00:00.000000000&#x27;, &#x27;1980-02-13T12:00:00.000000000&#x27;,\n",
" &#x27;1980-03-14T12:00:00.000000000&#x27;, &#x27;1980-04-14T00:00:00.000000000&#x27;,\n",
" &#x27;1980-05-14T12:00:00.000000000&#x27;, &#x27;1980-06-14T00:00:00.000000000&#x27;,\n",
" &#x27;1980-07-14T12:00:00.000000000&#x27;, &#x27;1980-08-14T12:00:00.000000000&#x27;,\n",
" &#x27;1980-09-14T00:00:00.000000000&#x27;, &#x27;1980-10-14T12:00:00.000000000&#x27;,\n",
" &#x27;1980-11-14T00:00:00.000000000&#x27;, &#x27;1980-12-14T12:00:00.000000000&#x27;,\n",
" &#x27;1981-01-14T12:00:00.000000000&#x27;, &#x27;1981-02-13T00:00:00.000000000&#x27;,\n",
" &#x27;1981-03-14T12:00:00.000000000&#x27;, &#x27;1981-04-14T00:00:00.000000000&#x27;,\n",
" &#x27;1981-05-14T12:00:00.000000000&#x27;, &#x27;1981-06-14T00:00:00.000000000&#x27;,\n",
" &#x27;1981-07-14T12:00:00.000000000&#x27;, &#x27;1981-08-14T12:00:00.000000000&#x27;,\n",
" &#x27;1981-09-14T00:00:00.000000000&#x27;, &#x27;1981-10-14T12:00:00.000000000&#x27;,\n",
" &#x27;1981-11-14T00:00:00.000000000&#x27;, &#x27;1981-12-14T12:00:00.000000000&#x27;,\n",
" &#x27;1982-01-14T12:00:00.000000000&#x27;, &#x27;1982-02-13T00:00:00.000000000&#x27;,\n",
" &#x27;1982-03-14T12:00:00.000000000&#x27;, &#x27;1982-04-14T00:00:00.000000000&#x27;,\n",
" &#x27;1982-05-14T12:00:00.000000000&#x27;, &#x27;1982-06-14T00:00:00.000000000&#x27;,\n",
" &#x27;1982-07-14T12:00:00.000000000&#x27;, &#x27;1982-08-14T12:00:00.000000000&#x27;,\n",
" &#x27;1982-09-14T00:00:00.000000000&#x27;, &#x27;1982-10-14T12:00:00.000000000&#x27;,\n",
" &#x27;1982-11-14T00:00:00.000000000&#x27;, &#x27;1982-12-14T12:00:00.000000000&#x27;,\n",
" &#x27;1983-01-14T12:00:00.000000000&#x27;, &#x27;1983-02-13T00:00:00.000000000&#x27;,\n",
" &#x27;1983-03-14T12:00:00.000000000&#x27;, &#x27;1983-04-14T00:00:00.000000000&#x27;,\n",
" &#x27;1983-05-14T12:00:00.000000000&#x27;, &#x27;1983-06-14T00:00:00.000000000&#x27;,\n",
" &#x27;1983-07-14T12:00:00.000000000&#x27;, &#x27;1983-08-14T12:00:00.000000000&#x27;,\n",
" &#x27;1983-09-14T00:00:00.000000000&#x27;, &#x27;1983-10-14T12:00:00.000000000&#x27;,\n",
" &#x27;1983-11-14T00:00:00.000000000&#x27;, &#x27;1983-12-14T12:00:00.000000000&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>st_ocean</span></div><div class='xr-var-dims'>(st_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.152 3.649 ... 5.034e+03 5.254e+03</div><input id='attrs-8a86a872-8fa7-4bed-abe3-ddab742c435b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a86a872-8fa7-4bed-abe3-ddab742c435b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e825dd04-2025-4697-b9c6-9ea1570fcf4a' class='xr-var-data-in' type='checkbox'><label for='data-e825dd04-2025-4697-b9c6-9ea1570fcf4a' 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>tcell zstar depth</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd></dl></div><div class='xr-var-data'><pre>array([1.151750e+00, 3.648674e+00, 6.564919e+00, 9.970869e+00, 1.394871e+01,\n",
" 1.859438e+01, 2.401987e+01, 3.035588e+01, 3.775489e+01, 4.639470e+01,\n",
" 5.648257e+01, 6.825986e+01, 8.200741e+01, 9.805147e+01, 1.167703e+02,\n",
" 1.386016e+02, 1.640494e+02, 1.936921e+02, 2.281881e+02, 2.682812e+02,\n",
" 3.148002e+02, 3.686535e+02, 4.308139e+02, 5.022893e+02, 5.840771e+02,\n",
" 6.771003e+02, 7.821267e+02, 8.996818e+02, 1.029968e+03, 1.172813e+03,\n",
" 1.327662e+03, 1.493618e+03, 1.669533e+03, 1.854114e+03, 2.046034e+03,\n",
" 2.244025e+03, 2.446937e+03, 2.653770e+03, 2.863688e+03, 3.076005e+03,\n",
" 3.290172e+03, 3.505757e+03, 3.722423e+03, 3.939909e+03, 4.158017e+03,\n",
" 4.376593e+03, 4.595523e+03, 4.814719e+03, 5.034116e+03, 5.253663e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xu_ocean</span></div><div class='xr-var-dims'>(xu_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-279.8 -279.5 -279.2 ... 79.75 80.0</div><input id='attrs-bfd19715-fa58-4738-9ae7-2b0b45439c92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfd19715-fa58-4738-9ae7-2b0b45439c92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b73b42f-87d8-498f-a68b-cb31b71b75bc' class='xr-var-data-in' type='checkbox'><label for='data-2b73b42f-87d8-498f-a68b-cb31b71b75bc' 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>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-279.75, -279.5 , -279.25, ..., 79.5 , 79.75, 80. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yu_ocean</span></div><div class='xr-var-dims'>(yu_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-81.02 -80.92 -80.81 ... 89.89 90.0</div><input id='attrs-0c801141-8308-4c56-8981-d77da328908a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c801141-8308-4c56-8981-d77da328908a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7d967b4-cf66-4e1a-94ed-9e7f9e8f31ab' class='xr-var-data-in' type='checkbox'><label for='data-c7d967b4-cf66-4e1a-94ed-9e7f9e8f31ab' 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>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-81.024202, -80.918603, -80.813004, ..., 89.788884, 89.894483,\n",
" 90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fbc452bb-0e76-45bd-b256-2ab60335b261' class='xr-section-summary-in' type='checkbox' ><label for='section-fbc452bb-0e76-45bd-b256-2ab60335b261' 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>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e83f5ab8-3751-4295-8da6-4e662eb25111' class='xr-index-data-in' type='checkbox'/><label for='index-e83f5ab8-3751-4295-8da6-4e662eb25111' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1980-01-14 12:00:00&#x27;, &#x27;1980-02-13 12:00:00&#x27;,\n",
" &#x27;1980-03-14 12:00:00&#x27;, &#x27;1980-04-14 00:00:00&#x27;,\n",
" &#x27;1980-05-14 12:00:00&#x27;, &#x27;1980-06-14 00:00:00&#x27;,\n",
" &#x27;1980-07-14 12:00:00&#x27;, &#x27;1980-08-14 12:00:00&#x27;,\n",
" &#x27;1980-09-14 00:00:00&#x27;, &#x27;1980-10-14 12:00:00&#x27;,\n",
" &#x27;1980-11-14 00:00:00&#x27;, &#x27;1980-12-14 12:00:00&#x27;,\n",
" &#x27;1981-01-14 12:00:00&#x27;, &#x27;1981-02-13 00:00:00&#x27;,\n",
" &#x27;1981-03-14 12:00:00&#x27;, &#x27;1981-04-14 00:00:00&#x27;,\n",
" &#x27;1981-05-14 12:00:00&#x27;, &#x27;1981-06-14 00:00:00&#x27;,\n",
" &#x27;1981-07-14 12:00:00&#x27;, &#x27;1981-08-14 12:00:00&#x27;,\n",
" &#x27;1981-09-14 00:00:00&#x27;, &#x27;1981-10-14 12:00:00&#x27;,\n",
" &#x27;1981-11-14 00:00:00&#x27;, &#x27;1981-12-14 12:00:00&#x27;,\n",
" &#x27;1982-01-14 12:00:00&#x27;, &#x27;1982-02-13 00:00:00&#x27;,\n",
" &#x27;1982-03-14 12:00:00&#x27;, &#x27;1982-04-14 00:00:00&#x27;,\n",
" &#x27;1982-05-14 12:00:00&#x27;, &#x27;1982-06-14 00:00:00&#x27;,\n",
" &#x27;1982-07-14 12:00:00&#x27;, &#x27;1982-08-14 12:00:00&#x27;,\n",
" &#x27;1982-09-14 00:00:00&#x27;, &#x27;1982-10-14 12:00:00&#x27;,\n",
" &#x27;1982-11-14 00:00:00&#x27;, &#x27;1982-12-14 12:00:00&#x27;,\n",
" &#x27;1983-01-14 12:00:00&#x27;, &#x27;1983-02-13 00:00:00&#x27;,\n",
" &#x27;1983-03-14 12:00:00&#x27;, &#x27;1983-04-14 00:00:00&#x27;,\n",
" &#x27;1983-05-14 12:00:00&#x27;, &#x27;1983-06-14 00:00:00&#x27;,\n",
" &#x27;1983-07-14 12:00:00&#x27;, &#x27;1983-08-14 12:00:00&#x27;,\n",
" &#x27;1983-09-14 00:00:00&#x27;, &#x27;1983-10-14 12:00:00&#x27;,\n",
" &#x27;1983-11-14 00:00:00&#x27;, &#x27;1983-12-14 12:00:00&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>st_ocean</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-42744823-b720-4ad9-866e-913d99e40fa3' class='xr-index-data-in' type='checkbox'/><label for='index-42744823-b720-4ad9-866e-913d99e40fa3' 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([ 1.151749849319458, 3.6486740112304688, 6.564918518066406,\n",
" 9.970869064331055, 13.948708534240723, 18.594379425048828,\n",
" 24.019872665405273, 30.355884552001953, 37.75489044189453,\n",
" 46.39470291137695, 56.48257064819336, 68.2598648071289,\n",
" 82.00740814208984, 98.05146789550781, 116.77034759521484,\n",
" 138.6016082763672, 164.0494384765625, 193.6920623779297,\n",
" 228.18814086914062, 268.2812194824219, 314.8001708984375,\n",
" 368.6535339355469, 430.8139343261719, 502.289306640625,\n",
" 584.0770874023438, 677.1002807617188, 782.126708984375,\n",
" 899.6817626953125, 1029.9681396484375, 1172.8133544921875,\n",
" 1327.6619873046875, 1493.618408203125, 1669.533447265625,\n",
" 1854.1141357421875, 2046.034423828125, 2244.025146484375,\n",
" 2446.9365234375, 2653.77001953125, 2863.68798828125,\n",
" 3076.0048828125, 3290.17236328125, 3505.75732421875,\n",
" 3722.423095703125, 3939.9091796875, 4158.0166015625,\n",
" 4376.5927734375, 4595.52294921875, 4814.71923828125,\n",
" 5034.11572265625, 5253.6630859375],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;st_ocean&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>xu_ocean</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ab22949a-0546-4ebf-8644-622467b7073e' class='xr-index-data-in' type='checkbox'/><label for='index-ab22949a-0546-4ebf-8644-622467b7073e' 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([-279.75, -279.5, -279.25, -279.0, -278.75, -278.5, -278.25, -278.0,\n",
" -277.75, -277.5,\n",
" ...\n",
" 77.75, 78.0, 78.25, 78.5, 78.75, 79.0, 79.25, 79.5,\n",
" 79.75, 80.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;xu_ocean&#x27;, length=1440))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>yu_ocean</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9b5723e2-e7c8-47ae-977c-4a3a255b85b7' class='xr-index-data-in' type='checkbox'/><label for='index-9b5723e2-e7c8-47ae-977c-4a3a255b85b7' 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([-81.02420153923416, -80.91860295002925, -80.81300436082435,\n",
" -80.70740577161945, -80.60180718241455, -80.49620859320964,\n",
" -80.39061000400474, -80.28501141479984, -80.17941282559494,\n",
" -80.07381423639004,\n",
" ...\n",
" 89.04969431880795, 89.15529290801285, 89.2608914972178,\n",
" 89.36649008642271, 89.47208867562759, 89.57768726483256,\n",
" 89.68328585403744, 89.78888444324235, 89.89448303244733,\n",
" 90.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;yu_ocean&#x27;, length=1080))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cee81bea-3eee-4f2e-a0ed-fd6a6bd50c42' class='xr-section-summary-in' type='checkbox' ><label for='section-cee81bea-3eee-4f2e-a0ed-fd6a6bd50c42' class='xr-section-summary' >Attributes: <span>(13)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>i-current</dd><dt><span>units :</span></dt><dd>m/sec</dd><dt><span>valid_range :</span></dt><dd>[-10. 10.]</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>standard_name :</span></dt><dd>sea_water_x_velocity</dd><dt><span>ncfiles :</span></dt><dd>[&#x27;/g/data/ik11/outputs/access-om2-025/025deg_jra55_iaf_omip2_cycle6/output327/ocean/ocean_month.nc&#x27;, &#x27;/g/data/ik11/outputs/access-om2-025/025deg_jra55_iaf_omip2_cycle6/output328/ocean/ocean_month.nc&#x27;, &#x27;/g/data/ik11/outputs/access-om2-025/025deg_jra55_iaf_omip2_cycle6/output329/ocean/ocean_month.nc&#x27;, &#x27;/g/data/ik11/outputs/access-om2-025/025deg_jra55_iaf_omip2_cycle6/output330/ocean/ocean_month.nc&#x27;]</dd><dt><span>contact :</span></dt><dd>Ryan Holmes</dd><dt><span>email :</span></dt><dd>[email protected]</dd><dt><span>created :</span></dt><dd>2020-11-03</dd><dt><span>description :</span></dt><dd>Cycle 6/6 of 0.25 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2019)</dd><dt><span>notes :</span></dt><dd>Output diagnostics are extensive based on the CMIP6 OMIP diagnostics request listed in Griffies et al (2016, https://doi.org/10.5194/gmd-9-3231-2016), including many budget diagnostics. This cycle (cycle 6) includes monthly frequency budget diagnostics.</dd><dt><span>url :</span></dt><dd>https://github.com/rmholmes/025deg_jra55_iaf/tree/omip_amoctopo_cycle6</dd></dl></div></li></ul></div></div>"
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"<xarray.DataArray 'u' (time: 48, st_ocean: 50, yu_ocean: 1080, xu_ocean: 1440)> Size: 15GB\n",
"dask.array<concatenate, shape=(48, 50, 1080, 1440), dtype=float32, chunksize=(1, 25, 108, 120), chunktype=numpy.ndarray>\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 384B 1980-01-14T12:00:00 ... 1983-12-14T1...\n",
" * st_ocean (st_ocean) float64 400B 1.152 3.649 6.565 ... 5.034e+03 5.254e+03\n",
" * xu_ocean (xu_ocean) float64 12kB -279.8 -279.5 -279.2 ... 79.5 79.75 80.0\n",
" * yu_ocean (yu_ocean) float64 9kB -81.02 -80.92 -80.81 ... 89.79 89.89 90.0\n",
"Attributes: (12/13)\n",
" long_name: i-current\n",
" units: m/sec\n",
" valid_range: [-10. 10.]\n",
" cell_methods: time: mean\n",
" time_avg_info: average_T1,average_T2,average_DT\n",
" standard_name: sea_water_x_velocity\n",
" ... ...\n",
" contact: Ryan Holmes\n",
" email: [email protected]\n",
" created: 2020-11-03\n",
" description: Cycle 6/6 of 0.25 degree ACCESS-OM2 physics-only global c...\n",
" notes: Output diagnostics are extensive based on the CMIP6 OMIP ...\n",
" url: https://github.com/rmholmes/025deg_jra55_iaf/tree/omip_am..."
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import cosima_cookbook as cc\n",
"\n",
"session = cc.database.create_session()\n",
"\n",
"u = cc.querying.getvar('025deg_jra55_iaf_omip2_cycle6', 'u', session, frequency='1 monthly',\n",
" start_time='1980-01-01', end_time='1982-12-31')\n",
"u"
]
},
{
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"execution_count": 2,
"id": "fd853654-cf98-425a-8ee1-2543c5e4a1c9",
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" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"xu_ocean\" starting at index 120. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"yu_ocean\" starting at index 108. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"yu_ocean\" starting at index 108. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"time\" starting at index 1. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"time\" starting at index 1. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"xu_ocean\" starting at index 120. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"yu_ocean\" starting at index 108. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"time\" starting at index 1. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"xu_ocean\" starting at index 120. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"yu_ocean\" starting at index 108. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n",
"/g/data/hh5/public/apps/miniconda3/envs/analysis3-24.01/lib/python3.10/site-packages/xarray/core/dataset.py:271: UserWarning: The specified chunks separate the stored chunks along dimension \"time\" starting at index 1. This could degrade performance. Instead, consider rechunking after loading.\n",
" warnings.warn(\n"
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;u&#x27; (time: 48, st_ocean: 50, yu_ocean: 1080, xu_ocean: 1440)&gt; Size: 15GB\n",
"dask.array&lt;concatenate, shape=(48, 50, 1080, 1440), dtype=float32, chunksize=(1, 25, 108, 120), chunktype=numpy.ndarray&gt;\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 384B 1980-01-14T12:00:00 ... 1983-12-14T1...\n",
" * st_ocean (st_ocean) float64 400B 1.152 3.649 6.565 ... 5.034e+03 5.254e+03\n",
" * xu_ocean (xu_ocean) float64 12kB -279.8 -279.5 -279.2 ... 79.5 79.75 80.0\n",
" * yu_ocean (yu_ocean) float64 9kB -81.02 -80.92 -80.81 ... 89.79 89.89 90.0\n",
"Attributes: (12/13)\n",
" long_name: i-current\n",
" units: m/sec\n",
" valid_range: [-10. 10.]\n",
" cell_methods: time: mean\n",
" time_avg_info: average_T1,average_T2,average_DT\n",
" standard_name: sea_water_x_velocity\n",
" ... ...\n",
" contact: Ryan Holmes\n",
" email: [email protected]\n",
" created: 2020-11-03\n",
" description: Cycle 6/6 of 0.25 degree ACCESS-OM2 physics-only global c...\n",
" notes: Output diagnostics are extensive based on the CMIP6 OMIP ...\n",
" url: https://github.com/rmholmes/025deg_jra55_iaf/tree/omip_am...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'u'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 48</li><li><span class='xr-has-index'>st_ocean</span>: 50</li><li><span class='xr-has-index'>yu_ocean</span>: 1080</li><li><span class='xr-has-index'>xu_ocean</span>: 1440</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3bfff283-72ed-40ae-a40c-2c1e129d82ff' class='xr-array-in' type='checkbox' checked><label for='section-3bfff283-72ed-40ae-a40c-2c1e129d82ff' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 25, 108, 120), meta=np.ndarray&gt;</span></div><div class='xr-array-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> 13.90 GiB </td>\n",
" <td> 1.24 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (48, 50, 1080, 1440) </td>\n",
" <td> (1, 25, 108, 120) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 11520 chunks in 9 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></div></li><li class='xr-section-item'><input id='section-3d3d1ef4-544b-45a1-a723-ba443c079262' class='xr-section-summary-in' type='checkbox' checked><label for='section-3d3d1ef4-544b-45a1-a723-ba443c079262' class='xr-section-summary' >Coordinates: <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-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1980-01-14T12:00:00 ... 1983-12-...</div><input id='attrs-d792f324-cf1f-4e57-8c1f-7ad7e44af1d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d792f324-cf1f-4e57-8c1f-7ad7e44af1d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-426545e9-c89b-4fbf-8ba3-65b273b4a3b7' class='xr-var-data-in' type='checkbox'><label for='data-426545e9-c89b-4fbf-8ba3-65b273b4a3b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>calendar_type :</span></dt><dd>GREGORIAN</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-14T12:00:00.000000000&#x27;, &#x27;1980-02-13T12:00:00.000000000&#x27;,\n",
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" dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>st_ocean</span></div><div class='xr-var-dims'>(st_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.152 3.649 ... 5.034e+03 5.254e+03</div><input id='attrs-0f0900f7-860f-40a5-b830-bd4c4ea6d9f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f0900f7-860f-40a5-b830-bd4c4ea6d9f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6b6cdd1-1d4b-4828-a2f9-f9937bfe8b8c' class='xr-var-data-in' type='checkbox'><label for='data-c6b6cdd1-1d4b-4828-a2f9-f9937bfe8b8c' 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>tcell zstar depth</dd><dt><span>units :</span></dt><dd>meters</dd><dt><span>cartesian_axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd></dl></div><div class='xr-var-data'><pre>array([1.151750e+00, 3.648674e+00, 6.564919e+00, 9.970869e+00, 1.394871e+01,\n",
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" 2.244025e+03, 2.446937e+03, 2.653770e+03, 2.863688e+03, 3.076005e+03,\n",
" 3.290172e+03, 3.505757e+03, 3.722423e+03, 3.939909e+03, 4.158017e+03,\n",
" 4.376593e+03, 4.595523e+03, 4.814719e+03, 5.034116e+03, 5.253663e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xu_ocean</span></div><div class='xr-var-dims'>(xu_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-279.8 -279.5 -279.2 ... 79.75 80.0</div><input id='attrs-569afd7b-1670-4833-bdec-4e3b37900ece' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-569afd7b-1670-4833-bdec-4e3b37900ece' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc82c05f-7cb9-40ed-b3d1-de271b05eed5' class='xr-var-data-in' type='checkbox'><label for='data-dc82c05f-7cb9-40ed-b3d1-de271b05eed5' 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>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd><dt><span>cartesian_axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-279.75, -279.5 , -279.25, ..., 79.5 , 79.75, 80. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yu_ocean</span></div><div class='xr-var-dims'>(yu_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-81.02 -80.92 -80.81 ... 89.89 90.0</div><input id='attrs-db6d050b-907e-454a-8fd6-473b95cb33fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db6d050b-907e-454a-8fd6-473b95cb33fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac69f529-3469-4b0b-9c4d-37d50d65a2e6' class='xr-var-data-in' type='checkbox'><label for='data-ac69f529-3469-4b0b-9c4d-37d50d65a2e6' 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>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd><dt><span>cartesian_axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-81.024202, -80.918603, -80.813004, ..., 89.788884, 89.894483,\n",
" 90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7506bcfc-1c5a-4e24-9ea4-5b1a533cfee3' class='xr-section-summary-in' type='checkbox' ><label for='section-7506bcfc-1c5a-4e24-9ea4-5b1a533cfee3' 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>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-865178b4-ebae-41cd-9a0c-1d42bf59bd94' class='xr-index-data-in' type='checkbox'/><label for='index-865178b4-ebae-41cd-9a0c-1d42bf59bd94' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1980-01-14 12:00:00&#x27;, &#x27;1980-02-13 12:00:00&#x27;,\n",
" &#x27;1980-03-14 12:00:00&#x27;, &#x27;1980-04-14 00:00:00&#x27;,\n",
" &#x27;1980-05-14 12:00:00&#x27;, &#x27;1980-06-14 00:00:00&#x27;,\n",
" &#x27;1980-07-14 12:00:00&#x27;, &#x27;1980-08-14 12:00:00&#x27;,\n",
" &#x27;1980-09-14 00:00:00&#x27;, &#x27;1980-10-14 12:00:00&#x27;,\n",
" &#x27;1980-11-14 00:00:00&#x27;, &#x27;1980-12-14 12:00:00&#x27;,\n",
" &#x27;1981-01-14 12:00:00&#x27;, &#x27;1981-02-13 00:00:00&#x27;,\n",
" &#x27;1981-03-14 12:00:00&#x27;, &#x27;1981-04-14 00:00:00&#x27;,\n",
" &#x27;1981-05-14 12:00:00&#x27;, &#x27;1981-06-14 00:00:00&#x27;,\n",
" &#x27;1981-07-14 12:00:00&#x27;, &#x27;1981-08-14 12:00:00&#x27;,\n",
" &#x27;1981-09-14 00:00:00&#x27;, &#x27;1981-10-14 12:00:00&#x27;,\n",
" &#x27;1981-11-14 00:00:00&#x27;, &#x27;1981-12-14 12:00:00&#x27;,\n",
" &#x27;1982-01-14 12:00:00&#x27;, &#x27;1982-02-13 00:00:00&#x27;,\n",
" &#x27;1982-03-14 12:00:00&#x27;, &#x27;1982-04-14 00:00:00&#x27;,\n",
" &#x27;1982-05-14 12:00:00&#x27;, &#x27;1982-06-14 00:00:00&#x27;,\n",
" &#x27;1982-07-14 12:00:00&#x27;, &#x27;1982-08-14 12:00:00&#x27;,\n",
" &#x27;1982-09-14 00:00:00&#x27;, &#x27;1982-10-14 12:00:00&#x27;,\n",
" &#x27;1982-11-14 00:00:00&#x27;, &#x27;1982-12-14 12:00:00&#x27;,\n",
" &#x27;1983-01-14 12:00:00&#x27;, &#x27;1983-02-13 00:00:00&#x27;,\n",
" &#x27;1983-03-14 12:00:00&#x27;, &#x27;1983-04-14 00:00:00&#x27;,\n",
" &#x27;1983-05-14 12:00:00&#x27;, &#x27;1983-06-14 00:00:00&#x27;,\n",
" &#x27;1983-07-14 12:00:00&#x27;, &#x27;1983-08-14 12:00:00&#x27;,\n",
" &#x27;1983-09-14 00:00:00&#x27;, &#x27;1983-10-14 12:00:00&#x27;,\n",
" &#x27;1983-11-14 00:00:00&#x27;, &#x27;1983-12-14 12:00:00&#x27;],\n",
" dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>st_ocean</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9f57d924-6929-4827-b354-3487cce64332' class='xr-index-data-in' type='checkbox'/><label for='index-9f57d924-6929-4827-b354-3487cce64332' 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([ 1.151749849319458, 3.6486740112304688, 6.564918518066406,\n",
" 9.970869064331055, 13.948708534240723, 18.594379425048828,\n",
" 24.019872665405273, 30.355884552001953, 37.75489044189453,\n",
" 46.39470291137695, 56.48257064819336, 68.2598648071289,\n",
" 82.00740814208984, 98.05146789550781, 116.77034759521484,\n",
" 138.6016082763672, 164.0494384765625, 193.6920623779297,\n",
" 228.18814086914062, 268.2812194824219, 314.8001708984375,\n",
" 368.6535339355469, 430.8139343261719, 502.289306640625,\n",
" 584.0770874023438, 677.1002807617188, 782.126708984375,\n",
" 899.6817626953125, 1029.9681396484375, 1172.8133544921875,\n",
" 1327.6619873046875, 1493.618408203125, 1669.533447265625,\n",
" 1854.1141357421875, 2046.034423828125, 2244.025146484375,\n",
" 2446.9365234375, 2653.77001953125, 2863.68798828125,\n",
" 3076.0048828125, 3290.17236328125, 3505.75732421875,\n",
" 3722.423095703125, 3939.9091796875, 4158.0166015625,\n",
" 4376.5927734375, 4595.52294921875, 4814.71923828125,\n",
" 5034.11572265625, 5253.6630859375],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;st_ocean&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>xu_ocean</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-398b4bbe-0ffe-48b7-a5ec-861f9f7a8b30' class='xr-index-data-in' type='checkbox'/><label for='index-398b4bbe-0ffe-48b7-a5ec-861f9f7a8b30' 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([-279.75, -279.5, -279.25, -279.0, -278.75, -278.5, -278.25, -278.0,\n",
" -277.75, -277.5,\n",
" ...\n",
" 77.75, 78.0, 78.25, 78.5, 78.75, 79.0, 79.25, 79.5,\n",
" 79.75, 80.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;xu_ocean&#x27;, length=1440))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>yu_ocean</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-37810ae1-993b-4acd-847c-c59e8c45880d' class='xr-index-data-in' type='checkbox'/><label for='index-37810ae1-993b-4acd-847c-c59e8c45880d' 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([-81.02420153923416, -80.91860295002925, -80.81300436082435,\n",
" -80.70740577161945, -80.60180718241455, -80.49620859320964,\n",
" -80.39061000400474, -80.28501141479984, -80.17941282559494,\n",
" -80.07381423639004,\n",
" ...\n",
" 89.04969431880795, 89.15529290801285, 89.2608914972178,\n",
" 89.36649008642271, 89.47208867562759, 89.57768726483256,\n",
" 89.68328585403744, 89.78888444324235, 89.89448303244733,\n",
" 90.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;yu_ocean&#x27;, length=1080))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-44f4f9c7-3175-491c-9977-e833469ed510' class='xr-section-summary-in' type='checkbox' ><label for='section-44f4f9c7-3175-491c-9977-e833469ed510' class='xr-section-summary' >Attributes: <span>(13)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>i-current</dd><dt><span>units :</span></dt><dd>m/sec</dd><dt><span>valid_range :</span></dt><dd>[-10. 10.]</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>standard_name :</span></dt><dd>sea_water_x_velocity</dd><dt><span>ncfiles :</span></dt><dd>[&#x27;/g/data/ik11/outputs/access-om2-025/025deg_jra55_iaf_omip2_cycle6/output327/ocean/ocean_month.nc&#x27;, &#x27;/g/data/ik11/outputs/access-om2-025/025deg_jra55_iaf_omip2_cycle6/output328/ocean/ocean_month.nc&#x27;, &#x27;/g/data/ik11/outputs/access-om2-025/025deg_jra55_iaf_omip2_cycle6/output329/ocean/ocean_month.nc&#x27;, &#x27;/g/data/ik11/outputs/access-om2-025/025deg_jra55_iaf_omip2_cycle6/output330/ocean/ocean_month.nc&#x27;]</dd><dt><span>contact :</span></dt><dd>Ryan Holmes</dd><dt><span>email :</span></dt><dd>[email protected]</dd><dt><span>created :</span></dt><dd>2020-11-03</dd><dt><span>description :</span></dt><dd>Cycle 6/6 of 0.25 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2019)</dd><dt><span>notes :</span></dt><dd>Output diagnostics are extensive based on the CMIP6 OMIP diagnostics request listed in Griffies et al (2016, https://doi.org/10.5194/gmd-9-3231-2016), including many budget diagnostics. This cycle (cycle 6) includes monthly frequency budget diagnostics.</dd><dt><span>url :</span></dt><dd>https://github.com/rmholmes/025deg_jra55_iaf/tree/omip_amoctopo_cycle6</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'u' (time: 48, st_ocean: 50, yu_ocean: 1080, xu_ocean: 1440)> Size: 15GB\n",
"dask.array<concatenate, shape=(48, 50, 1080, 1440), dtype=float32, chunksize=(1, 25, 108, 120), chunktype=numpy.ndarray>\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 384B 1980-01-14T12:00:00 ... 1983-12-14T1...\n",
" * st_ocean (st_ocean) float64 400B 1.152 3.649 6.565 ... 5.034e+03 5.254e+03\n",
" * xu_ocean (xu_ocean) float64 12kB -279.8 -279.5 -279.2 ... 79.5 79.75 80.0\n",
" * yu_ocean (yu_ocean) float64 9kB -81.02 -80.92 -80.81 ... 89.79 89.89 90.0\n",
"Attributes: (12/13)\n",
" long_name: i-current\n",
" units: m/sec\n",
" valid_range: [-10. 10.]\n",
" cell_methods: time: mean\n",
" time_avg_info: average_T1,average_T2,average_DT\n",
" standard_name: sea_water_x_velocity\n",
" ... ...\n",
" contact: Ryan Holmes\n",
" email: [email protected]\n",
" created: 2020-11-03\n",
" description: Cycle 6/6 of 0.25 degree ACCESS-OM2 physics-only global c...\n",
" notes: Output diagnostics are extensive based on the CMIP6 OMIP ...\n",
" url: https://github.com/rmholmes/025deg_jra55_iaf/tree/omip_am..."
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from dask.distributed import Client\n",
"client = Client()\n",
"\n",
"u = cc.querying.getvar('025deg_jra55_iaf_omip2_cycle6', 'u', session, frequency='1 monthly',\n",
" start_time='1980-01-01', end_time='1982-12-31')\n",
"u"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:analysis3-unstable]",
"language": "python",
"name": "conda-env-analysis3-unstable-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": "3.10.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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