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land-aware-interp.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "df2a1b24-1b81-4e89-a2c4-bf5264a0bcba",
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"source": [
"import xgcm\n",
"import xarray as xr\n",
"import numpy as np"
]
},
{
"cell_type": "markdown",
"id": "65cba002-f926-465c-8395-743ae18a9f24",
"metadata": {},
"source": [
"## Motivation: Interpolate Cell Centered Data to U Points (Cell Face)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "4ce6b522-f601-4eca-b13f-5400d0674312",
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (nv: 2, st_edges_ocean: 51, st_ocean: 50, time: 985, xt_ocean: 1440, xu_ocean: 1440, yt_ocean: 1070, yu_ocean: 1070)\n",
"Coordinates:\n",
" * nv (nv) float64 1.0 2.0\n",
" * st_edges_ocean (st_edges_ocean) float64 0.0 10.07 ... 5.29e+03 5.5e+03\n",
" * st_ocean (st_ocean) float64 5.034 15.1 25.22 ... 5.185e+03 5.395e+03\n",
" * time (time) object 1993-01-07 01:00:00 ... 2019-12-17 01:00:00\n",
" * xt_ocean (xt_ocean) float64 -279.9 -279.6 -279.4 ... 79.62 79.88\n",
" * xu_ocean (xu_ocean) float64 -279.8 -279.5 -279.2 ... 79.5 79.75 80.0\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.84 89.95\n",
" * yu_ocean (yu_ocean) float64 -79.97 -79.86 -79.76 ... 89.79 89.89 90.0\n",
"Data variables:\n",
" average_DT (time) timedelta64[ns] dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
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" tx_int (time, yt_ocean, xu_ocean) float32 dask.array&lt;chunksize=(1, 1070, 1440), meta=np.ndarray&gt;\n",
" tx_trans (time, st_ocean, yt_ocean, xu_ocean) float32 dask.array&lt;chunksize=(1, 50, 1070, 1440), meta=np.ndarray&gt;\n",
" ty_int (time, yu_ocean, xt_ocean) float32 dask.array&lt;chunksize=(1, 1070, 1440), meta=np.ndarray&gt;\n",
" ty_trans (time, st_ocean, yu_ocean, xt_ocean) float32 dask.array&lt;chunksize=(1, 50, 1070, 1440), meta=np.ndarray&gt;\n",
"Attributes:\n",
" filename: soda3.4.2_10dy_transport_or_1993_01_07.nc\n",
" grid_tile: 1\n",
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" title: MOM5_SODA_3.4.2</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-84b998a6-2553-4da2-af1f-3c4cc245b6ed' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-84b998a6-2553-4da2-af1f-3c4cc245b6ed' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>st_edges_ocean</span>: 51</li><li><span class='xr-has-index'>st_ocean</span>: 50</li><li><span class='xr-has-index'>time</span>: 985</li><li><span class='xr-has-index'>xt_ocean</span>: 1440</li><li><span class='xr-has-index'>xu_ocean</span>: 1440</li><li><span class='xr-has-index'>yt_ocean</span>: 1070</li><li><span class='xr-has-index'>yu_ocean</span>: 1070</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c6deabed-745b-4c78-ac6b-0bd5f5f23ad7' class='xr-section-summary-in' type='checkbox' checked><label for='section-c6deabed-745b-4c78-ac6b-0bd5f5f23ad7' class='xr-section-summary' >Coordinates: <span>(8)</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'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-f8ab43e6-a2ae-46ce-bb52-3ff23724348f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8ab43e6-a2ae-46ce-bb52-3ff23724348f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d267c80-081b-47e6-84db-54a7e40efede' class='xr-var-data-in' type='checkbox'><label for='data-1d267c80-081b-47e6-84db-54a7e40efede' 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>cartesian_axis :</span></dt><dd>N</dd><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>st_edges_ocean</span></div><div class='xr-var-dims'>(st_edges_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 10.07 ... 5.29e+03 5.5e+03</div><input id='attrs-05d77e35-e74d-48b5-9107-0c5ef0c03fb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05d77e35-e74d-48b5-9107-0c5ef0c03fb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8951a6f8-2e97-4294-bd71-d4b7436bf128' class='xr-var-data-in' type='checkbox'><label for='data-8951a6f8-2e97-4294-bd71-d4b7436bf128' 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>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>tcell zstar depth edges</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([ 0. , 10.0671 , 20.16 , 30.2889 , 40.4674 ,\n",
" 50.714802, 61.057499, 71.532303, 82.189903, 93.100098,\n",
" 104.359703, 116.101402, 128.507599, 141.827606, 156.400208,\n",
" 172.683105, 191.287704, 213.020096, 238.922699, 270.309509,\n",
" 308.779297, 356.186401, 414.545685, 485.854401, 571.842773,\n",
" 673.697571, 791.842773, 925.85437 , 1074.545654, 1236.186401,\n",
" 1408.779297, 1590.30957 , 1778.922729, 1973.020142, 2171.287598,\n",
" 2372.683105, 2576.400146, 2781.827637, 2988.507568, 3196.101562,\n",
" 3404.359619, 3613.100098, 3822.189941, 4031.532227, 4241.057617,\n",
" 4450.714844, 4660.467285, 4870.289062, 5080.160156, 5290.066895,\n",
" 5500. ])</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'>5.034 15.1 ... 5.185e+03 5.395e+03</div><input id='attrs-635a3878-d6ec-4d25-8465-9e44d9ae4b5f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-635a3878-d6ec-4d25-8465-9e44d9ae4b5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50c96473-f427-4844-8464-6ea554131934' class='xr-var-data-in' type='checkbox'><label for='data-50c96473-f427-4844-8464-6ea554131934' 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>cartesian_axis :</span></dt><dd>Z</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd><dt><span>long_name :</span></dt><dd>tcell zstar depth</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([5.033550e+00, 1.510065e+01, 2.521935e+01, 3.535845e+01, 4.557635e+01,\n",
" 5.585325e+01, 6.626175e+01, 7.680285e+01, 8.757695e+01, 9.862325e+01,\n",
" 1.100962e+02, 1.221067e+02, 1.349086e+02, 1.487466e+02, 1.640538e+02,\n",
" 1.813125e+02, 2.012630e+02, 2.247773e+02, 2.530681e+02, 2.875508e+02,\n",
" 3.300078e+02, 3.823651e+02, 4.467263e+02, 5.249824e+02, 6.187031e+02,\n",
" 7.286921e+02, 8.549935e+02, 9.967153e+02, 1.152376e+03, 1.319997e+03,\n",
" 1.497562e+03, 1.683057e+03, 1.874788e+03, 2.071252e+03, 2.271323e+03,\n",
" 2.474043e+03, 2.678757e+03, 2.884898e+03, 3.092117e+03, 3.300086e+03,\n",
" 3.508633e+03, 3.717567e+03, 3.926813e+03, 4.136251e+03, 4.345864e+03,\n",
" 4.555566e+03, 4.765369e+03, 4.975209e+03, 5.185111e+03, 5.395023e+03])</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'>1993-01-07 01:00:00 ... 2019-12-...</div><input id='attrs-33e303fe-cb31-4df2-aba8-3fd82d5b2abd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33e303fe-cb31-4df2-aba8-3fd82d5b2abd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf310bc2-fe9b-4672-92aa-183a70638b30' class='xr-var-data-in' type='checkbox'><label for='data-bf310bc2-fe9b-4672-92aa-183a70638b30' 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>bounds :</span></dt><dd>time_bounds</dd><dt><span>calendar_type :</span></dt><dd>JULIAN</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeJulian(1993, 1, 7, 1, 0, 0, 0),\n",
" cftime.DatetimeJulian(1993, 1, 17, 1, 0, 0, 0),\n",
" cftime.DatetimeJulian(1993, 1, 27, 1, 0, 0, 0), ...,\n",
" cftime.DatetimeJulian(2019, 11, 27, 1, 0, 0, 0),\n",
" cftime.DatetimeJulian(2019, 12, 7, 1, 0, 0, 0),\n",
" cftime.DatetimeJulian(2019, 12, 17, 1, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xt_ocean</span></div><div class='xr-var-dims'>(xt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-279.9 -279.6 ... 79.62 79.88</div><input id='attrs-69c3f6fb-9220-4275-8b23-db8eea0eadb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69c3f6fb-9220-4275-8b23-db8eea0eadb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-324573cd-17f9-4a58-b1a8-fbacf8200853' class='xr-var-data-in' type='checkbox'><label for='data-324573cd-17f9-4a58-b1a8-fbacf8200853' 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>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>tcell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd></dl></div><div class='xr-var-data'><pre>array([-279.875, -279.625, -279.375, ..., 79.375, 79.625, 79.875])</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-1935b6d9-02f3-4ef2-a216-3ff3104e2339' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1935b6d9-02f3-4ef2-a216-3ff3104e2339' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9848d98-9806-43a6-9e4c-b727ac28f17f' class='xr-var-data-in' type='checkbox'><label for='data-c9848d98-9806-43a6-9e4c-b727ac28f17f' 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>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</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'>yt_ocean</span></div><div class='xr-var-dims'>(yt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.02 -79.92 ... 89.84 89.95</div><input id='attrs-bba2a8f8-d42e-4ed6-9b88-dfc24d4caff5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bba2a8f8-d42e-4ed6-9b88-dfc24d4caff5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71cc1a9c-2b98-4f97-84ee-c1107053c020' class='xr-var-data-in' type='checkbox'><label for='data-71cc1a9c-2b98-4f97-84ee-c1107053c020' 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>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>tcell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-80.021015, -79.915416, -79.809818, ..., 89.736085, 89.841684,\n",
" 89.947282])</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'>-79.97 -79.86 -79.76 ... 89.89 90.0</div><input id='attrs-7185b2a6-cf9b-41ed-9ff5-e1dbe0d072e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7185b2a6-cf9b-41ed-9ff5-e1dbe0d072e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5feb547c-6bc6-4057-a087-f021a95ef02d' class='xr-var-data-in' type='checkbox'><label for='data-5feb547c-6bc6-4057-a087-f021a95ef02d' 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>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-79.968216, -79.862617, -79.757018, ..., 89.788884, 89.894483,\n",
" 90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1581de7a-4589-45e1-a5e7-81bb2ca4cba9' class='xr-section-summary-in' type='checkbox' checked><label for='section-1581de7a-4589-45e1-a5e7-81bb2ca4cba9' class='xr-section-summary' >Data variables: <span>(8)</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>average_DT</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-2453cb63-98d4-475f-ad06-467dd3fc952e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2453cb63-98d4-475f-ad06-467dd3fc952e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aef1d1ea-cba8-4ac3-9fdb-cf94ede41658' class='xr-var-data-in' type='checkbox'><label for='data-aef1d1ea-cba8-4ac3-9fdb-cf94ede41658' 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>Length of average period</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> 7.70 kiB </td> <td> 8 B </td></tr>\n",
" <tr><th> Shape </th><td> (985,) </td> <td> (1,) </td></tr>\n",
" <tr><th> Count </th><td> 986 Tasks </td><td> 985 Chunks </td></tr>\n",
" <tr><th> Type </th><td> timedelta64[ns] </td><td> numpy.ndarray </td></tr>\n",
" </tbody>\n",
"</table>\n",
"</td>\n",
"<td>\n",
"<svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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"\n",
" <!-- Vertical lines -->\n",
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" <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
" <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
" <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
" <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
" <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"25\" />\n",
" <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
" <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
" <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
" <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
" <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
" <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
" <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
" <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
" <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
" <line x1=\"107\" y1=\"0\" x2=\"107\" y2=\"25\" />\n",
" <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
"\n",
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >985</text>\n",
" <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
"</svg>\n",
"</td>\n",
"</tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T1</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-0c5c17ad-5a8a-4c96-a66a-1141cac94f83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c5c17ad-5a8a-4c96-a66a-1141cac94f83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67b2c9b0-7d18-4050-be82-2f554bae5e62' class='xr-var-data-in' type='checkbox'><label for='data-67b2c9b0-7d18-4050-be82-2f554bae5e62' 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>Start time for average period</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> 7.70 kiB </td> <td> 8 B </td></tr>\n",
" <tr><th> Shape </th><td> (985,) </td> <td> (1,) </td></tr>\n",
" <tr><th> Count </th><td> 986 Tasks </td><td> 985 Chunks </td></tr>\n",
" <tr><th> Type </th><td> datetime64[ns] </td><td> numpy.ndarray </td></tr>\n",
" </tbody>\n",
"</table>\n",
"</td>\n",
"<td>\n",
"<svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
" <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
" <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
" <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
" <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
" <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
" <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
" <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"25\" />\n",
" <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
" <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
" <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
" <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
" <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
" <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
" <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
" <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
" <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
" <line x1=\"107\" y1=\"0\" x2=\"107\" y2=\"25\" />\n",
" <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
"\n",
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >985</text>\n",
" <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
"</svg>\n",
"</td>\n",
"</tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-1b3bee35-9053-465e-a579-495d735b74c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b3bee35-9053-465e-a579-495d735b74c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d1b8569-6e3d-4991-ba22-fb12a1afef2d' class='xr-var-data-in' type='checkbox'><label for='data-8d1b8569-6e3d-4991-ba22-fb12a1afef2d' 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>End time for average period</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> 7.70 kiB </td> <td> 8 B </td></tr>\n",
" <tr><th> Shape </th><td> (985,) </td> <td> (1,) </td></tr>\n",
" <tr><th> Count </th><td> 986 Tasks </td><td> 985 Chunks </td></tr>\n",
" <tr><th> Type </th><td> datetime64[ns] </td><td> numpy.ndarray </td></tr>\n",
" </tbody>\n",
"</table>\n",
"</td>\n",
"<td>\n",
"<svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
" <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
" <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
" <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
" <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
" <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
" <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
" <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"25\" />\n",
" <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
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],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (nv: 2, st_edges_ocean: 51, st_ocean: 50, time: 985, xt_ocean: 1440, xu_ocean: 1440, yt_ocean: 1070, yu_ocean: 1070)\n",
"Coordinates:\n",
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"Data variables:\n",
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" average_T2 (time) datetime64[ns] dask.array<chunksize=(1,), meta=np.ndarray>\n",
" time_bounds (time, nv) timedelta64[ns] dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
" tx_int (time, yt_ocean, xu_ocean) float32 dask.array<chunksize=(1, 1070, 1440), meta=np.ndarray>\n",
" tx_trans (time, st_ocean, yt_ocean, xu_ocean) float32 dask.array<chunksize=(1, 50, 1070, 1440), meta=np.ndarray>\n",
" ty_int (time, yu_ocean, xt_ocean) float32 dask.array<chunksize=(1, 1070, 1440), meta=np.ndarray>\n",
" ty_trans (time, st_ocean, yu_ocean, xt_ocean) float32 dask.array<chunksize=(1, 50, 1070, 1440), meta=np.ndarray>\n",
"Attributes:\n",
" filename: soda3.4.2_10dy_transport_or_1993_01_07.nc\n",
" grid_tile: 1\n",
" grid_type: mosaic\n",
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]
},
"execution_count": 2,
"metadata": {},
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}
],
"source": [
"ds_trans = xr.open_zarr(\"gs://pangeo-forge-us-central1/pangeo-forge/soda/soda3.4.2_10dy_transport_or\",\n",
" consolidated=True)\n",
"ds_trans"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "554efeb5-f065-4be3-9c63-be7716ea20b1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f0d3a636730>"
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},
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"metadata": {},
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{
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"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"tx_trans = ds_trans.tx_trans[0, 0].load()\n",
"tx_trans.plot()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "8c81fe2f-0075-46c5-a11c-1f03da158a1e",
"metadata": {},
"outputs": [
{
"data": {
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" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=dark],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
" --xr-border-color: #1F1F1F;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
" --xr-background-color-row-odd: #313131;\n",
"}\n",
"\n",
".xr-wrap {\n",
" display: block;\n",
" min-width: 300px;\n",
" max-width: 700px;\n",
"}\n",
"\n",
".xr-text-repr-fallback {\n",
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
" display: none;\n",
"}\n",
"\n",
".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
" border-bottom: solid 1px var(--xr-border-color);\n",
"}\n",
"\n",
".xr-header > div,\n",
".xr-header > ul {\n",
" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: '►';\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: '▼';\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: '(';\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: ')';\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: ',';\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data {\n",
" 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",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (nv: 2, st_edges_ocean: 51, st_ocean: 50, sw_edges_ocean: 51, sw_ocean: 50, time: 1970, xt_ocean: 1440, xu_ocean: 1440, yt_ocean: 1070, yu_ocean: 1070)\n",
"Coordinates:\n",
" * nv (nv) float64 1.0 2.0\n",
" * st_edges_ocean (st_edges_ocean) float64 0.0 10.07 ... 5.29e+03 5.5e+03\n",
" * st_ocean (st_ocean) float64 5.034 15.1 25.22 ... 5.185e+03 5.395e+03\n",
" * sw_edges_ocean (sw_edges_ocean) float64 5.034 15.1 ... 5.395e+03 5.5e+03\n",
" * sw_ocean (sw_ocean) float64 10.07 20.16 30.29 ... 5.29e+03 5.5e+03\n",
" * time (time) object 1993-01-04 13:00:00 ... 2019-12-19 13:00:00\n",
" * xt_ocean (xt_ocean) float64 -279.9 -279.6 -279.4 ... 79.62 79.88\n",
" * xu_ocean (xu_ocean) float64 -279.8 -279.5 -279.2 ... 79.5 79.75 80.0\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.84 89.95\n",
" * yu_ocean (yu_ocean) float64 -79.97 -79.86 -79.76 ... 89.89 90.0\n",
"Data variables: (12/32)\n",
" anompb (time, yt_ocean, xt_ocean) float32 dask.array&lt;chunksize=(1, 1070, 1440), meta=np.ndarray&gt;\n",
" average_DT (time) timedelta64[ns] dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" average_T1 (time) datetime64[ns] dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" average_T2 (time) datetime64[ns] dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
" evap_heat (time, yt_ocean, xt_ocean) float32 dask.array&lt;chunksize=(1, 1070, 1440), meta=np.ndarray&gt;\n",
" hflux_cpl (time, yt_ocean, xt_ocean) float32 dask.array&lt;chunksize=(1, 1070, 1440), meta=np.ndarray&gt;\n",
" ... ...\n",
" tauy (time, yu_ocean, xu_ocean) float32 dask.array&lt;chunksize=(1, 1070, 1440), meta=np.ndarray&gt;\n",
" temp (time, st_ocean, yt_ocean, xt_ocean) float32 dask.array&lt;chunksize=(1, 50, 1070, 1440), meta=np.ndarray&gt;\n",
" time_bounds (time, nv) timedelta64[ns] dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;\n",
" u (time, st_ocean, yu_ocean, xu_ocean) float32 dask.array&lt;chunksize=(1, 50, 1070, 1440), meta=np.ndarray&gt;\n",
" v (time, st_ocean, yu_ocean, xu_ocean) float32 dask.array&lt;chunksize=(1, 50, 1070, 1440), meta=np.ndarray&gt;\n",
" wt (time, sw_ocean, yt_ocean, xt_ocean) float32 dask.array&lt;chunksize=(1, 50, 1070, 1440), meta=np.ndarray&gt;\n",
"Attributes:\n",
" filename: soda3.4.2_5dy_ocean_or_1993_01_04.nc\n",
" grid_tile: 1\n",
" grid_type: mosaic\n",
" title: MOM5_SODA_3.4.2</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-ab06eb67-ada8-4bff-b58d-51d9e4099885' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ab06eb67-ada8-4bff-b58d-51d9e4099885' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nv</span>: 2</li><li><span class='xr-has-index'>st_edges_ocean</span>: 51</li><li><span class='xr-has-index'>st_ocean</span>: 50</li><li><span class='xr-has-index'>sw_edges_ocean</span>: 51</li><li><span class='xr-has-index'>sw_ocean</span>: 50</li><li><span class='xr-has-index'>time</span>: 1970</li><li><span class='xr-has-index'>xt_ocean</span>: 1440</li><li><span class='xr-has-index'>xu_ocean</span>: 1440</li><li><span class='xr-has-index'>yt_ocean</span>: 1070</li><li><span class='xr-has-index'>yu_ocean</span>: 1070</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a4315e86-92de-4b18-9baa-1d075b829eb9' class='xr-section-summary-in' type='checkbox' checked><label for='section-a4315e86-92de-4b18-9baa-1d075b829eb9' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nv</span></div><div class='xr-var-dims'>(nv)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0</div><input id='attrs-dc443a9c-b568-4002-9060-f83c06cef363' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc443a9c-b568-4002-9060-f83c06cef363' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15b01fc8-10de-4870-9825-8d22d4aafbfa' class='xr-var-data-in' type='checkbox'><label for='data-15b01fc8-10de-4870-9825-8d22d4aafbfa' 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>cartesian_axis :</span></dt><dd>N</dd><dt><span>long_name :</span></dt><dd>vertex number</dd><dt><span>units :</span></dt><dd>none</dd></dl></div><div class='xr-var-data'><pre>array([1., 2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>st_edges_ocean</span></div><div class='xr-var-dims'>(st_edges_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 10.07 ... 5.29e+03 5.5e+03</div><input id='attrs-2bfde48a-208c-42a5-a26a-fa3da9822965' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bfde48a-208c-42a5-a26a-fa3da9822965' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb09f46f-441c-46ee-94b0-b904e0bf96b2' class='xr-var-data-in' type='checkbox'><label for='data-fb09f46f-441c-46ee-94b0-b904e0bf96b2' 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>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>tcell zstar depth edges</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([ 0. , 10.0671 , 20.16 , 30.2889 , 40.4674 ,\n",
" 50.714802, 61.057499, 71.532303, 82.189903, 93.100098,\n",
" 104.359703, 116.101402, 128.507599, 141.827606, 156.400208,\n",
" 172.683105, 191.287704, 213.020096, 238.922699, 270.309509,\n",
" 308.779297, 356.186401, 414.545685, 485.854401, 571.842773,\n",
" 673.697571, 791.842773, 925.85437 , 1074.545654, 1236.186401,\n",
" 1408.779297, 1590.30957 , 1778.922729, 1973.020142, 2171.287598,\n",
" 2372.683105, 2576.400146, 2781.827637, 2988.507568, 3196.101562,\n",
" 3404.359619, 3613.100098, 3822.189941, 4031.532227, 4241.057617,\n",
" 4450.714844, 4660.467285, 4870.289062, 5080.160156, 5290.066895,\n",
" 5500. ])</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'>5.034 15.1 ... 5.185e+03 5.395e+03</div><input id='attrs-d9697daf-4d55-4af0-8f05-83532113575d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9697daf-4d55-4af0-8f05-83532113575d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7f651ad-22bc-4977-969d-0ac95327465f' class='xr-var-data-in' type='checkbox'><label for='data-f7f651ad-22bc-4977-969d-0ac95327465f' 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>cartesian_axis :</span></dt><dd>Z</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd><dt><span>long_name :</span></dt><dd>tcell zstar depth</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([5.033550e+00, 1.510065e+01, 2.521935e+01, 3.535845e+01, 4.557635e+01,\n",
" 5.585325e+01, 6.626175e+01, 7.680285e+01, 8.757695e+01, 9.862325e+01,\n",
" 1.100962e+02, 1.221067e+02, 1.349086e+02, 1.487466e+02, 1.640538e+02,\n",
" 1.813125e+02, 2.012630e+02, 2.247773e+02, 2.530681e+02, 2.875508e+02,\n",
" 3.300078e+02, 3.823651e+02, 4.467263e+02, 5.249824e+02, 6.187031e+02,\n",
" 7.286921e+02, 8.549935e+02, 9.967153e+02, 1.152376e+03, 1.319997e+03,\n",
" 1.497562e+03, 1.683057e+03, 1.874788e+03, 2.071252e+03, 2.271323e+03,\n",
" 2.474043e+03, 2.678757e+03, 2.884898e+03, 3.092117e+03, 3.300086e+03,\n",
" 3.508633e+03, 3.717567e+03, 3.926813e+03, 4.136251e+03, 4.345864e+03,\n",
" 4.555566e+03, 4.765369e+03, 4.975209e+03, 5.185111e+03, 5.395023e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sw_edges_ocean</span></div><div class='xr-var-dims'>(sw_edges_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.034 15.1 ... 5.395e+03 5.5e+03</div><input id='attrs-5bf678c0-9ddb-4123-8dc0-cc2c69bd12fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5bf678c0-9ddb-4123-8dc0-cc2c69bd12fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9feddd32-5246-44d0-bb17-bc8664a9b5f3' class='xr-var-data-in' type='checkbox'><label for='data-9feddd32-5246-44d0-bb17-bc8664a9b5f3' 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>cartesian_axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>ucell zstar depth edges</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([5.033550e+00, 1.510065e+01, 2.521935e+01, 3.535845e+01, 4.557635e+01,\n",
" 5.585325e+01, 6.626175e+01, 7.680285e+01, 8.757695e+01, 9.862325e+01,\n",
" 1.100962e+02, 1.221067e+02, 1.349086e+02, 1.487466e+02, 1.640538e+02,\n",
" 1.813125e+02, 2.012630e+02, 2.247773e+02, 2.530681e+02, 2.875508e+02,\n",
" 3.300078e+02, 3.823651e+02, 4.467263e+02, 5.249824e+02, 6.187031e+02,\n",
" 7.286921e+02, 8.549935e+02, 9.967153e+02, 1.152376e+03, 1.319997e+03,\n",
" 1.497562e+03, 1.683057e+03, 1.874788e+03, 2.071252e+03, 2.271323e+03,\n",
" 2.474043e+03, 2.678757e+03, 2.884898e+03, 3.092117e+03, 3.300086e+03,\n",
" 3.508633e+03, 3.717567e+03, 3.926813e+03, 4.136251e+03, 4.345864e+03,\n",
" 4.555566e+03, 4.765369e+03, 4.975209e+03, 5.185111e+03, 5.395023e+03,\n",
" 5.500000e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sw_ocean</span></div><div class='xr-var-dims'>(sw_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.07 20.16 ... 5.29e+03 5.5e+03</div><input id='attrs-89c047e9-c073-4f02-b97b-cb1101af5d0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89c047e9-c073-4f02-b97b-cb1101af5d0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ccde8f4-ed6e-4b81-aa51-e2ddb38e3df7' class='xr-var-data-in' type='checkbox'><label for='data-2ccde8f4-ed6e-4b81-aa51-e2ddb38e3df7' 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>cartesian_axis :</span></dt><dd>Z</dd><dt><span>edges :</span></dt><dd>sw_edges_ocean</dd><dt><span>long_name :</span></dt><dd>ucell zstar depth</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([ 10.0671 , 20.16 , 30.2889 , 40.4674 , 50.714802,\n",
" 61.057499, 71.532303, 82.189903, 93.100098, 104.359703,\n",
" 116.101402, 128.507599, 141.827606, 156.400208, 172.683105,\n",
" 191.287704, 213.020096, 238.922699, 270.309509, 308.779297,\n",
" 356.186401, 414.545685, 485.854401, 571.842773, 673.697571,\n",
" 791.842773, 925.85437 , 1074.545654, 1236.186401, 1408.779297,\n",
" 1590.30957 , 1778.922729, 1973.020142, 2171.287598, 2372.683105,\n",
" 2576.400146, 2781.827637, 2988.507568, 3196.101562, 3404.359619,\n",
" 3613.100098, 3822.189941, 4031.532227, 4241.057617, 4450.714844,\n",
" 4660.467285, 4870.289062, 5080.160156, 5290.066895, 5500. ])</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'>1993-01-04 13:00:00 ... 2019-12-...</div><input id='attrs-8b3c5417-56d3-426e-b574-b2e213607cf3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b3c5417-56d3-426e-b574-b2e213607cf3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-670bcd71-ddb4-4b26-a758-3cb34ab2c579' class='xr-var-data-in' type='checkbox'><label for='data-670bcd71-ddb4-4b26-a758-3cb34ab2c579' 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>bounds :</span></dt><dd>time_bounds</dd><dt><span>calendar_type :</span></dt><dd>JULIAN</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeJulian(1993, 1, 4, 13, 0, 0, 0),\n",
" cftime.DatetimeJulian(1993, 1, 9, 13, 0, 0, 0),\n",
" cftime.DatetimeJulian(1993, 1, 14, 13, 0, 0, 0), ...,\n",
" cftime.DatetimeJulian(2019, 12, 9, 13, 0, 0, 0),\n",
" cftime.DatetimeJulian(2019, 12, 14, 13, 0, 0, 0),\n",
" cftime.DatetimeJulian(2019, 12, 19, 13, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xt_ocean</span></div><div class='xr-var-dims'>(xt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-279.9 -279.6 ... 79.62 79.88</div><input id='attrs-c09b9ba0-c5ed-4db7-ad84-90bb95f7df78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c09b9ba0-c5ed-4db7-ad84-90bb95f7df78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ffdf034-35ee-40bf-8d88-8b8c50a68cad' class='xr-var-data-in' type='checkbox'><label for='data-0ffdf034-35ee-40bf-8d88-8b8c50a68cad' 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>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>tcell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd></dl></div><div class='xr-var-data'><pre>array([-279.875, -279.625, -279.375, ..., 79.375, 79.625, 79.875])</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-1aab003d-b453-4bd9-a803-2fc8c53c003f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1aab003d-b453-4bd9-a803-2fc8c53c003f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe14e972-50a3-44bd-a9e6-c21f85b3811f' class='xr-var-data-in' type='checkbox'><label for='data-fe14e972-50a3-44bd-a9e6-c21f85b3811f' 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>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</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'>yt_ocean</span></div><div class='xr-var-dims'>(yt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.02 -79.92 ... 89.84 89.95</div><input id='attrs-acc0b27b-6b21-4736-86a0-10d261b47696' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acc0b27b-6b21-4736-86a0-10d261b47696' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20f39bfb-94ff-4750-9d65-1673c1a7405a' class='xr-var-data-in' type='checkbox'><label for='data-20f39bfb-94ff-4750-9d65-1673c1a7405a' 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>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>tcell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-80.021015, -79.915416, -79.809818, ..., 89.736085, 89.841684,\n",
" 89.947282])</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'>-79.97 -79.86 -79.76 ... 89.89 90.0</div><input id='attrs-4353e1ec-2ae8-407a-9839-ad0aad956520' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4353e1ec-2ae8-407a-9839-ad0aad956520' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edb703b2-4bae-48ad-bce9-d022d60d7eb0' class='xr-var-data-in' type='checkbox'><label for='data-edb703b2-4bae-48ad-bce9-d022d60d7eb0' 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>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-79.968216, -79.862617, -79.757018, ..., 89.788884, 89.894483,\n",
" 90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-99a1e5e4-81b1-4309-aca7-53e8a105c64c' class='xr-section-summary-in' type='checkbox' ><label for='section-99a1e5e4-81b1-4309-aca7-53e8a105c64c' class='xr-section-summary' >Data variables: <span>(32)</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>anompb</span></div><div class='xr-var-dims'>(time, yt_ocean, xt_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1070, 1440), meta=np.ndarray&gt;</div><input id='attrs-cefb3a70-2f1c-4ce6-9313-9e50f88d2cb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cefb3a70-2f1c-4ce6-9313-9e50f88d2cb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28a15e89-1952-412f-bf87-960581805746' class='xr-var-data-in' type='checkbox'><label for='data-28a15e89-1952-412f-bf87-960581805746' 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_methods :</span></dt><dd>time: mean</dd><dt><span>coordinates :</span></dt><dd>geolon_t geolat_t</dd><dt><span>long_name :</span></dt><dd>T-cell bottom pressure - rho0*grav*ht</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>dbar</dd><dt><span>valid_range :</span></dt><dd>[-1000000.0, 1000000.0]</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> 11.31 GiB </td> <td> 5.88 MiB </td></tr>\n",
" <tr><th> Shape </th><td> (1970, 1070, 1440) </td> <td> (1, 1070, 1440) </td></tr>\n",
" <tr><th> Count </th><td> 1971 Tasks </td><td> 1970 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>average_DT</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-ad5b324b-a555-40be-b031-4f0ecb15d7db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad5b324b-a555-40be-b031-4f0ecb15d7db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a2a394d-786a-455d-99f6-8803b93fa699' class='xr-var-data-in' type='checkbox'><label for='data-6a2a394d-786a-455d-99f6-8803b93fa699' 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>Length of average period</dd></dl></div><div class='xr-var-data'><table>\n",
"<tr>\n",
"<td>\n",
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" <tr><th> Shape </th><td> (1970,) </td> <td> (1,) </td></tr>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_T1</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-9fb28a42-b618-4203-9a6c-d6e28e1de67b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fb28a42-b618-4203-9a6c-d6e28e1de67b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d348ca0-2077-4b7f-8558-243d4c67f479' class='xr-var-data-in' type='checkbox'><label for='data-5d348ca0-2077-4b7f-8558-243d4c67f479' 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>Start time for average period</dd></dl></div><div class='xr-var-data'><table>\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>evap_heat</span></div><div class='xr-var-dims'>(time, yt_ocean, xt_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1070, 1440), meta=np.ndarray&gt;</div><input id='attrs-2c5b536a-1bd0-4b67-91c8-2ee749c91b24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c5b536a-1bd0-4b67-91c8-2ee749c91b24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78e08086-9bf4-44e1-9ce4-888cf0954439' class='xr-var-data-in' type='checkbox'><label for='data-78e08086-9bf4-44e1-9ce4-888cf0954439' 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_methods :</span></dt><dd>time: mean</dd><dt><span>coordinates :</span></dt><dd>geolon_t geolat_t</dd><dt><span>long_name :</span></dt><dd>latent heat flux into ocean (&lt;0 cools ocean)</dd><dt><span>standard_name :</span></dt><dd>surface_downward_latent_heat_flux</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>W/m^2</dd><dt><span>valid_range :</span></dt><dd>[-10000000000.0, 10000000000.0]</dd></dl></div><div class='xr-var-data'><table>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>net_heating</span></div><div class='xr-var-dims'>(time, yt_ocean, xt_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1070, 1440), meta=np.ndarray&gt;</div><input id='attrs-29d50d4b-80bc-4359-975b-20fbedf90807' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29d50d4b-80bc-4359-975b-20fbedf90807' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-918bbf7f-f422-4181-8e6c-e286a49466e8' class='xr-var-data-in' type='checkbox'><label for='data-918bbf7f-f422-4181-8e6c-e286a49466e8' 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_methods :</span></dt><dd>time: mean</dd><dt><span>coordinates :</span></dt><dd>geolon_t geolat_t</dd><dt><span>long_name :</span></dt><dd>surface ocean heat flux coming through coupler and mass transfer</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>Watts/m^2</dd><dt><span>valid_range :</span></dt><dd>[-10000.0, 10000.0]</dd></dl></div><div class='xr-var-data'><table>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salt</span></div><div class='xr-var-dims'>(time, st_ocean, yt_ocean, xt_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 50, 1070, 1440), meta=np.ndarray&gt;</div><input id='attrs-60a35295-497b-4c2b-9221-1692631ba5e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60a35295-497b-4c2b-9221-1692631ba5e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ece890de-6f2a-4814-abef-ee1b864fd163' class='xr-var-data-in' type='checkbox'><label for='data-ece890de-6f2a-4814-abef-ee1b864fd163' 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_methods :</span></dt><dd>time: mean</dd><dt><span>coordinates :</span></dt><dd>geolon_t geolat_t</dd><dt><span>long_name :</span></dt><dd>Practical Salinity</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>psu</dd><dt><span>valid_range :</span></dt><dd>[-10.0, 100.0]</dd></dl></div><div class='xr-var-data'><table>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time, st_ocean, yt_ocean, xt_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 50, 1070, 1440), meta=np.ndarray&gt;</div><input id='attrs-7c08560d-ede2-485b-9e6f-927929f10326' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c08560d-ede2-485b-9e6f-927929f10326' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd26a0e5-dffc-4178-b6de-06a4fd176612' class='xr-var-data-in' type='checkbox'><label for='data-dd26a0e5-dffc-4178-b6de-06a4fd176612' 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_methods :</span></dt><dd>time: mean</dd><dt><span>coordinates :</span></dt><dd>geolon_t geolat_t</dd><dt><span>long_name :</span></dt><dd>Potential temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>degrees C</dd><dt><span>valid_range :</span></dt><dd>[-10.0, 500.0]</dd></dl></div><div class='xr-var-data'><table>\n",
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],
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},
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"metadata": {},
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}
],
"source": [
"ds_full = xr.open_zarr(\"gs://pangeo-forge-us-central1/pangeo-forge/soda/soda3.4.2_5dy_ocean_or\",\n",
" consolidated=True)\n",
"ds_full"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "95e92a6e-6cf0-4df1-a1a1-22dd53b89158",
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (xt_ocean: 1440, xu_ocean: 1440, yt_ocean: 1070, yu_ocean: 1070)\n",
"Coordinates:\n",
" st_ocean float64 5.034\n",
" time object 1993-01-04 13:00:00\n",
" * xt_ocean (xt_ocean) float64 -279.9 -279.6 -279.4 ... 79.38 79.62 79.88\n",
" * xu_ocean (xu_ocean) float64 -279.8 -279.5 -279.2 -279.0 ... 79.5 79.75 80.0\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.74 89.84 89.95\n",
" * yu_ocean (yu_ocean) float64 -79.97 -79.86 -79.76 ... 89.79 89.89 90.0\n",
"Data variables:\n",
" temp (yt_ocean, xt_ocean) float32 nan nan nan nan ... nan nan nan nan\n",
" u (yu_ocean, xu_ocean) float32 nan nan nan nan ... nan nan nan nan\n",
" v (yu_ocean, xu_ocean) float32 nan nan nan nan ... nan nan nan nan\n",
"Attributes:\n",
" filename: soda3.4.2_5dy_ocean_or_1993_01_04.nc\n",
" grid_tile: 1\n",
" grid_type: mosaic\n",
" title: MOM5_SODA_3.4.2</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-794f28dd-955c-4f85-a834-22874b5af8ee' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-794f28dd-955c-4f85-a834-22874b5af8ee' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>xt_ocean</span>: 1440</li><li><span class='xr-has-index'>xu_ocean</span>: 1440</li><li><span class='xr-has-index'>yt_ocean</span>: 1070</li><li><span class='xr-has-index'>yu_ocean</span>: 1070</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ed8e14b0-137e-46bd-9a08-3090c1286ea4' class='xr-section-summary-in' type='checkbox' checked><label for='section-ed8e14b0-137e-46bd-9a08-3090c1286ea4' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>st_ocean</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.034</div><input id='attrs-ec5f9070-3849-4621-a9be-cd21af5822a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec5f9070-3849-4621-a9be-cd21af5822a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96f80369-b91c-4f9c-96f4-5bf5c87a2f4e' class='xr-var-data-in' type='checkbox'><label for='data-96f80369-b91c-4f9c-96f4-5bf5c87a2f4e' 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>cartesian_axis :</span></dt><dd>Z</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd><dt><span>long_name :</span></dt><dd>tcell zstar depth</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array(5.03354979)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1993-01-04 13:00:00</div><input id='attrs-b4ed5a98-182c-489b-b1ba-e9258144a551' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4ed5a98-182c-489b-b1ba-e9258144a551' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-870f474b-a4ff-4efc-b93b-42486cab9d7b' class='xr-var-data-in' type='checkbox'><label for='data-870f474b-a4ff-4efc-b93b-42486cab9d7b' 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>bounds :</span></dt><dd>time_bounds</dd><dt><span>calendar_type :</span></dt><dd>JULIAN</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(cftime.DatetimeJulian(1993, 1, 4, 13, 0, 0, 0), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xt_ocean</span></div><div class='xr-var-dims'>(xt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-279.9 -279.6 ... 79.62 79.88</div><input id='attrs-3b61a7ed-7d77-40f3-97f6-63af5d42f96d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b61a7ed-7d77-40f3-97f6-63af5d42f96d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e135c79-6392-4375-ac7d-2ef0166b76a7' class='xr-var-data-in' type='checkbox'><label for='data-0e135c79-6392-4375-ac7d-2ef0166b76a7' 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>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>tcell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd></dl></div><div class='xr-var-data'><pre>array([-279.875, -279.625, -279.375, ..., 79.375, 79.625, 79.875])</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-5a2e1ee1-8809-4119-a885-2acc8e14a19c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a2e1ee1-8809-4119-a885-2acc8e14a19c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e4420f0-de27-4976-97a7-dc79a13eeaea' class='xr-var-data-in' type='checkbox'><label for='data-8e4420f0-de27-4976-97a7-dc79a13eeaea' 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>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</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'>yt_ocean</span></div><div class='xr-var-dims'>(yt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.02 -79.92 ... 89.84 89.95</div><input id='attrs-3bbd4a74-4036-4e9d-96e2-7bec9ba89505' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bbd4a74-4036-4e9d-96e2-7bec9ba89505' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1e06237-985d-4c81-b6c8-dc5a311fc179' class='xr-var-data-in' type='checkbox'><label for='data-d1e06237-985d-4c81-b6c8-dc5a311fc179' 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>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>tcell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-80.021015, -79.915416, -79.809818, ..., 89.736085, 89.841684,\n",
" 89.947282])</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'>-79.97 -79.86 -79.76 ... 89.89 90.0</div><input id='attrs-85c243d1-37b0-4cbf-a3dc-d013f76f5844' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85c243d1-37b0-4cbf-a3dc-d013f76f5844' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e4c7c4f-87ce-4d70-81c7-788382f03a06' class='xr-var-data-in' type='checkbox'><label for='data-6e4c7c4f-87ce-4d70-81c7-788382f03a06' 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>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>ucell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-79.968216, -79.862617, -79.757018, ..., 89.788884, 89.894483,\n",
" 90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fdb0f16f-dd87-47ab-89ed-6fb805fc8338' class='xr-section-summary-in' type='checkbox' checked><label for='section-fdb0f16f-dd87-47ab-89ed-6fb805fc8338' class='xr-section-summary' >Data variables: <span>(3)</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>temp</span></div><div class='xr-var-dims'>(yt_ocean, xt_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8a05aac8-22a5-496d-8d75-ef5b746ace16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a05aac8-22a5-496d-8d75-ef5b746ace16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4e96a78-7ff9-4f76-b391-069f9582a3ed' class='xr-var-data-in' type='checkbox'><label for='data-a4e96a78-7ff9-4f76-b391-069f9582a3ed' 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_methods :</span></dt><dd>time: mean</dd><dt><span>coordinates :</span></dt><dd>geolon_t geolat_t</dd><dt><span>long_name :</span></dt><dd>Potential temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>degrees C</dd><dt><span>valid_range :</span></dt><dd>[-10.0, 500.0]</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" ...,\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(yu_ocean, xu_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fb9b87a0-0037-4c61-a16c-fca224454794' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb9b87a0-0037-4c61-a16c-fca224454794' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a391559-95d7-44b7-a3a0-65ab090bcc0f' class='xr-var-data-in' type='checkbox'><label for='data-3a391559-95d7-44b7-a3a0-65ab090bcc0f' 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_methods :</span></dt><dd>time: mean</dd><dt><span>coordinates :</span></dt><dd>geolon_c geolat_c</dd><dt><span>long_name :</span></dt><dd>i-current</dd><dt><span>standard_name :</span></dt><dd>sea_water_x_velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m/sec</dd><dt><span>valid_range :</span></dt><dd>[-10.0, 10.0]</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" ...,\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(yu_ocean, xu_ocean)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cdf9cdc4-4db1-4643-aac9-46feed086caa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cdf9cdc4-4db1-4643-aac9-46feed086caa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2af0e666-1116-4c4a-b4de-953f3143f492' class='xr-var-data-in' type='checkbox'><label for='data-2af0e666-1116-4c4a-b4de-953f3143f492' 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_methods :</span></dt><dd>time: mean</dd><dt><span>coordinates :</span></dt><dd>geolon_c geolat_c</dd><dt><span>long_name :</span></dt><dd>j-current</dd><dt><span>standard_name :</span></dt><dd>sea_water_y_velocity</dd><dt><span>time_avg_info :</span></dt><dd>average_T1,average_T2,average_DT</dd><dt><span>units :</span></dt><dd>m/sec</dd><dt><span>valid_range :</span></dt><dd>[-10.0, 10.0]</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" ...,\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-52ee1537-1266-4b60-8415-2e5c19e5e831' class='xr-section-summary-in' type='checkbox' checked><label for='section-52ee1537-1266-4b60-8415-2e5c19e5e831' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filename :</span></dt><dd>soda3.4.2_5dy_ocean_or_1993_01_04.nc</dd><dt><span>grid_tile :</span></dt><dd>1</dd><dt><span>grid_type :</span></dt><dd>mosaic</dd><dt><span>title :</span></dt><dd>MOM5_SODA_3.4.2</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (xt_ocean: 1440, xu_ocean: 1440, yt_ocean: 1070, yu_ocean: 1070)\n",
"Coordinates:\n",
" st_ocean float64 5.034\n",
" time object 1993-01-04 13:00:00\n",
" * xt_ocean (xt_ocean) float64 -279.9 -279.6 -279.4 ... 79.38 79.62 79.88\n",
" * xu_ocean (xu_ocean) float64 -279.8 -279.5 -279.2 -279.0 ... 79.5 79.75 80.0\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.74 89.84 89.95\n",
" * yu_ocean (yu_ocean) float64 -79.97 -79.86 -79.76 ... 89.79 89.89 90.0\n",
"Data variables:\n",
" temp (yt_ocean, xt_ocean) float32 nan nan nan nan ... nan nan nan nan\n",
" u (yu_ocean, xu_ocean) float32 nan nan nan nan ... nan nan nan nan\n",
" v (yu_ocean, xu_ocean) float32 nan nan nan nan ... nan nan nan nan\n",
"Attributes:\n",
" filename: soda3.4.2_5dy_ocean_or_1993_01_04.nc\n",
" grid_tile: 1\n",
" grid_type: mosaic\n",
" title: MOM5_SODA_3.4.2"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds = ds_full[['temp', 'u', 'v']].isel(time=0, st_ocean=0).load()\n",
"ds"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "39e5da65-31d1-4137-97ff-9d632190e62b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f0d32795310>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ds.temp.plot()"
]
},
{
"cell_type": "markdown",
"id": "057c8080-303a-437c-934b-42d97093678f",
"metadata": {},
"source": [
"We want to estimate `temp` at the spatial points of `tx_trans`."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "63faf1fe-049b-4214-9390-030ba13c4013",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xgcm.Grid>\n",
"X Axis (periodic, boundary=None):\n",
" * center xt_ocean --> right\n",
" * right xu_ocean --> center\n",
"Y Axis (not periodic, boundary=None):\n",
" * center yt_ocean --> right\n",
" * right yu_ocean --> center"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"grid = xgcm.Grid(\n",
" ds,\n",
" coords={'X': {'center': 'xt_ocean', 'right': 'xu_ocean'},\n",
" 'Y': {'center': 'yt_ocean', 'right': 'yu_ocean'}},\n",
" periodic=['X']\n",
")\n",
"grid"
]
},
{
"cell_type": "markdown",
"id": "aa8d4954-f7d8-4f7a-ab70-ddac3130ac28",
"metadata": {},
"source": [
"## The Problem\n",
"\n",
"Interpolating in the presence of a land mask grows the mask"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "1b8dcc5f-3841-4a49-ae59-42bc51023b6f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(970922)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tx_trans.notnull().sum().values"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "90d76ea0-e246-49e2-b18e-d550d0925bd5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(964568)"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"temp_at_tx = grid.interp(ds.temp, 'X', boundary='fill')\n",
"temp_at_tx.notnull().sum().values"
]
},
{
"cell_type": "markdown",
"id": "ce2f49d1-8bc3-41bd-bb36-63fd831ed3d3",
"metadata": {},
"source": [
"**We lost a few thousand points!***\n",
"This is because anything that touches a NaN becomes a NaN.\n",
"We can't solve this just by filling NaNs. We need to be smarter about handling \"interior boundaries\"."
]
},
{
"cell_type": "markdown",
"id": "ce27cfac-d145-4382-90b2-e2caa77e5f68",
"metadata": {},
"source": [
"## The Solution\n",
"\n",
"Land aware interpolation kernel.\n",
"This modifies the interpolation weights depending on whether there is land nearby."
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "33630d16-9c38-4a92-81b4-c7c220650f6e",
"metadata": {},
"outputs": [],
"source": [
"def interp_right_with_land(array, wet_mask):\n",
" # there are several different ways to implement this; this is one\n",
" \n",
" data = wet_mask * np.nan_to_num(array) # zeros the data on land\n",
" data_shift = np.roll(data, 1, -1)\n",
" \n",
" wet_fac = wet_mask + np.roll(wet_mask, 1, -1)\n",
" # wet_fac = 0: water on left AND right\n",
" # wet_fac = 1: water on left OR right\n",
" # wet_fac = 2: no land nearby\n",
" \n",
" # division by zero creates NaNs\n",
" out = 1 / wet_fac * (data + data_shift)\n",
" \n",
" return np.nan_to_num(out)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "a91fff1f-6dc9-40d0-9c4b-c868f1bad606",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-10-57d308efda75>:13: RuntimeWarning: divide by zero encountered in true_divide\n",
" out = 1 / wet_fac * (data + data_shift)\n",
"<ipython-input-10-57d308efda75>:13: RuntimeWarning: invalid value encountered in multiply\n",
" out = 1 / wet_fac * (data + data_shift)\n"
]
},
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (yt_ocean: 1070, xu_ocean: 1440)&gt;\n",
"array([[0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" ...,\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.]])\n",
"Coordinates:\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.74 89.84 89.95\n",
" * xu_ocean (xu_ocean) float64 -279.8 -279.5 -279.2 -279.0 ... 79.5 79.75 80.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>yt_ocean</span>: 1070</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-ca1d64ec-2fcb-49c8-904f-75d13a5b6c75' class='xr-array-in' type='checkbox' checked><label for='section-ca1d64ec-2fcb-49c8-904f-75d13a5b6c75' 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>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" ...,\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.]])</pre></div></div></li><li class='xr-section-item'><input id='section-4c59b83f-cdde-4c3a-8332-8930b7ab72b9' class='xr-section-summary-in' type='checkbox' checked><label for='section-4c59b83f-cdde-4c3a-8332-8930b7ab72b9' class='xr-section-summary' >Coordinates: <span>(2)</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'>yt_ocean</span></div><div class='xr-var-dims'>(yt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.02 -79.92 ... 89.84 89.95</div><input id='attrs-426be018-a565-4e91-b811-b63bde2cd26f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-426be018-a565-4e91-b811-b63bde2cd26f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9e86e8f-2d31-48b0-af97-f4d4d7d7613e' class='xr-var-data-in' type='checkbox'><label for='data-e9e86e8f-2d31-48b0-af97-f4d4d7d7613e' 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>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>tcell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-80.021015, -79.915416, -79.809818, ..., 89.736085, 89.841684,\n",
" 89.947282])</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-7adb1d0a-d197-475d-bacb-4d048c226d6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7adb1d0a-d197-475d-bacb-4d048c226d6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-001b5e11-b96f-48d9-837e-e6077c6842d5' class='xr-var-data-in' type='checkbox'><label for='data-001b5e11-b96f-48d9-837e-e6077c6842d5' 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>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd></dl></div><div class='xr-var-data'><pre>array([-279.75, -279.5 , -279.25, ..., 79.5 , 79.75, 80. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eef262b5-435b-4f7b-8780-52821bba1ec8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-eef262b5-435b-4f7b-8780-52821bba1ec8' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray (yt_ocean: 1070, xu_ocean: 1440)>\n",
"array([[0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" ...,\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.],\n",
" [0., 0., 0., ..., 0., 0., 0.]])\n",
"Coordinates:\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.74 89.84 89.95\n",
" * xu_ocean (xu_ocean) float64 -279.8 -279.5 -279.2 -279.0 ... 79.5 79.75 80.0"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wet_mask = ds.temp.notnull().astype(int)\n",
"\n",
"temp_at_tx_land = xr.DataArray(\n",
" interp_right_with_land(ds.temp.fillna(0.).data, wet_mask.data),\n",
" dims=temp_at_tx.dims,\n",
" coords=temp_at_tx.coords\n",
")\n",
"temp_at_tx_land"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "80f23e0b-e50d-4173-82ca-50e0480f632e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(1540800)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"temp_at_tx_land.notnull().sum().values"
]
},
{
"cell_type": "markdown",
"id": "223715a4-63d6-4a71-97d7-949b9abc57ed",
"metadata": {},
"source": [
"We now have no mask at all. I am not sure the best way to construct a new mask, particularly one that matches the mask of `tx_trans`.\n",
"\n",
"However, we can verify that our solution is the same as xgcm's `interp` method using the same mask."
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "93370246-993a-4b10-a899-1d9861a36332",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"temp_at_tx.equals(temp_at_tx.where(temp_at_tx.notnull()))"
]
},
{
"cell_type": "markdown",
"id": "f9d85c16-05fc-47ff-b0a7-f3524e0838cc",
"metadata": {},
"source": [
"## With Dask"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "2120755e-2390-4aeb-8daa-59a9ecacf27e",
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;temp&#x27; (st_ocean: 50, yt_ocean: 1070, xt_ocean: 1440)&gt;\n",
"dask.array&lt;astype, shape=(50, 1070, 1440), dtype=int8, chunksize=(50, 1070, 1440), chunktype=numpy.ndarray&gt;\n",
"Coordinates:\n",
" * st_ocean (st_ocean) float64 5.034 15.1 25.22 ... 5.185e+03 5.395e+03\n",
" time object 1993-01-04 13:00:00\n",
" * xt_ocean (xt_ocean) float64 -279.9 -279.6 -279.4 ... 79.38 79.62 79.88\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.74 89.84 89.95</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'temp'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>st_ocean</span>: 50</li><li><span class='xr-has-index'>yt_ocean</span>: 1070</li><li><span class='xr-has-index'>xt_ocean</span>: 1440</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5589507d-9180-4e59-951f-d6e9a01601b6' class='xr-array-in' type='checkbox' checked><label for='section-5589507d-9180-4e59-951f-d6e9a01601b6' 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=(50, 1070, 1440), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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" <tr><th> Bytes </th><td> 73.47 MiB </td> <td> 73.47 MiB </td></tr>\n",
" <tr><th> Shape </th><td> (50, 1070, 1440) </td> <td> (50, 1070, 1440) </td></tr>\n",
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" 2.474043e+03, 2.678757e+03, 2.884898e+03, 3.092117e+03, 3.300086e+03,\n",
" 3.508633e+03, 3.717567e+03, 3.926813e+03, 4.136251e+03, 4.345864e+03,\n",
" 4.555566e+03, 4.765369e+03, 4.975209e+03, 5.185111e+03, 5.395023e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1993-01-04 13:00:00</div><input id='attrs-2cce1840-915a-4487-983a-896e1d1c8338' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2cce1840-915a-4487-983a-896e1d1c8338' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ad20287-3c6d-4337-ace3-fe2c30cdc369' class='xr-var-data-in' type='checkbox'><label for='data-4ad20287-3c6d-4337-ace3-fe2c30cdc369' 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>bounds :</span></dt><dd>time_bounds</dd><dt><span>calendar_type :</span></dt><dd>JULIAN</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(cftime.DatetimeJulian(1993, 1, 4, 13, 0, 0, 0), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xt_ocean</span></div><div class='xr-var-dims'>(xt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-279.9 -279.6 ... 79.62 79.88</div><input id='attrs-ceb403f9-cbea-43a7-a86b-c2f033cbd805' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ceb403f9-cbea-43a7-a86b-c2f033cbd805' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba171c31-90ca-4e1e-a8b7-83c88fd032a4' class='xr-var-data-in' type='checkbox'><label for='data-ba171c31-90ca-4e1e-a8b7-83c88fd032a4' 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>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>tcell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd></dl></div><div class='xr-var-data'><pre>array([-279.875, -279.625, -279.375, ..., 79.375, 79.625, 79.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yt_ocean</span></div><div class='xr-var-dims'>(yt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.02 -79.92 ... 89.84 89.95</div><input id='attrs-6d57e4ee-379a-4579-9225-f76e7e678352' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d57e4ee-379a-4579-9225-f76e7e678352' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69358bee-cbcf-4f4c-8c96-458cbc1537bd' class='xr-var-data-in' type='checkbox'><label for='data-69358bee-cbcf-4f4c-8c96-458cbc1537bd' 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>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>tcell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-80.021015, -79.915416, -79.809818, ..., 89.736085, 89.841684,\n",
" 89.947282])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e3c5f624-dfb6-4a15-9bcb-e8abf18105d0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e3c5f624-dfb6-4a15-9bcb-e8abf18105d0' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'temp' (st_ocean: 50, yt_ocean: 1070, xt_ocean: 1440)>\n",
"dask.array<astype, shape=(50, 1070, 1440), dtype=int8, chunksize=(50, 1070, 1440), chunktype=numpy.ndarray>\n",
"Coordinates:\n",
" * st_ocean (st_ocean) float64 5.034 15.1 25.22 ... 5.185e+03 5.395e+03\n",
" time object 1993-01-04 13:00:00\n",
" * xt_ocean (xt_ocean) float64 -279.9 -279.6 -279.4 ... 79.38 79.62 79.88\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.74 89.84 89.95"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wet_mask_full = ds_full.temp[0].notnull().astype(np.int8)\n",
"wet_mask_full"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "f8605aa2-8a15-43d8-97c5-c1c4ce99a8de",
"metadata": {},
"outputs": [
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;temp&#x27; (time: 1970, st_ocean: 50, yt_ocean: 1070, xu_ocean: 1440)&gt;\n",
"dask.array&lt;transpose, shape=(1970, 50, 1070, 1440), dtype=float64, chunksize=(1, 50, 1070, 1440), chunktype=numpy.ndarray&gt;\n",
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" * time (time) object 1993-01-04 13:00:00 ... 2019-12-19 13:00:00\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.74 89.84 89.95\n",
" * xu_ocean (xu_ocean) float64 -279.8 -279.5 -279.2 -279.0 ... 79.5 79.75 80.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'temp'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1970</li><li><span class='xr-has-index'>st_ocean</span>: 50</li><li><span class='xr-has-index'>yt_ocean</span>: 1070</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-4ca670d5-3e9d-4ef0-9ffa-d42ea3e920e7' class='xr-array-in' type='checkbox' checked><label for='section-4ca670d5-3e9d-4ef0-9ffa-d42ea3e920e7' 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, 50, 1070, 1440), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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" <tbody>\n",
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" <line x1=\"112\" y1=\"0\" x2=\"112\" y2=\"25\" />\n",
" <line x1=\"116\" y1=\"0\" x2=\"116\" y2=\"25\" />\n",
" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
"\n",
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1970</text>\n",
" <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
"\n",
"\n",
" <!-- Horizontal lines -->\n",
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"\n",
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"\n",
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"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"190\" y1=\"0\" x2=\"277\" y2=\"0\" style=\"stroke-width:2\" />\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"\n",
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" <text x=\"315.597991\" y=\"50.471087\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,315.597991,50.471087)\">1070</text>\n",
" <text x=\"188.941127\" y=\"94.118792\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,188.941127,94.118792)\">50</text>\n",
"</svg>\n",
"</td>\n",
"</tr>\n",
"</table></div></div></li><li class='xr-section-item'><input id='section-df08fb45-8052-4bf5-9ccd-db87ae1c4001' class='xr-section-summary-in' type='checkbox' checked><label for='section-df08fb45-8052-4bf5-9ccd-db87ae1c4001' 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'>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'>5.034 15.1 ... 5.185e+03 5.395e+03</div><input id='attrs-00b3c0e7-4257-473a-b90a-2013a5e4cb19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00b3c0e7-4257-473a-b90a-2013a5e4cb19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4380d25-31e3-4f0d-8a99-d614026bde1b' class='xr-var-data-in' type='checkbox'><label for='data-a4380d25-31e3-4f0d-8a99-d614026bde1b' 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>cartesian_axis :</span></dt><dd>Z</dd><dt><span>edges :</span></dt><dd>st_edges_ocean</dd><dt><span>long_name :</span></dt><dd>tcell zstar depth</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([5.033550e+00, 1.510065e+01, 2.521935e+01, 3.535845e+01, 4.557635e+01,\n",
" 5.585325e+01, 6.626175e+01, 7.680285e+01, 8.757695e+01, 9.862325e+01,\n",
" 1.100962e+02, 1.221067e+02, 1.349086e+02, 1.487466e+02, 1.640538e+02,\n",
" 1.813125e+02, 2.012630e+02, 2.247773e+02, 2.530681e+02, 2.875508e+02,\n",
" 3.300078e+02, 3.823651e+02, 4.467263e+02, 5.249824e+02, 6.187031e+02,\n",
" 7.286921e+02, 8.549935e+02, 9.967153e+02, 1.152376e+03, 1.319997e+03,\n",
" 1.497562e+03, 1.683057e+03, 1.874788e+03, 2.071252e+03, 2.271323e+03,\n",
" 2.474043e+03, 2.678757e+03, 2.884898e+03, 3.092117e+03, 3.300086e+03,\n",
" 3.508633e+03, 3.717567e+03, 3.926813e+03, 4.136251e+03, 4.345864e+03,\n",
" 4.555566e+03, 4.765369e+03, 4.975209e+03, 5.185111e+03, 5.395023e+03])</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'>1993-01-04 13:00:00 ... 2019-12-...</div><input id='attrs-ae1c9025-0086-4382-a1e9-9f7d99b483e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae1c9025-0086-4382-a1e9-9f7d99b483e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a72bef86-3e51-482e-862c-47ae75db76d4' class='xr-var-data-in' type='checkbox'><label for='data-a72bef86-3e51-482e-862c-47ae75db76d4' 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>bounds :</span></dt><dd>time_bounds</dd><dt><span>calendar_type :</span></dt><dd>JULIAN</dd><dt><span>cartesian_axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeJulian(1993, 1, 4, 13, 0, 0, 0),\n",
" cftime.DatetimeJulian(1993, 1, 9, 13, 0, 0, 0),\n",
" cftime.DatetimeJulian(1993, 1, 14, 13, 0, 0, 0), ...,\n",
" cftime.DatetimeJulian(2019, 12, 9, 13, 0, 0, 0),\n",
" cftime.DatetimeJulian(2019, 12, 14, 13, 0, 0, 0),\n",
" cftime.DatetimeJulian(2019, 12, 19, 13, 0, 0, 0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yt_ocean</span></div><div class='xr-var-dims'>(yt_ocean)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-80.02 -79.92 ... 89.84 89.95</div><input id='attrs-fa4da44b-b968-4f92-972e-6218de94144a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa4da44b-b968-4f92-972e-6218de94144a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58d73b4a-68ee-4ec4-ae51-fb520ba491b8' class='xr-var-data-in' type='checkbox'><label for='data-58d73b4a-68ee-4ec4-ae51-fb520ba491b8' 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>cartesian_axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>tcell latitude</dd><dt><span>units :</span></dt><dd>degrees_N</dd></dl></div><div class='xr-var-data'><pre>array([-80.021015, -79.915416, -79.809818, ..., 89.736085, 89.841684,\n",
" 89.947282])</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-b93673ca-6e66-4cce-a2c9-0d3e04554da6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b93673ca-6e66-4cce-a2c9-0d3e04554da6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71099659-c9f7-43d2-8e24-f1f4ee1a8e8a' class='xr-var-data-in' type='checkbox'><label for='data-71099659-c9f7-43d2-8e24-f1f4ee1a8e8a' 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>cartesian_axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>ucell longitude</dd><dt><span>units :</span></dt><dd>degrees_E</dd></dl></div><div class='xr-var-data'><pre>array([-279.75, -279.5 , -279.25, ..., 79.5 , 79.75, 80. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3fcae9a5-9867-487c-a95a-3b9a4d521061' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3fcae9a5-9867-487c-a95a-3b9a4d521061' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'temp' (time: 1970, st_ocean: 50, yt_ocean: 1070, xu_ocean: 1440)>\n",
"dask.array<transpose, shape=(1970, 50, 1070, 1440), dtype=float64, chunksize=(1, 50, 1070, 1440), chunktype=numpy.ndarray>\n",
"Coordinates:\n",
" * st_ocean (st_ocean) float64 5.034 15.1 25.22 ... 5.185e+03 5.395e+03\n",
" * time (time) object 1993-01-04 13:00:00 ... 2019-12-19 13:00:00\n",
" * yt_ocean (yt_ocean) float64 -80.02 -79.92 -79.81 ... 89.74 89.84 89.95\n",
" * xu_ocean (xu_ocean) float64 -279.8 -279.5 -279.2 -279.0 ... 79.5 79.75 80.0"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"temp_at_tx_full = xr.apply_ufunc(\n",
" interp_right_with_land,\n",
" ds_full.temp,\n",
" wet_mask_full,\n",
" dask='parallelized',\n",
" input_core_dims=[['yt_ocean', 'xt_ocean'], ['yt_ocean', 'xt_ocean']],\n",
" output_core_dims=[['yt_ocean', 'xu_ocean']],\n",
" dask_gufunc_kwargs=dict(output_sizes={'xu_ocean': ds_full.dims['xu_ocean']}),\n",
" output_dtypes=[ds_full.temp.dtype],\n",
").assign_coords(xu_ocean=ds_full.xu_ocean)\n",
"\n",
"temp_at_tx_full"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "de1fe700-021b-45b5-9f04-d37c1859e6b6",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-10-57d308efda75>:13: RuntimeWarning: divide by zero encountered in true_divide\n",
" out = 1 / wet_fac * (data + data_shift)\n",
"<ipython-input-10-57d308efda75>:13: RuntimeWarning: invalid value encountered in multiply\n",
" out = 1 / wet_fac * (data + data_shift)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 2.26 s, sys: 1.32 s, total: 3.58 s\n",
"Wall time: 3.69 s\n"
]
}
],
"source": [
"%time temp_at_tx_full_c = temp_at_tx_full[0].compute()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "0ab77f7e-7d50-4e9b-a952-b8ef5c4bd281",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7f0d328219a0>"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"temp_at_tx_full_c[30].plot(vmin=-2, vmax=10)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "79a355d3-01a7-478e-9dd6-04c23ac017af",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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