LLC4320_geomap_pyinterp.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7260dff3-4829-4998-bd84-470c06e34f2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cartopy.crs\n",
    "import cartopy.mpl.ticker\n",
    "import intake\n",
    "import matplotlib.pyplot\n",
    "import numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "28e43ec1-975a-4642-ba2c-22934335f623",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6c8961a8-ffa2-41a3-bd14-70348e1e7a08",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !conda install pyinterp -c conda-forge -y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ab9b3479-d0da-4a5d-8d36-5801109a5a42",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyinterp\n",
    "mesh = pyinterp.RTree()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5e3928f1-e552-4663-b12d-967bfda0ee03",
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_url = \"https://raw.githubusercontent.com/pangeo-data/pangeo-datastore\" \\\n",
    "    \"/master/intake-catalogs/ocean/llc4320.yaml\"\n",
    "cat = intake.open_catalog(cat_url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "704c0fb3-3f1e-4f6f-9a6a-1eb6c4f5640a",
   "metadata": {},
   "outputs": [],
   "source": [
    "array = cat.LLC4320_grid.to_dask()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f9f6ebf1-594c-4c28-9247-619a6355e6a8",
   "metadata": {},
   "outputs": [
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       "Dimensions:  (face: 13, j: 4320, i: 4320, k_p1: 2, j_g: 4320, i_g: 4320,\n",
       "              time: 9030)\n",
       "Coordinates: (12/37)\n",
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       "    PHrefC   float32 ...\n",
       "    PHrefF   (k_p1) float32 dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;\n",
       "    SN       (face, j, i) float32 dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;\n",
       "    XC       (face, j, i) float32 dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;\n",
       "    ...       ...\n",
       "    k_u      int64 ...\n",
       "    rA       (face, j, i) float32 dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;\n",
       "    rAs      (face, j_g, i) float32 dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;\n",
       "    rAw      (face, j, i_g) float32 dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;\n",
       "    rAz      (face, j_g, i_g) float32 dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;\n",
       "  * time     (time) datetime64[ns] 2011-09-13 ... 2012-09-23T05:00:00\n",
       "Data variables:\n",
       "    *empty*\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Created by calling `open_mdsdataset(llc_method=&#x27;smallchunks...\n",
       "    source:       MITgcm\n",
       "    title:        netCDF wrapper of MITgcm MDS binary data</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-cd259547-6648-49c7-b73d-793874e12080' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cd259547-6648-49c7-b73d-793874e12080' 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'>face</span>: 13</li><li><span class='xr-has-index'>j</span>: 4320</li><li><span class='xr-has-index'>i</span>: 4320</li><li><span class='xr-has-index'>k_p1</span>: 2</li><li><span class='xr-has-index'>j_g</span>: 4320</li><li><span class='xr-has-index'>i_g</span>: 4320</li><li><span class='xr-has-index'>time</span>: 9030</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-312e2899-2753-4826-9745-b0f6e58640fe' class='xr-section-summary-in' type='checkbox'  ><label for='section-312e2899-2753-4826-9745-b0f6e58640fe' class='xr-section-summary' >Coordinates: <span>(37)</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>CS</span></div><div class='xr-var-dims'>(face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-623f4e78-ed29-4398-b408-a2bac1fe1a80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-623f4e78-ed29-4398-b408-a2bac1fe1a80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37e8f13e-283c-4a79-b812-bb4cb7a15ae6' class='xr-var-data-in' type='checkbox'><label for='data-37e8f13e-283c-4a79-b812-bb4cb7a15ae6' 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>coordinate :</span></dt><dd>YC XC</dd><dt><span>long_name :</span></dt><dd>AngleCS</dd><dt><span>standard_name :</span></dt><dd>Cos of grid orientation angle</dd><dt><span>units :</span></dt><dd> </dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 0.90 GiB </td>\n",
       "                        <td> 71.19 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (13, 4320, 4320) </td>\n",
       "                        <td> (1, 4320, 4320) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 14 Tasks </td>\n",
       "                        <td> 13 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Depth</span></div><div class='xr-var-dims'>(face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-8fd2e339-7eff-4405-9b03-478c5674a90e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fd2e339-7eff-4405-9b03-478c5674a90e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4576b4b3-784f-46b4-ab57-ba29f9853a67' class='xr-var-data-in' type='checkbox'><label for='data-4576b4b3-784f-46b4-ab57-ba29f9853a67' 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>coordinate :</span></dt><dd>XC YC</dd><dt><span>long_name :</span></dt><dd>ocean depth</dd><dt><span>standard_name :</span></dt><dd>ocean_depth</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 0.90 GiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Count </th>\n",
       "                        <td> 14 Tasks </td>\n",
       "                        <td> 13 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PHrefC</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1cb0f397-8219-4856-bb16-3fdd0bcb115c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cb0f397-8219-4856-bb16-3fdd0bcb115c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49d39245-c471-4d5d-80de-fc76017f7da6' class='xr-var-data-in' type='checkbox'><label for='data-49d39245-c471-4d5d-80de-fc76017f7da6' 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>Reference Hydrostatic Pressure</dd><dt><span>standard_name :</span></dt><dd>cell_reference_pressure</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><pre>array(15.4017, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PHrefF</span></div><div class='xr-var-dims'>(k_p1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-84599a2b-db78-412e-a8db-3693d742ad2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84599a2b-db78-412e-a8db-3693d742ad2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d587a19-dc13-4c9e-b61d-7d29b2206ab6' class='xr-var-data-in' type='checkbox'><label for='data-6d587a19-dc13-4c9e-b61d-7d29b2206ab6' 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>Reference Hydrostatic Pressure</dd><dt><span>standard_name :</span></dt><dd>cell_reference_pressure</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
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       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 8 B </td>\n",
       "                        <td> 8 B </td>\n",
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       "                    \n",
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       "                        <td> (2,) </td>\n",
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       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
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       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SN</span></div><div class='xr-var-dims'>(face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-3947c6c8-2504-44ee-8167-973e265d7c82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3947c6c8-2504-44ee-8167-973e265d7c82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d62cd3f-c722-4a11-8376-47a80fc77f03' class='xr-var-data-in' type='checkbox'><label for='data-8d62cd3f-c722-4a11-8376-47a80fc77f03' 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>coordinate :</span></dt><dd>YC XC</dd><dt><span>long_name :</span></dt><dd>AngleSN</dd><dt><span>standard_name :</span></dt><dd>Sin of grid orientation angle</dd><dt><span>units :</span></dt><dd> </dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <th> Count </th>\n",
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       "                    <th> Type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>YG</span></div><div class='xr-var-dims'>(face, j_g, i_g)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-995c6ab1-080c-43fa-a12f-d426e48095f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-995c6ab1-080c-43fa-a12f-d426e48095f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d338975-c0f4-416e-982f-3c5ef3d2e54b' class='xr-var-data-in' type='checkbox'><label for='data-9d338975-c0f4-416e-982f-3c5ef3d2e54b' 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>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude_at_f_location</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> 13 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ea6f8189-e726-472c-80e5-1abc28e3dca7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea6f8189-e726-472c-80e5-1abc28e3dca7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c8ce0f0-c49a-4e87-99e0-b51bb12351d8' class='xr-var-data-in' type='checkbox'><label for='data-8c8ce0f0-c49a-4e87-99e0-b51bb12351d8' 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>vertical coordinate of cell center</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(-1.57, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Zl</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3ff3c934-9a38-4268-a222-6855e330e987' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ff3c934-9a38-4268-a222-6855e330e987' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f6ac935-6bc1-48e5-98a1-b067cc9d24fa' class='xr-var-data-in' type='checkbox'><label for='data-9f6ac935-6bc1-48e5-98a1-b067cc9d24fa' 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>vertical coordinate of upper cell interface</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth_at_upper_w_location</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(-1., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Zp1</span></div><div class='xr-var-dims'>(k_p1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-d85d68b7-0d3e-429f-b1c4-fe96419d2266' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d85d68b7-0d3e-429f-b1c4-fe96419d2266' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2a4eddd-3a8b-4c14-9f45-df63dc38e757' class='xr-var-data-in' type='checkbox'><label for='data-b2a4eddd-3a8b-4c14-9f45-df63dc38e757' 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>vertical coordinate of cell interface</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth_at_w_location</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 8 B </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (2,) </td>\n",
       "                        <td> (2,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Zu</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5a2cde2d-ccdd-40a1-ba1b-aa88ae0a7445' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a2cde2d-ccdd-40a1-ba1b-aa88ae0a7445' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e27e053-6b19-4408-923a-0a69d7e32444' class='xr-var-data-in' type='checkbox'><label for='data-9e27e053-6b19-4408-923a-0a69d7e32444' 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>vertical coordinate of lower cell interface</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth_at_lower_w_location</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(-2.14, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drC</span></div><div class='xr-var-dims'>(k_p1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2,), meta=np.ndarray&gt;</div><input id='attrs-58c3d56e-679f-47f8-ac60-2d1062b22119' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58c3d56e-679f-47f8-ac60-2d1062b22119' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06d03e57-cb65-44ff-b923-4eb2aac832b1' class='xr-var-data-in' type='checkbox'><label for='data-06d03e57-cb65-44ff-b923-4eb2aac832b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell z size</dd><dt><span>standard_name :</span></dt><dd>cell_z_size_at_w_location</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
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       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 8 B </td>\n",
       "                        <td> 8 B </td>\n",
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       "                        <td> (2,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
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       "                        <td> 1 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drF</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8e86024f-59a0-410c-9317-de5e0deaae70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e86024f-59a0-410c-9317-de5e0deaae70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22defcee-79bf-4a1a-9cf9-5f2ce43b3d6f' class='xr-var-data-in' type='checkbox'><label for='data-22defcee-79bf-4a1a-9cf9-5f2ce43b3d6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell z size</dd><dt><span>standard_name :</span></dt><dd>cell_z_size</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(1.14, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxC</span></div><div class='xr-var-dims'>(face, j, i_g)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-c7801077-7a57-42c4-a34d-96fe7ba2d3d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7801077-7a57-42c4-a34d-96fe7ba2d3d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b06ab05-07d1-41c4-97f5-d8f715c7a50d' class='xr-var-data-in' type='checkbox'><label for='data-2b06ab05-07d1-41c4-97f5-d8f715c7a50d' 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>coordinate :</span></dt><dd>YC XG</dd><dt><span>long_name :</span></dt><dd>cell x size</dd><dt><span>standard_name :</span></dt><dd>cell_x_size_at_u_location</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 0.90 GiB </td>\n",
       "                        <td> 71.19 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (13, 4320, 4320) </td>\n",
       "                        <td> (1, 4320, 4320) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 14 Tasks </td>\n",
       "                        <td> 13 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
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       "                <thead>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 0.90 GiB </td>\n",
       "                        <td> 71.19 MiB </td>\n",
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       "                        <th> Shape </th>\n",
       "                        <td> (13, 4320, 4320) </td>\n",
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       "                        <td> 14 Tasks </td>\n",
       "                        <td> 13 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyC</span></div><div class='xr-var-dims'>(face, j_g, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-7bb4f67c-4739-40bc-b433-4cc33c0ca82c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bb4f67c-4739-40bc-b433-4cc33c0ca82c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47f56a30-f47d-4189-9db5-108535cc1fd0' class='xr-var-data-in' type='checkbox'><label for='data-47f56a30-f47d-4189-9db5-108535cc1fd0' 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>coordinate :</span></dt><dd>YG XC</dd><dt><span>long_name :</span></dt><dd>cell y size</dd><dt><span>standard_name :</span></dt><dd>cell_y_size_at_v_location</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 0.90 GiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (13, 4320, 4320) </td>\n",
       "                        <td> (1, 4320, 4320) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyG</span></div><div class='xr-var-dims'>(face, j, i_g)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-7712503b-9d39-4b80-af3d-dc7e79cfac29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7712503b-9d39-4b80-af3d-dc7e79cfac29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2103ecd-33be-4a47-92cb-25d0737bc55c' class='xr-var-data-in' type='checkbox'><label for='data-d2103ecd-33be-4a47-92cb-25d0737bc55c' 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>coordinate :</span></dt><dd>YC XG</dd><dt><span>long_name :</span></dt><dd>cell y size</dd><dt><span>standard_name :</span></dt><dd>cell_y_size_at_u_location</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Count </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>face</span></div><div class='xr-var-dims'>(face)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-bd4b1cd3-07d0-4473-a980-f8729ca2bdfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd4b1cd3-07d0-4473-a980-f8729ca2bdfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a63e385-2d88-4709-b5c3-e8d0609a620c' class='xr-var-data-in' type='checkbox'><label for='data-5a63e385-2d88-4709-b5c3-e8d0609a620c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>face_index</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hFacC</span></div><div class='xr-var-dims'>(face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-4102dc5e-7d01-44e6-8255-5cbf76056721' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4102dc5e-7d01-44e6-8255-5cbf76056721' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07105a73-ee8d-4f80-b5d8-30a5f6953681' class='xr-var-data-in' type='checkbox'><label for='data-07105a73-ee8d-4f80-b5d8-30a5f6953681' 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>vertical fraction of open cell</dd><dt><span>standard_name :</span></dt><dd>cell_vertical_fraction</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <td> (1, 4320, 4320) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 14 Tasks </td>\n",
       "                        <td> 13 Chunks </td>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hFacS</span></div><div class='xr-var-dims'>(face, j_g, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-d903b8db-8f13-436a-92e5-46f00b683107' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d903b8db-8f13-436a-92e5-46f00b683107' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01d50f2a-c375-4135-bd94-495ef22be4d0' class='xr-var-data-in' type='checkbox'><label for='data-01d50f2a-c375-4135-bd94-495ef22be4d0' 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>vertical fraction of open cell</dd><dt><span>standard_name :</span></dt><dd>cell_vertical_fraction_at_v_location</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                    <tr>\n",
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       "                        <th> Count </th>\n",
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       "                        <td> 13 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>i</span></div><div class='xr-var-dims'>(i)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 4316 4317 4318 4319</div><input id='attrs-eb53188c-fd5c-4aea-8272-229083c8055f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb53188c-fd5c-4aea-8272-229083c8055f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35f3b923-8de3-432a-bbf2-cf12f6d6c70a' class='xr-var-data-in' type='checkbox'><label for='data-35f3b923-8de3-432a-bbf2-cf12f6d6c70a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>x_grid_index</dd><dt><span>swap_dim :</span></dt><dd>XC</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 4317, 4318, 4319])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>i_g</span></div><div class='xr-var-dims'>(i_g)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 4316 4317 4318 4319</div><input id='attrs-dea938fb-31d3-415e-b50f-a0a639870b86' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dea938fb-31d3-415e-b50f-a0a639870b86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39a7049f-c51f-45c3-8192-7b2882921249' class='xr-var-data-in' type='checkbox'><label for='data-39a7049f-c51f-45c3-8192-7b2882921249' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd><dt><span>long_name :</span></dt><dd>x-dimension of the u grid</dd><dt><span>standard_name :</span></dt><dd>x_grid_index_at_u_location</dd><dt><span>swap_dim :</span></dt><dd>XG</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 4317, 4318, 4319])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iter</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(9030,), meta=np.ndarray&gt;</div><input id='attrs-465d98b2-544e-4521-bc0d-4631f7bee238' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-465d98b2-544e-4521-bc0d-4631f7bee238' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-228a264a-b916-4988-a9f7-40509021c3fb' class='xr-var-data-in' type='checkbox'><label for='data-228a264a-b916-4988-a9f7-40509021c3fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 70.55 kiB </td>\n",
       "                        <td> 70.55 kiB </td>\n",
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       "                        <td> (9030,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
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       "                        <td> 1 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> int64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>j</span></div><div class='xr-var-dims'>(j)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 4316 4317 4318 4319</div><input id='attrs-e90694ed-00af-4cff-a38c-13e63524f316' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e90694ed-00af-4cff-a38c-13e63524f316' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e215855f-d6e7-4683-90f4-53dcd2bd1baf' class='xr-var-data-in' type='checkbox'><label for='data-e215855f-d6e7-4683-90f4-53dcd2bd1baf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>y_grid_index</dd><dt><span>swap_dim :</span></dt><dd>YC</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 4317, 4318, 4319])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>j_g</span></div><div class='xr-var-dims'>(j_g)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 4316 4317 4318 4319</div><input id='attrs-9fa8758e-97bd-42f6-9c40-d0c2355d65f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fa8758e-97bd-42f6-9c40-d0c2355d65f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dba1c58-714d-4377-8c4e-54357e6963dd' class='xr-var-data-in' type='checkbox'><label for='data-3dba1c58-714d-4377-8c4e-54357e6963dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd><dt><span>long_name :</span></dt><dd>y-dimension of the v grid</dd><dt><span>standard_name :</span></dt><dd>y_grid_index_at_v_location</dd><dt><span>swap_dim :</span></dt><dd>YG</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 4317, 4318, 4319])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>k</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8185b044-632c-4d94-9f2c-a7b016e476ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8185b044-632c-4d94-9f2c-a7b016e476ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0f3617e-d586-42ed-ab32-7284ae8e1e6b' class='xr-var-data-in' type='checkbox'><label for='data-d0f3617e-d586-42ed-ab32-7284ae8e1e6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>z-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>z_grid_index</dd><dt><span>swap_dim :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>k_l</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-183e84eb-d26a-4433-ac3f-5c1f58aca1b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-183e84eb-d26a-4433-ac3f-5c1f58aca1b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a51e1d6a-cb7c-4331-b152-01b2c9b25f14' class='xr-var-data-in' type='checkbox'><label for='data-a51e1d6a-cb7c-4331-b152-01b2c9b25f14' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd><dt><span>long_name :</span></dt><dd>z-dimension of the w grid</dd><dt><span>standard_name :</span></dt><dd>z_grid_index_at_upper_w_location</dd><dt><span>swap_dim :</span></dt><dd>Zl</dd></dl></div><div class='xr-var-data'><pre>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>k_p1</span></div><div class='xr-var-dims'>(k_p1)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1</div><input id='attrs-9e981c16-1688-4080-963a-4617f57d1469' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e981c16-1688-4080-963a-4617f57d1469' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d21817a-068f-4603-b15f-b45f70bd4b3c' class='xr-var-data-in' type='checkbox'><label for='data-5d21817a-068f-4603-b15f-b45f70bd4b3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>[-0.5, 0.5]</dd><dt><span>long_name :</span></dt><dd>z-dimension of the w grid</dd><dt><span>standard_name :</span></dt><dd>z_grid_index_at_w_location</dd><dt><span>swap_dim :</span></dt><dd>Zp1</dd></dl></div><div class='xr-var-data'><pre>array([0, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>k_u</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8584ace0-54e8-4b64-9dd8-797d8036e0a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8584ace0-54e8-4b64-9dd8-797d8036e0a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6f8d1e9-d9e0-485e-94ae-eb5470be75de' class='xr-var-data-in' type='checkbox'><label for='data-b6f8d1e9-d9e0-485e-94ae-eb5470be75de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>0.5</dd><dt><span>long_name :</span></dt><dd>z-dimension of the w grid</dd><dt><span>standard_name :</span></dt><dd>z_grid_index_at_lower_w_location</dd><dt><span>swap_dim :</span></dt><dd>Zu</dd></dl></div><div class='xr-var-data'><pre>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rA</span></div><div 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       "</table></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'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2011-09-13 ... 2012-09-23T05:00:00</div><input id='attrs-0b703778-a203-4897-ae1a-d25f17cbdfbc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b703778-a203-4897-ae1a-d25f17cbdfbc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c3bf423-b676-485e-a576-74bbd7e29ab4' class='xr-var-data-in' type='checkbox'><label for='data-5c3bf423-b676-485e-a576-74bbd7e29ab4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2011-09-13T00:00:00.000000000&#x27;, &#x27;2011-09-13T01:00:00.000000000&#x27;,\n",
       "       &#x27;2011-09-13T02:00:00.000000000&#x27;, ..., &#x27;2012-09-23T03:00:00.000000000&#x27;,\n",
       "       &#x27;2012-09-23T04:00:00.000000000&#x27;, &#x27;2012-09-23T05:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9ba6890c-430c-4bec-851d-c0bfe1d96390' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9ba6890c-430c-4bec-851d-c0bfe1d96390' class='xr-section-summary'  title='Expand/collapse section'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-66a230a4-6ef9-4748-b6b1-c18fbf176503' class='xr-section-summary-in' type='checkbox'  checked><label for='section-66a230a4-6ef9-4748-b6b1-c18fbf176503' 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>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Created by calling `open_mdsdataset(llc_method=&#x27;smallchunks&#x27;, nz=None, ny=None, nx=None, default_dtype=dtype(&#x27;&gt;f4&#x27;), ignore_unknown_vars=True, chunks=None, endian=&#x27;&gt;&#x27;, swap_dims=False, grid_vars_to_coords=True, geometry=&#x27;llc&#x27;, calendar=&#x27;gregorian&#x27;, ref_date=None, delta_t=1, read_grid=True, prefix=None, iters=487152, grid_dir=&#x27;/data/scratch/rpa/LLC/llc_4320/run&#x27;, data_dir=&#x27;/data/scratch/rpa/LLC/llc_4320/run&#x27;)`</dd><dt><span>source :</span></dt><dd>MITgcm</dd><dt><span>title :</span></dt><dd>netCDF wrapper of MITgcm MDS binary data</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:  (face: 13, j: 4320, i: 4320, k_p1: 2, j_g: 4320, i_g: 4320,\n",
       "              time: 9030)\n",
       "Coordinates: (12/37)\n",
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       "    Depth    (face, j, i) float32 dask.array<chunksize=(1, 4320, 4320), meta=np.ndarray>\n",
       "    PHrefC   float32 ...\n",
       "    PHrefF   (k_p1) float32 dask.array<chunksize=(2,), meta=np.ndarray>\n",
       "    SN       (face, j, i) float32 dask.array<chunksize=(1, 4320, 4320), meta=np.ndarray>\n",
       "    XC       (face, j, i) float32 dask.array<chunksize=(1, 4320, 4320), meta=np.ndarray>\n",
       "    ...       ...\n",
       "    k_u      int64 ...\n",
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       "    rAs      (face, j_g, i) float32 dask.array<chunksize=(1, 4320, 4320), meta=np.ndarray>\n",
       "    rAw      (face, j, i_g) float32 dask.array<chunksize=(1, 4320, 4320), meta=np.ndarray>\n",
       "    rAz      (face, j_g, i_g) float32 dask.array<chunksize=(1, 4320, 4320), meta=np.ndarray>\n",
       "  * time     (time) datetime64[ns] 2011-09-13 ... 2012-09-23T05:00:00\n",
       "Data variables:\n",
       "    *empty*\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Created by calling `open_mdsdataset(llc_method='smallchunks...\n",
       "    source:       MITgcm\n",
       "    title:        netCDF wrapper of MITgcm MDS binary data"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
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  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b5ac4484-ea22-4982-87c9-4a565c58bc7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "indices = slice(0, None, 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f3806aed-c9bd-4d8d-99d8-e2f382aa6953",
   "metadata": {},
   "outputs": [],
   "source": [
    "lons = array[\"XC\"].isel(i=indices, j=indices)\n",
    "lats = array[\"YC\"].isel(i=indices, j=indices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "6692268d-1063-4cf8-8b01-f89b60dbe82e",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;XC&#x27; (face: 13, j: 540, i: 540)&gt;\n",
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       "    PHrefC   float32 ...\n",
       "    SN       (face, j, i) float32 dask.array&lt;chunksize=(1, 540, 540), meta=np.ndarray&gt;\n",
       "    XC       (face, j, i) float32 dask.array&lt;chunksize=(1, 540, 540), meta=np.ndarray&gt;\n",
       "    YC       (face, j, i) float32 dask.array&lt;chunksize=(1, 540, 540), meta=np.ndarray&gt;\n",
       "    ...       ...\n",
       "  * i        (i) int64 0 8 16 24 32 40 48 ... 4264 4272 4280 4288 4296 4304 4312\n",
       "  * j        (j) int64 0 8 16 24 32 40 48 ... 4264 4272 4280 4288 4296 4304 4312\n",
       "    k        int64 ...\n",
       "    k_l      int64 ...\n",
       "    k_u      int64 ...\n",
       "    rA       (face, j, i) float32 dask.array&lt;chunksize=(1, 540, 540), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    coordinate:     YC XC\n",
       "    long_name:      longitude\n",
       "    standard_name:  longitude\n",
       "    units:          degrees_east</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'XC'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>face</span>: 13</li><li><span class='xr-has-index'>j</span>: 540</li><li><span class='xr-has-index'>i</span>: 540</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-acd8c2af-f76f-420c-b594-0b6423e08f64' class='xr-array-in' type='checkbox' checked><label for='section-acd8c2af-f76f-420c-b594-0b6423e08f64' 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, 540, 540), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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       "                <tbody>\n",
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       "                        <td> 14.46 MiB </td>\n",
       "                        <td> 1.11 MiB </td>\n",
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       "                    <th> Type </th>\n",
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       "                        <th> Count </th>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PHrefC</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dd5961d5-a8c3-4611-90bb-c7b6c282aaba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd5961d5-a8c3-4611-90bb-c7b6c282aaba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0ee4b49-dc80-4e8a-aa4f-87cf807dfc6a' class='xr-var-data-in' type='checkbox'><label for='data-a0ee4b49-dc80-4e8a-aa4f-87cf807dfc6a' 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>Reference Hydrostatic Pressure</dd><dt><span>standard_name :</span></dt><dd>cell_reference_pressure</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><pre>array(15.4017, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SN</span></div><div class='xr-var-dims'>(face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 540, 540), meta=np.ndarray&gt;</div><input id='attrs-eb627926-f4b6-41fa-89fc-acb8a14d8448' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb627926-f4b6-41fa-89fc-acb8a14d8448' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62ca779d-5116-45c0-8a5a-b81c1a1ce657' class='xr-var-data-in' type='checkbox'><label for='data-62ca779d-5116-45c0-8a5a-b81c1a1ce657' 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>coordinate :</span></dt><dd>YC XC</dd><dt><span>long_name :</span></dt><dd>AngleSN</dd><dt><span>standard_name :</span></dt><dd>Sin of grid orientation angle</dd><dt><span>units :</span></dt><dd> </dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 14.46 MiB </td>\n",
       "                        <td> 1.11 MiB </td>\n",
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       "                        <td> (1, 540, 540) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
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       "                        <td> 13 Chunks </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XC</span></div><div class='xr-var-dims'>(face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 540, 540), meta=np.ndarray&gt;</div><input id='attrs-287eddd9-ffa0-4855-9696-5816cc740764' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-287eddd9-ffa0-4855-9696-5816cc740764' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63bc75a4-4492-44c5-b368-3b2b7b85de82' class='xr-var-data-in' type='checkbox'><label for='data-63bc75a4-4492-44c5-b368-3b2b7b85de82' 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>coordinate :</span></dt><dd>YC XC</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 14.46 MiB </td>\n",
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       "                    <tr>\n",
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       "                        <td> (1, 540, 540) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 27 Tasks </td>\n",
       "                        <td> 13 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>YC</span></div><div class='xr-var-dims'>(face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 540, 540), meta=np.ndarray&gt;</div><input id='attrs-dbacda89-d9fa-4a1a-be90-2045e39f6b94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbacda89-d9fa-4a1a-be90-2045e39f6b94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a59c9f03-4e5d-4857-a717-b635962f6835' class='xr-var-data-in' type='checkbox'><label for='data-a59c9f03-4e5d-4857-a717-b635962f6835' 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>coordinate :</span></dt><dd>YC XC</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                        <td> 14.46 MiB </td>\n",
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       "                        <th> Count </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a66b4cbe-d91c-4696-aee9-1d0dd1231cd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a66b4cbe-d91c-4696-aee9-1d0dd1231cd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa1c097e-81ab-42d7-994e-76434a57cfed' class='xr-var-data-in' type='checkbox'><label for='data-fa1c097e-81ab-42d7-994e-76434a57cfed' 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>vertical coordinate of cell center</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(-1.57, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Zl</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-732f443f-3f25-453f-8df7-78b64605ba16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-732f443f-3f25-453f-8df7-78b64605ba16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e01a238c-26b1-441d-8b79-e6c24e97383d' class='xr-var-data-in' type='checkbox'><label for='data-e01a238c-26b1-441d-8b79-e6c24e97383d' 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>vertical coordinate of upper cell interface</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth_at_upper_w_location</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(-1., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Zu</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-28b58893-1596-4e46-b99a-2f6e9827ba9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28b58893-1596-4e46-b99a-2f6e9827ba9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6b64aae-2c9d-440b-a3d3-3262e01628d7' class='xr-var-data-in' type='checkbox'><label for='data-a6b64aae-2c9d-440b-a3d3-3262e01628d7' 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>vertical coordinate of lower cell interface</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth_at_lower_w_location</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(-2.14, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drF</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-06186e34-c941-45bf-aa1e-df93e7cea1a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06186e34-c941-45bf-aa1e-df93e7cea1a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-664c8ab3-25b0-4de9-8f5c-78cc0bab2fcb' class='xr-var-data-in' type='checkbox'><label for='data-664c8ab3-25b0-4de9-8f5c-78cc0bab2fcb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell z size</dd><dt><span>standard_name :</span></dt><dd>cell_z_size</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(1.14, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>face</span></div><div class='xr-var-dims'>(face)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-459456c3-56c8-4f45-81bb-3d4aa362661e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-459456c3-56c8-4f45-81bb-3d4aa362661e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec06c6f6-760a-4df5-afef-5341134a692e' class='xr-var-data-in' type='checkbox'><label for='data-ec06c6f6-760a-4df5-afef-5341134a692e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>face_index</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hFacC</span></div><div class='xr-var-dims'>(face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 540, 540), meta=np.ndarray&gt;</div><input id='attrs-0ef449cd-e0b6-4e1f-b1e2-49b5312c34fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ef449cd-e0b6-4e1f-b1e2-49b5312c34fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6db63cc-5855-420d-8d7e-deeee109f79d' class='xr-var-data-in' type='checkbox'><label for='data-b6db63cc-5855-420d-8d7e-deeee109f79d' 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>vertical fraction of open cell</dd><dt><span>standard_name :</span></dt><dd>cell_vertical_fraction</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 14.46 MiB </td>\n",
       "                        <td> 1.11 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (13, 540, 540) </td>\n",
       "                        <td> (1, 540, 540) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 27 Tasks </td>\n",
       "                        <td> 13 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"197\" height=\"187\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>i</span></div><div class='xr-var-dims'>(i)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 8 16 24 ... 4288 4296 4304 4312</div><input id='attrs-7e1c8021-71c4-4359-b730-b24df613e7fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e1c8021-71c4-4359-b730-b24df613e7fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88abd15e-f0d0-485b-b515-ba6708937241' class='xr-var-data-in' type='checkbox'><label for='data-88abd15e-f0d0-485b-b515-ba6708937241' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>x_grid_index</dd><dt><span>swap_dim :</span></dt><dd>XC</dd></dl></div><div class='xr-var-data'><pre>array([   0,    8,   16, ..., 4296, 4304, 4312])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>j</span></div><div class='xr-var-dims'>(j)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 8 16 24 ... 4288 4296 4304 4312</div><input id='attrs-0aaacde8-975f-493b-b4f0-38d013ee7fc7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0aaacde8-975f-493b-b4f0-38d013ee7fc7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c86a0293-4d12-435d-a8d8-f691401261a6' class='xr-var-data-in' type='checkbox'><label for='data-c86a0293-4d12-435d-a8d8-f691401261a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>y_grid_index</dd><dt><span>swap_dim :</span></dt><dd>YC</dd></dl></div><div class='xr-var-data'><pre>array([   0,    8,   16, ..., 4296, 4304, 4312])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>k</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0593975e-a0fa-4d51-a819-925af416dfc6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0593975e-a0fa-4d51-a819-925af416dfc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-202542ca-f1d8-4f37-ac40-6b27c970fdb0' class='xr-var-data-in' type='checkbox'><label for='data-202542ca-f1d8-4f37-ac40-6b27c970fdb0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>z-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>z_grid_index</dd><dt><span>swap_dim :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>k_l</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-16379df1-2622-4fe8-958a-75e40d8b4668' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16379df1-2622-4fe8-958a-75e40d8b4668' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc92fd52-c442-4f2d-9290-3ac51c2fc4f0' class='xr-var-data-in' type='checkbox'><label for='data-bc92fd52-c442-4f2d-9290-3ac51c2fc4f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd><dt><span>long_name :</span></dt><dd>z-dimension of the w grid</dd><dt><span>standard_name :</span></dt><dd>z_grid_index_at_upper_w_location</dd><dt><span>swap_dim :</span></dt><dd>Zl</dd></dl></div><div class='xr-var-data'><pre>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>k_u</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e7e22258-785e-439e-947e-20b37c232ec1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7e22258-785e-439e-947e-20b37c232ec1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a978f75e-0dab-4fe5-af3e-4b46b4acace7' class='xr-var-data-in' type='checkbox'><label for='data-a978f75e-0dab-4fe5-af3e-4b46b4acace7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>0.5</dd><dt><span>long_name :</span></dt><dd>z-dimension of the w grid</dd><dt><span>standard_name :</span></dt><dd>z_grid_index_at_lower_w_location</dd><dt><span>swap_dim :</span></dt><dd>Zu</dd></dl></div><div class='xr-var-data'><pre>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rA</span></div><div class='xr-var-dims'>(face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 540, 540), meta=np.ndarray&gt;</div><input id='attrs-7a97f28b-5a42-4902-9acb-90f614f3847b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a97f28b-5a42-4902-9acb-90f614f3847b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7796fc33-111f-49ac-a457-d993eb26aa38' class='xr-var-data-in' type='checkbox'><label for='data-7796fc33-111f-49ac-a457-d993eb26aa38' 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>coordinate :</span></dt><dd>YC XC</dd><dt><span>long_name :</span></dt><dd>cell area</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 14.46 MiB </td>\n",
       "                        <td> 1.11 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (13, 540, 540) </td>\n",
       "                        <td> (1, 540, 540) </td>\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 9030, face: 13, j: 4320, i: 4320)\n",
       "Coordinates:\n",
       "  * face     (face) int64 0 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "  * i        (i) int64 0 1 2 3 4 5 6 7 ... 4313 4314 4315 4316 4317 4318 4319\n",
       "  * j        (j) int64 0 1 2 3 4 5 6 7 ... 4313 4314 4315 4316 4317 4318 4319\n",
       "  * time     (time) datetime64[ns] 2011-09-13 ... 2012-09-23T05:00:00\n",
       "Data variables:\n",
       "    Eta      (time, face, j, i) float32 dask.array&lt;chunksize=(1, 1, 4320, 4320), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Created by calling `open_mdsdataset(llc_method=&#x27;smallchunks...\n",
       "    source:       MITgcm\n",
       "    title:        netCDF wrapper of MITgcm MDS binary data</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ccf6aeb4-5919-429c-b767-c29ba4932e3e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ccf6aeb4-5919-429c-b767-c29ba4932e3e' 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'>time</span>: 9030</li><li><span class='xr-has-index'>face</span>: 13</li><li><span class='xr-has-index'>j</span>: 4320</li><li><span class='xr-has-index'>i</span>: 4320</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8c12ef0a-8e47-45c4-bd83-12e3045c9861' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8c12ef0a-8e47-45c4-bd83-12e3045c9861' 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'>face</span></div><div class='xr-var-dims'>(face)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-75fddbea-2c19-45d4-9787-c4397a4e3933' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75fddbea-2c19-45d4-9787-c4397a4e3933' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97b7ae46-0a8a-48a5-954f-60f7ef479237' class='xr-var-data-in' type='checkbox'><label for='data-97b7ae46-0a8a-48a5-954f-60f7ef479237' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>face_index</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>i</span></div><div class='xr-var-dims'>(i)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 4316 4317 4318 4319</div><input id='attrs-81840940-ca74-4c89-83af-28201f1be875' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81840940-ca74-4c89-83af-28201f1be875' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3edd9421-40fb-4a16-a220-272f410c1954' class='xr-var-data-in' type='checkbox'><label for='data-3edd9421-40fb-4a16-a220-272f410c1954' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>x_grid_index</dd><dt><span>swap_dim :</span></dt><dd>XC</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 4317, 4318, 4319])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>j</span></div><div class='xr-var-dims'>(j)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 4316 4317 4318 4319</div><input id='attrs-ab7c0cca-fa0a-4449-b9e8-234b93f41883' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab7c0cca-fa0a-4449-b9e8-234b93f41883' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfc9a074-1057-4f91-8879-d2879fd295d9' class='xr-var-data-in' type='checkbox'><label for='data-cfc9a074-1057-4f91-8879-d2879fd295d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>y_grid_index</dd><dt><span>swap_dim :</span></dt><dd>YC</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 4317, 4318, 4319])</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'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2011-09-13 ... 2012-09-23T05:00:00</div><input id='attrs-c11b7a05-7ebb-4bf2-9158-1a42499e67df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c11b7a05-7ebb-4bf2-9158-1a42499e67df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-056890d2-b143-451b-bb69-e5440fb7f6ae' class='xr-var-data-in' type='checkbox'><label for='data-056890d2-b143-451b-bb69-e5440fb7f6ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2011-09-13T00:00:00.000000000&#x27;, &#x27;2011-09-13T01:00:00.000000000&#x27;,\n",
       "       &#x27;2011-09-13T02:00:00.000000000&#x27;, ..., &#x27;2012-09-23T03:00:00.000000000&#x27;,\n",
       "       &#x27;2012-09-23T04:00:00.000000000&#x27;, &#x27;2012-09-23T05:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2b019e52-b761-45eb-9ac3-f3096c2c41c4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2b019e52-b761-45eb-9ac3-f3096c2c41c4' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Eta</span></div><div class='xr-var-dims'>(time, face, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 4320, 4320), meta=np.ndarray&gt;</div><input id='attrs-84f09c01-8562-4667-9abd-55111f629a44' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-84f09c01-8562-4667-9abd-55111f629a44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8661acf5-85d1-41ff-97ac-4014d26daa06' class='xr-var-data-in' type='checkbox'><label for='data-8661acf5-85d1-41ff-97ac-4014d26daa06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 7.97 TiB </td>\n",
       "                        <td> 71.19 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9030, 13, 4320, 4320) </td>\n",
       "                        <td> (1, 1, 4320, 4320) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
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       "                        <td> 117390 Chunks </td>\n",
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       "                    <th> Type </th>\n",
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      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 9030, face: 13, j: 4320, i: 4320)\n",
       "Coordinates:\n",
       "  * face     (face) int64 0 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "  * i        (i) int64 0 1 2 3 4 5 6 7 ... 4313 4314 4315 4316 4317 4318 4319\n",
       "  * j        (j) int64 0 1 2 3 4 5 6 7 ... 4313 4314 4315 4316 4317 4318 4319\n",
       "  * time     (time) datetime64[ns] 2011-09-13 ... 2012-09-23T05:00:00\n",
       "Data variables:\n",
       "    Eta      (time, face, j, i) float32 dask.array<chunksize=(1, 1, 4320, 4320), meta=np.ndarray>\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Created by calling `open_mdsdataset(llc_method='smallchunks...\n",
       "    source:       MITgcm\n",
       "    title:        netCDF wrapper of MITgcm MDS binary data"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ssh = cat.LLC4320_SSH.to_dask()\n",
    "ssh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "318de8a7-bd70-49f6-afd5-f761492511d1",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;Eta&#x27; (face: 13, j: 540, i: 540)&gt;\n",
       "dask.array&lt;getitem, shape=(13, 540, 540), dtype=float32, chunksize=(1, 540, 540), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
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       "  * j        (j) int64 0 8 16 24 32 40 48 ... 4264 4272 4280 4288 4296 4304 4312\n",
       "    time     datetime64[ns] 2011-09-13</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'Eta'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>face</span>: 13</li><li><span class='xr-has-index'>j</span>: 540</li><li><span class='xr-has-index'>i</span>: 540</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-307b0a5d-6720-46d5-b088-e24d95855019' class='xr-array-in' type='checkbox' checked><label for='section-307b0a5d-6720-46d5-b088-e24d95855019' 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, 540, 540), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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       "</table></div></div></li><li class='xr-section-item'><input id='section-4b37312c-5602-44bb-997d-3ecc5e38f339' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4b37312c-5602-44bb-997d-3ecc5e38f339' 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'>face</span></div><div class='xr-var-dims'>(face)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-c2856610-963e-4fbb-92a7-ff933a8704ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2856610-963e-4fbb-92a7-ff933a8704ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a3e2ed2-59cf-4676-8003-c1d4ed20ee1f' class='xr-var-data-in' type='checkbox'><label for='data-5a3e2ed2-59cf-4676-8003-c1d4ed20ee1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>face_index</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>i</span></div><div class='xr-var-dims'>(i)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 8 16 24 ... 4288 4296 4304 4312</div><input id='attrs-ef86a381-ff0f-4b88-bcca-ec9ef15682c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef86a381-ff0f-4b88-bcca-ec9ef15682c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efc9ddc7-5b8e-43a1-a27a-ef300a0e0809' class='xr-var-data-in' type='checkbox'><label for='data-efc9ddc7-5b8e-43a1-a27a-ef300a0e0809' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>x_grid_index</dd><dt><span>swap_dim :</span></dt><dd>XC</dd></dl></div><div class='xr-var-data'><pre>array([   0,    8,   16, ..., 4296, 4304, 4312])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>j</span></div><div class='xr-var-dims'>(j)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 8 16 24 ... 4288 4296 4304 4312</div><input id='attrs-127d958a-5cc6-4175-8c1d-1286c70605d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-127d958a-5cc6-4175-8c1d-1286c70605d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29aab65e-e44b-487a-99e2-bed920a7d8be' class='xr-var-data-in' type='checkbox'><label for='data-29aab65e-e44b-487a-99e2-bed920a7d8be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y-dimension of the t grid</dd><dt><span>standard_name :</span></dt><dd>y_grid_index</dd><dt><span>swap_dim :</span></dt><dd>YC</dd></dl></div><div class='xr-var-data'><pre>array([   0,    8,   16, ..., 4296, 4304, 4312])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2011-09-13</div><input id='attrs-52f67ae2-b0e0-487b-926d-04bf0f890018' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52f67ae2-b0e0-487b-926d-04bf0f890018' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-188beb1c-dffe-4ed1-9db1-0e412d4bc68c' class='xr-var-data-in' type='checkbox'><label for='data-188beb1c-dffe-4ed1-9db1-0e412d4bc68c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2011-09-13T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e1233bfc-2d7a-4d4b-90d5-faf8f9d9cc5b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e1233bfc-2d7a-4d4b-90d5-faf8f9d9cc5b' 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 'Eta' (face: 13, j: 540, i: 540)>\n",
       "dask.array<getitem, shape=(13, 540, 540), dtype=float32, chunksize=(1, 540, 540), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * face     (face) int64 0 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "  * i        (i) int64 0 8 16 24 32 40 48 ... 4264 4272 4280 4288 4296 4304 4312\n",
       "  * j        (j) int64 0 8 16 24 32 40 48 ... 4264 4272 4280 4288 4296 4304 4312\n",
       "    time     datetime64[ns] 2011-09-13"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ssh = ssh[\"Eta\"].isel(time=0, i=indices, j=indices)\n",
    "ssh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ed71e650-837a-4801-bff2-8fefe71a2520",
   "metadata": {},
   "outputs": [],
   "source": [
    "mesh.packing(\n",
    "    numpy.vstack((lons.values.ravel(), lats.values.ravel())).T,\n",
    "    ssh.values.ravel())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "69f21387-01bc-44bc-a13d-a6f44a4c3b8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyinterp.rtree.RTree at 0x7f90663ecf70>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mesh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6430cf44-3eb8-405c-8766-5990bb1b06ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "x0, x1 = 100, 170\n",
    "y0, y1 = -15, 30\n",
    "res = 1 / 48.0\n",
    "mx, my = numpy.meshgrid(numpy.arange(x0, x1, res),\n",
    "                        numpy.arange(y0, y1, res),\n",
    "                        indexing=\"ij\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9fabf613-c1ca-4420-8d61-568029417158",
   "metadata": {},
   "outputs": [],
   "source": [
    "idw_eta, neighbors = mesh.inverse_distance_weighting(\n",
    "    numpy.vstack((mx.ravel(), my.ravel())).T,\n",
    "    within=True,  # Extrapolation is forbidden\n",
    "    radius=55000,  # In a radius of 5.5 Km\n",
    "    k=8,  # We are looking for at most 8 neighbours\n",
    "    num_threads=0)\n",
    "idw_eta = idw_eta.reshape(mx.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "30b36f2a-a935-41b8-9b75-f205173ac0dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "rbf_eta, neighbors = mesh.radial_basis_function(\n",
    "    numpy.vstack((mx.ravel(), my.ravel())).T,\n",
    "    within=True,  # Extrapolation is forbidden\n",
    "    k=11,  # We are looking for at most 11 neighbours\n",
    "    num_threads=0)\n",
    "rbf_eta = rbf_eta.reshape(mx.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c3edb2b2-6d7c-4cb5-b85b-3a18f22708f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = matplotlib.pyplot.figure(figsize=(18, 9))\n",
    "\n",
    "lon_formatter = cartopy.mpl.ticker.LongitudeFormatter(\n",
    "    zero_direction_label=True)\n",
    "lat_formatter = cartopy.mpl.ticker.LatitudeFormatter()\n",
    "\n",
    "ax = fig.add_subplot(121, projection=cartopy.crs.PlateCarree())\n",
    "ax.pcolormesh(mx,\n",
    "              my,\n",
    "              idw_eta,\n",
    "              cmap='terrain',\n",
    "              shading='auto',\n",
    "              transform=cartopy.crs.PlateCarree())\n",
    "\n",
    "ax.coastlines()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "ax.set_xticks(numpy.arange(x0, x1, 10.0))\n",
    "ax.set_yticks(numpy.arange(y0, y1, 10))\n",
    "ax.set_title(\"Eta (IDW)\")\n",
    "\n",
    "ax = fig.add_subplot(122, projection=cartopy.crs.PlateCarree())\n",
    "ax.pcolormesh(mx,\n",
    "              my,\n",
    "              rbf_eta,\n",
    "              cmap='terrain',\n",
    "              shading='auto',\n",
    "              transform=cartopy.crs.PlateCarree())\n",
    "ax.coastlines()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "ax.set_xticks(numpy.arange(x0, x1, 10.0))\n",
    "ax.set_yticks(numpy.arange(y0, y1, 10))\n",
    "ax.set_title(\"Eta (RBF)\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0ccd589d-ae6c-4001-9365-af28f5a54da4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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