open_output.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "49216fc9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import xmitgcm\n",
    "import datetime\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from xgcm import Grid"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3eb2f66b",
   "metadata": {},
   "source": [
    "To open the output, point this to the location where the output is located, and run it (it's ok if there is a warning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6e57f166",
   "metadata": {},
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/scratch/user/spencerjones/.conda/envs/grace1/lib/python3.9/site-packages/xmitgcm/mds_store.py:913: UserWarning: Couldn't find available_diagnostics.log in /scratch/user/spencerjones/deep_ekman/run/ or /scratch/user/spencerjones/deep_ekman/run/. Using default version.\n",
      "  warnings.warn(\"Couldn't find available_diagnostics.log \"\n"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:               (time: 580, Z: 32, YC: 128, XG: 64, YG: 128, XC: 64, Zl: 32, Zp1: 33, Zu: 32, layer_1RHO_bounds: 37, layer_1RHO_center: 36, layer_1RHO_interface: 35)\n",
       "Coordinates: (12/37)\n",
       "    iter                  (time) int64 dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "  * time                  (time) timedelta64[ns] 0 days 04:10:00 ... 100 days...\n",
       "  * XC                    (XC) &gt;f4 0.5078 1.523 2.539 ... 62.46 63.48 64.49\n",
       "  * YC                    (YC) &gt;f4 -64.49 -63.46 -62.44 ... 63.46 64.49 65.51\n",
       "  * XG                    (XG) &gt;f4 -4.441e-16 1.016 2.031 ... 61.95 62.97 63.98\n",
       "  * YG                    (YG) &gt;f4 -65.0 -63.98 -62.95 ... 62.95 63.98 65.0\n",
       "    ...                    ...\n",
       "    dyU                   (YG, XG) &gt;f4 dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;\n",
       "    dxV                   (YG, XG) &gt;f4 dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;\n",
       "    rhoRef                (Z) &gt;f4 dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;\n",
       "  * layer_1RHO_bounds     (layer_1RHO_bounds) &gt;f4 28.0 29.0 29.5 ... 34.45 34.5\n",
       "  * layer_1RHO_center     (layer_1RHO_center) float32 28.5 29.25 ... 34.43 34.47\n",
       "  * layer_1RHO_interface  (layer_1RHO_interface) &gt;f4 29.0 29.5 ... 34.4 34.45\n",
       "Data variables:\n",
       "    UVEL                  (time, Z, YC, XG) float32 dask.array&lt;chunksize=(1, 32, 128, 64), meta=np.ndarray&gt;\n",
       "    VVEL                  (time, Z, YG, XC) float32 dask.array&lt;chunksize=(1, 32, 128, 64), meta=np.ndarray&gt;\n",
       "    WVEL                  (time, Zl, YC, XC) float32 dask.array&lt;chunksize=(1, 32, 128, 64), meta=np.ndarray&gt;\n",
       "    THETA                 (time, Z, YC, XC) float32 dask.array&lt;chunksize=(1, 32, 128, 64), meta=np.ndarray&gt;\n",
       "    SALT                  (time, Z, YC, XC) float32 dask.array&lt;chunksize=(1, 32, 128, 64), meta=np.ndarray&gt;\n",
       "    CONVADJ               (time, Zl, YC, XC) float32 dask.array&lt;chunksize=(1, 32, 128, 64), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    title:        netCDF wrapper of MITgcm MDS binary data\n",
       "    source:       MITgcm\n",
       "    history:      Created by calling `open_mdsdataset(grid_dir=None, iters=No...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8f60abb9-00ca-483b-9398-219a5f62841a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8f60abb9-00ca-483b-9398-219a5f62841a' 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>: 580</li><li><span class='xr-has-index'>Z</span>: 32</li><li><span class='xr-has-index'>YC</span>: 128</li><li><span class='xr-has-index'>XG</span>: 64</li><li><span class='xr-has-index'>YG</span>: 128</li><li><span class='xr-has-index'>XC</span>: 64</li><li><span class='xr-has-index'>Zl</span>: 32</li><li><span class='xr-has-index'>Zp1</span>: 33</li><li><span class='xr-has-index'>Zu</span>: 32</li><li><span class='xr-has-index'>layer_1RHO_bounds</span>: 37</li><li><span class='xr-has-index'>layer_1RHO_center</span>: 36</li><li><span class='xr-has-index'>layer_1RHO_interface</span>: 35</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b465ca45-23c1-400f-9673-c1875b443a89' class='xr-section-summary-in' type='checkbox'  ><label for='section-b465ca45-23c1-400f-9673-c1875b443a89' 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>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=(1,), meta=np.ndarray&gt;</div><input id='attrs-c24f41dd-d72d-4dbc-a1fe-9645c5279d35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c24f41dd-d72d-4dbc-a1fe-9645c5279d35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd3d7248-cde5-4c17-88ef-dcbae23cc2b7' class='xr-var-data-in' type='checkbox'><label for='data-fd3d7248-cde5-4c17-88ef-dcbae23cc2b7' 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>timestep</dd><dt><span>long_name :</span></dt><dd>model timestep number</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                </thead>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 4.53 kiB </td>\n",
       "                        <td> 8 B </td>\n",
       "                    </tr>\n",
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       "                        <th> Shape </th>\n",
       "                        <td> (580,) </td>\n",
       "                        <td> (1,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 1160 Tasks </td>\n",
       "                        <td> 580 Chunks </td>\n",
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       "                    <th> Type </th>\n",
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       "\n",
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       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
       "  <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"25\" />\n",
       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
       "  <line x1=\"107\" y1=\"0\" x2=\"107\" y2=\"25\" />\n",
       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >580</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>0 days 04:10:00 ... 100 days 16:...</div><input id='attrs-9d680a66-2f3f-4952-9210-e16d9009f395' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d680a66-2f3f-4952-9210-e16d9009f395' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e1a38e6-73e8-45bd-9af0-5bcaac4858bb' class='xr-var-data-in' type='checkbox'><label for='data-1e1a38e6-73e8-45bd-9af0-5bcaac4858bb' 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>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>calendar :</span></dt><dd>gregorian</dd></dl></div><div class='xr-var-data'><pre>array([  15000000000000,   30000000000000,   45000000000000, ...,\n",
       "       8670000000000000, 8685000000000000, 8700000000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>XC</span></div><div class='xr-var-dims'>(XC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>0.5078 1.523 2.539 ... 63.48 64.49</div><input id='attrs-37c0cda8-3133-43b4-8fb2-5490b0af1ece' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37c0cda8-3133-43b4-8fb2-5490b0af1ece' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-803f0811-8657-488d-a9c3-aac502e502f5' class='xr-var-data-in' type='checkbox'><label for='data-803f0811-8657-488d-a9c3-aac502e502f5' 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>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>coordinate :</span></dt><dd>YC XC</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 0.507815,  1.523445,  2.539075,  3.554705,  4.570335,  5.585965,\n",
       "        6.601595,  7.617225,  8.632855,  9.648485, 10.664115, 11.679745,\n",
       "       12.695375, 13.711005, 14.726635, 15.742265, 16.757895, 17.773525,\n",
       "       18.789154, 19.804785, 20.820415, 21.836044, 22.851675, 23.867306,\n",
       "       24.882935, 25.898565, 26.914194, 27.929825, 28.945456, 29.961084,\n",
       "       30.976715, 31.992346, 33.007977, 34.023605, 35.039234, 36.054867,\n",
       "       37.070496, 38.086124, 39.101753, 40.117386, 41.133015, 42.148643,\n",
       "       43.164276, 44.179905, 45.195534, 46.211166, 47.226795, 48.242424,\n",
       "       49.258057, 50.273685, 51.289314, 52.304947, 53.320576, 54.336205,\n",
       "       55.351833, 56.367466, 57.383095, 58.398724, 59.414356, 60.429985,\n",
       "       61.445614, 62.461246, 63.476875, 64.49251 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>YC</span></div><div class='xr-var-dims'>(YC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>-64.49 -63.46 ... 64.49 65.51</div><input id='attrs-11b4d111-69ac-4009-bddf-09ecbd677dcc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11b4d111-69ac-4009-bddf-09ecbd677dcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fd467e5-ffa7-4f04-afe6-283aa155bf3a' class='xr-var-data-in' type='checkbox'><label for='data-9fd467e5-ffa7-4f04-afe6-283aa155bf3a' 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>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>coordinate :</span></dt><dd>YC XC</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-6.448819e+01, -6.346457e+01, -6.244095e+01, -6.141733e+01,\n",
       "       -6.039371e+01, -5.937009e+01, -5.834647e+01, -5.732285e+01,\n",
       "       -5.629923e+01, -5.527561e+01, -5.425199e+01, -5.322837e+01,\n",
       "       -5.220475e+01, -5.118113e+01, -5.015751e+01, -4.913389e+01,\n",
       "       -4.811027e+01, -4.708665e+01, -4.606303e+01, -4.503941e+01,\n",
       "       -4.401579e+01, -4.299217e+01, -4.196855e+01, -4.094493e+01,\n",
       "       -3.992131e+01, -3.889769e+01, -3.787407e+01, -3.685045e+01,\n",
       "       -3.582683e+01, -3.480321e+01, -3.377959e+01, -3.275597e+01,\n",
       "       -3.173235e+01, -3.070873e+01, -2.968511e+01, -2.866149e+01,\n",
       "       -2.763787e+01, -2.661425e+01, -2.559063e+01, -2.456701e+01,\n",
       "       -2.354339e+01, -2.251977e+01, -2.149615e+01, -2.047253e+01,\n",
       "       -1.944891e+01, -1.842529e+01, -1.740167e+01, -1.637805e+01,\n",
       "       -1.535443e+01, -1.433081e+01, -1.330719e+01, -1.228357e+01,\n",
       "       -1.125995e+01, -1.023633e+01, -9.212710e+00, -8.189090e+00,\n",
       "       -7.165470e+00, -6.141850e+00, -5.118230e+00, -4.094610e+00,\n",
       "       -3.070990e+00, -2.047370e+00, -1.023750e+00, -1.300000e-04,\n",
       "        1.023490e+00,  2.047110e+00,  3.070730e+00,  4.094350e+00,\n",
       "        5.117970e+00,  6.141590e+00,  7.165210e+00,  8.188830e+00,\n",
       "        9.212450e+00,  1.023607e+01,  1.125969e+01,  1.228331e+01,\n",
       "        1.330693e+01,  1.433055e+01,  1.535417e+01,  1.637779e+01,\n",
       "        1.740141e+01,  1.842503e+01,  1.944865e+01,  2.047227e+01,\n",
       "        2.149589e+01,  2.251951e+01,  2.354313e+01,  2.456675e+01,\n",
       "        2.559037e+01,  2.661399e+01,  2.763761e+01,  2.866123e+01,\n",
       "        2.968485e+01,  3.070847e+01,  3.173209e+01,  3.275571e+01,\n",
       "        3.377933e+01,  3.480295e+01,  3.582657e+01,  3.685019e+01,\n",
       "        3.787381e+01,  3.889743e+01,  3.992105e+01,  4.094467e+01,\n",
       "        4.196829e+01,  4.299191e+01,  4.401553e+01,  4.503915e+01,\n",
       "        4.606277e+01,  4.708639e+01,  4.811001e+01,  4.913363e+01,\n",
       "        5.015725e+01,  5.118087e+01,  5.220449e+01,  5.322811e+01,\n",
       "        5.425173e+01,  5.527535e+01,  5.629897e+01,  5.732259e+01,\n",
       "        5.834621e+01,  5.936983e+01,  6.039345e+01,  6.141707e+01,\n",
       "        6.244069e+01,  6.346431e+01,  6.448793e+01,  6.551155e+01],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>XG</span></div><div class='xr-var-dims'>(XG)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>-4.441e-16 1.016 ... 62.97 63.98</div><input id='attrs-f7096529-f565-431d-9ff4-6c10c596d0e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7096529-f565-431d-9ff4-6c10c596d0e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cd3c314-a337-4a65-a3ec-c7a98559b383' class='xr-var-data-in' type='checkbox'><label for='data-3cd3c314-a337-4a65-a3ec-c7a98559b383' 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>longitude_at_f_location</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>coordinate :</span></dt><dd>YG XG</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd></dl></div><div class='xr-var-data'><pre>array([-4.440892e-16,  1.015630e+00,  2.031260e+00,  3.046890e+00,\n",
       "        4.062520e+00,  5.078150e+00,  6.093780e+00,  7.109410e+00,\n",
       "        8.125040e+00,  9.140670e+00,  1.015630e+01,  1.117193e+01,\n",
       "        1.218756e+01,  1.320319e+01,  1.421882e+01,  1.523445e+01,\n",
       "        1.625008e+01,  1.726571e+01,  1.828134e+01,  1.929697e+01,\n",
       "        2.031260e+01,  2.132823e+01,  2.234386e+01,  2.335949e+01,\n",
       "        2.437512e+01,  2.539075e+01,  2.640638e+01,  2.742201e+01,\n",
       "        2.843764e+01,  2.945327e+01,  3.046890e+01,  3.148453e+01,\n",
       "        3.250016e+01,  3.351579e+01,  3.453142e+01,  3.554705e+01,\n",
       "        3.656268e+01,  3.757831e+01,  3.859394e+01,  3.960957e+01,\n",
       "        4.062520e+01,  4.164083e+01,  4.265646e+01,  4.367209e+01,\n",
       "        4.468772e+01,  4.570335e+01,  4.671898e+01,  4.773461e+01,\n",
       "        4.875024e+01,  4.976587e+01,  5.078150e+01,  5.179713e+01,\n",
       "        5.281276e+01,  5.382839e+01,  5.484402e+01,  5.585965e+01,\n",
       "        5.687528e+01,  5.789091e+01,  5.890654e+01,  5.992217e+01,\n",
       "        6.093780e+01,  6.195343e+01,  6.296906e+01,  6.398469e+01],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>YG</span></div><div class='xr-var-dims'>(YG)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>-65.0 -63.98 -62.95 ... 63.98 65.0</div><input id='attrs-3f35105a-8dff-4abb-aeff-6bc595f39303' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f35105a-8dff-4abb-aeff-6bc595f39303' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa827fe3-f5d6-4abc-9068-aeb782402bf0' class='xr-var-data-in' type='checkbox'><label for='data-aa827fe3-f5d6-4abc-9068-aeb782402bf0' 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>latitude_at_f_location</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>coordinate :</span></dt><dd>YG XG</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd></dl></div><div class='xr-var-data'><pre>array([-65.     , -63.97638, -62.95276, -61.92914, -60.90552, -59.8819 ,\n",
       "       -58.85828, -57.83466, -56.81104, -55.78742, -54.7638 , -53.74018,\n",
       "       -52.71656, -51.69294, -50.66932, -49.6457 , -48.62208, -47.59846,\n",
       "       -46.57484, -45.55122, -44.5276 , -43.50398, -42.48036, -41.45674,\n",
       "       -40.43312, -39.4095 , -38.38588, -37.36226, -36.33864, -35.31502,\n",
       "       -34.2914 , -33.26778, -32.24416, -31.22054, -30.19692, -29.1733 ,\n",
       "       -28.14968, -27.12606, -26.10244, -25.07882, -24.0552 , -23.03158,\n",
       "       -22.00796, -20.98434, -19.96072, -18.9371 , -17.91348, -16.88986,\n",
       "       -15.86624, -14.84262, -13.819  , -12.79538, -11.77176, -10.74814,\n",
       "        -9.72452,  -8.7009 ,  -7.67728,  -6.65366,  -5.63004,  -4.60642,\n",
       "        -3.5828 ,  -2.55918,  -1.53556,  -0.51194,   0.51168,   1.5353 ,\n",
       "         2.55892,   3.58254,   4.60616,   5.62978,   6.6534 ,   7.67702,\n",
       "         8.70064,   9.72426,  10.74788,  11.7715 ,  12.79512,  13.81874,\n",
       "        14.84236,  15.86598,  16.8896 ,  17.91322,  18.93684,  19.96046,\n",
       "        20.98408,  22.0077 ,  23.03132,  24.05494,  25.07856,  26.10218,\n",
       "        27.1258 ,  28.14942,  29.17304,  30.19666,  31.22028,  32.2439 ,\n",
       "        33.26752,  34.29114,  35.31476,  36.33838,  37.362  ,  38.38562,\n",
       "        39.40924,  40.43286,  41.45648,  42.4801 ,  43.50372,  44.52734,\n",
       "        45.55096,  46.57458,  47.5982 ,  48.62182,  49.64544,  50.66906,\n",
       "        51.69268,  52.7163 ,  53.73992,  54.76354,  55.78716,  56.81078,\n",
       "        57.8344 ,  58.85802,  59.88164,  60.90526,  61.92888,  62.9525 ,\n",
       "        63.97612,  64.99974], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Z</span></div><div class='xr-var-dims'>(Z)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>-6.797 -21.38 ... -3.857e+03</div><input id='attrs-42b0bb09-57e1-41ea-bfd2-2c97165c676c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42b0bb09-57e1-41ea-bfd2-2c97165c676c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66978935-e7c7-42ca-aaa4-56c85cd8b9fd' class='xr-var-data-in' type='checkbox'><label for='data-66978935-e7c7-42ca-aaa4-56c85cd8b9fd' 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>depth</dd><dt><span>long_name :</span></dt><dd>vertical coordinate of cell center</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([   -6.796724,   -21.3834  ,   -38.09691 ,   -57.236347,   -79.1394  ,\n",
       "        -104.18622 ,  -132.80336 ,  -165.4676  ,  -202.70941 ,  -245.11592 ,\n",
       "        -293.333   ,  -348.06604 ,  -410.0788  ,  -480.18994 ,  -559.2663  ,\n",
       "        -648.2124  ,  -747.9551  ,  -859.4225  ,  -983.5175  , -1121.084   ,\n",
       "       -1272.867   , -1439.4667  , -1621.2897  , -1818.4957  , -2030.9484  ,\n",
       "       -2258.1697  , -2499.307   , -2753.1128  , -3017.9485  , -3291.8066  ,\n",
       "       -3572.361   , -3857.0378  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Zp1</span></div><div class='xr-var-dims'>(Zp1)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>0.0 -13.59 ... -3.714e+03 -4e+03</div><input id='attrs-1550f84a-68a4-4720-b280-f99b46c7e126' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1550f84a-68a4-4720-b280-f99b46c7e126' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3418ff75-c05a-47ba-a2ec-bfda8da21dda' class='xr-var-data-in' type='checkbox'><label for='data-3418ff75-c05a-47ba-a2ec-bfda8da21dda' 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>depth_at_w_location</dd><dt><span>long_name :</span></dt><dd>vertical coordinate of cell interface</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>(-0.5, 0.5)</dd></dl></div><div class='xr-var-data'><pre>array([    0.      ,   -13.593449,   -29.173353,   -47.02047 ,   -67.452225,\n",
       "         -90.82656 ,  -117.54587 ,  -148.06087 ,  -182.87434 ,  -222.54446 ,\n",
       "        -267.68738 ,  -318.97867 ,  -377.15344 ,  -443.00418 ,  -517.3757  ,\n",
       "        -601.1569  ,  -695.2679  ,  -800.6422  ,  -918.2028  , -1048.8323  ,\n",
       "       -1193.3357  , -1352.3981  , -1526.5354  , -1716.044   , -1920.9475  ,\n",
       "       -2140.9492  , -2375.3904  , -2623.2234  , -2883.0024  , -3152.8948  ,\n",
       "       -3430.7188  , -3714.0034  , -4000.0723  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Zu</span></div><div class='xr-var-dims'>(Zu)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>-13.59 -29.17 ... -3.714e+03 -4e+03</div><input id='attrs-04e3259b-659d-4bcb-ac8c-86b0e46d9dd6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04e3259b-659d-4bcb-ac8c-86b0e46d9dd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22908c71-c62f-4deb-a7d0-19a11170c30e' class='xr-var-data-in' type='checkbox'><label for='data-22908c71-c62f-4deb-a7d0-19a11170c30e' 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>depth_at_upper_w_location</dd><dt><span>long_name :</span></dt><dd>vertical coordinate of upper cell interface</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>0.5</dd></dl></div><div class='xr-var-data'><pre>array([  -13.593449,   -29.173353,   -47.02047 ,   -67.452225,   -90.82656 ,\n",
       "        -117.54587 ,  -148.06087 ,  -182.87434 ,  -222.54446 ,  -267.68738 ,\n",
       "        -318.97867 ,  -377.15344 ,  -443.00418 ,  -517.3757  ,  -601.1569  ,\n",
       "        -695.2679  ,  -800.6422  ,  -918.2028  , -1048.8323  , -1193.3357  ,\n",
       "       -1352.3981  , -1526.5354  , -1716.044   , -1920.9475  , -2140.9492  ,\n",
       "       -2375.3904  , -2623.2234  , -2883.0024  , -3152.8948  , -3430.7188  ,\n",
       "       -3714.0034  , -4000.0723  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Zl</span></div><div class='xr-var-dims'>(Zl)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>0.0 -13.59 ... -3.714e+03</div><input id='attrs-14590212-6b3a-4274-928d-0d9fc00f9045' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14590212-6b3a-4274-928d-0d9fc00f9045' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46730c47-5ddf-485a-a9c9-50d83488c231' class='xr-var-data-in' type='checkbox'><label for='data-46730c47-5ddf-485a-a9c9-50d83488c231' 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>depth_at_lower_w_location</dd><dt><span>long_name :</span></dt><dd>vertical coordinate of lower cell interface</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd></dl></div><div class='xr-var-data'><pre>array([    0.      ,   -13.593449,   -29.173353,   -47.02047 ,   -67.452225,\n",
       "         -90.82656 ,  -117.54587 ,  -148.06087 ,  -182.87434 ,  -222.54446 ,\n",
       "        -267.68738 ,  -318.97867 ,  -377.15344 ,  -443.00418 ,  -517.3757  ,\n",
       "        -601.1569  ,  -695.2679  ,  -800.6422  ,  -918.2028  , -1048.8323  ,\n",
       "       -1193.3357  , -1352.3981  , -1526.5354  , -1716.044   , -1920.9475  ,\n",
       "       -2140.9492  , -2375.3904  , -2623.2234  , -2883.0024  , -3152.8948  ,\n",
       "       -3430.7188  , -3714.0034  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rA</span></div><div class='xr-var-dims'>(YC, XC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-89b858a0-3c00-4044-82ca-7888820050a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89b858a0-3c00-4044-82ca-7888820050a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e63a4f30-ef71-409d-8aac-0c935f5a714b' class='xr-var-data-in' type='checkbox'><label for='data-e63a4f30-ef71-409d-8aac-0c935f5a714b' 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>cell_area</dd><dt><span>long_name :</span></dt><dd>cell area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>coordinate :</span></dt><dd>YC XC</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"110\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"60\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"60\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 60.0,0.0 60.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"30.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >64</text>\n",
       "  <text x=\"80.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,80.000000,60.000000)\">128</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxG</span></div><div class='xr-var-dims'>(YG, XC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-2a6597ba-49e2-467b-8781-783a84cdd82b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a6597ba-49e2-467b-8781-783a84cdd82b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acbcef31-6d75-4db7-bae5-7cd3d0fb93ac' class='xr-var-data-in' type='checkbox'><label for='data-acbcef31-6d75-4db7-bae5-7cd3d0fb93ac' 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>cell_x_size_at_v_location</dd><dt><span>long_name :</span></dt><dd>cell x size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>YG XC</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"110\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"60\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"60\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 60.0,0.0 60.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"30.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >64</text>\n",
       "  <text x=\"80.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,80.000000,60.000000)\">128</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyG</span></div><div class='xr-var-dims'>(YC, XG)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-f8600855-e5e9-4ef4-8534-16c0f24c4fee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8600855-e5e9-4ef4-8534-16c0f24c4fee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1fdeb7e-28e5-4331-b654-828dc795b396' class='xr-var-data-in' type='checkbox'><label for='data-e1fdeb7e-28e5-4331-b654-828dc795b396' 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>cell_y_size_at_u_location</dd><dt><span>long_name :</span></dt><dd>cell y size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>YC XG</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"110\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"60\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"60\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 60.0,0.0 60.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"30.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >64</text>\n",
       "  <text x=\"80.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,80.000000,60.000000)\">128</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Depth</span></div><div class='xr-var-dims'>(YC, XC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-b2c91c21-d863-4eae-a6f0-b12b8c294039' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2c91c21-d863-4eae-a6f0-b12b8c294039' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1eb7be75-7483-4f47-a12f-b9887bdab6fa' class='xr-var-data-in' type='checkbox'><label for='data-1eb7be75-7483-4f47-a12f-b9887bdab6fa' 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>ocean_depth</dd><dt><span>long_name :</span></dt><dd>ocean depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>XC YC</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"110\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"60\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "\n",
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       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
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       "\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rAz</span></div><div class='xr-var-dims'>(YG, XG)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-ea85d8a5-80da-4c7b-9864-1d18adc07453' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea85d8a5-80da-4c7b-9864-1d18adc07453' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef5b3cdc-0fae-4315-98e1-0f5ebf3d4d65' class='xr-var-data-in' type='checkbox'><label for='data-ef5b3cdc-0fae-4315-98e1-0f5ebf3d4d65' 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>cell_area_at_f_location</dd><dt><span>long_name :</span></dt><dd>cell area</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>YG XG</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxC</span></div><div class='xr-var-dims'>(YC, XG)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-188e8856-b036-4881-9755-d960667bfb06' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-188e8856-b036-4881-9755-d960667bfb06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f7044f2-7475-4adb-a19a-914ff0b49f63' class='xr-var-data-in' type='checkbox'><label for='data-1f7044f2-7475-4adb-a19a-914ff0b49f63' 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>cell_x_size_at_u_location</dd><dt><span>long_name :</span></dt><dd>cell x size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>YC XG</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "  <!-- Horizontal lines -->\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyC</span></div><div class='xr-var-dims'>(YG, XC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-40fe6cd9-3693-431f-9c6f-e2f3273500ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-40fe6cd9-3693-431f-9c6f-e2f3273500ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b614891-259d-4027-b750-7e15a90ec7f3' class='xr-var-data-in' type='checkbox'><label for='data-8b614891-259d-4027-b750-7e15a90ec7f3' 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>cell_y_size_at_v_location</dd><dt><span>long_name :</span></dt><dd>cell y size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>YG XC</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"110\" height=\"170\" 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>rAw</span></div><div class='xr-var-dims'>(YC, XG)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-a72f98d3-c4c1-4664-b9cd-d5b326fc6afb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a72f98d3-c4c1-4664-b9cd-d5b326fc6afb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-130567c1-ecf4-475c-be34-c1e763677b92' class='xr-var-data-in' type='checkbox'><label for='data-130567c1-ecf4-475c-be34-c1e763677b92' 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>cell_area_at_u_location</dd><dt><span>long_name :</span></dt><dd>cell area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>coordinate :</span></dt><dd>YG XC</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"110\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "  <!-- Horizontal lines -->\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rAs</span></div><div class='xr-var-dims'>(YG, XC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-18208e90-b973-4452-a848-7e15307e74f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18208e90-b973-4452-a848-7e15307e74f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d39b52b-5d76-4fcb-b330-bd35867653db' class='xr-var-data-in' type='checkbox'><label for='data-1d39b52b-5d76-4fcb-b330-bd35867653db' 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>cell_area_at_v_location</dd><dt><span>long_name :</span></dt><dd>cell area</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>coordinate :</span></dt><dd>YG XC</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drC</span></div><div class='xr-var-dims'>(Zp1)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(33,), meta=np.ndarray&gt;</div><input id='attrs-209417d4-9fdc-4203-b7f9-8099ed7bae2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-209417d4-9fdc-4203-b7f9-8099ed7bae2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f759179-e5ae-4e93-b40d-9f6d9a986df4' class='xr-var-data-in' type='checkbox'><label for='data-1f759179-e5ae-4e93-b40d-9f6d9a986df4' 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>cell_z_size_at_w_location</dd><dt><span>long_name :</span></dt><dd>cell z size</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> 132 B </td>\n",
       "                        <td> 132 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (33,) </td>\n",
       "                        <td> (33,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 1 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drF</span></div><div class='xr-var-dims'>(Z)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-1ce92a8a-d8dd-4e06-85bd-c957d12ceb99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ce92a8a-d8dd-4e06-85bd-c957d12ceb99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1006db7d-bbda-4148-9487-c65f47b69a21' class='xr-var-data-in' type='checkbox'><label for='data-1006db7d-bbda-4148-9487-c65f47b69a21' 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>cell_z_size</dd><dt><span>long_name :</span></dt><dd>cell z size</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Chunk </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 128 B </td>\n",
       "                        <td> 128 B </td>\n",
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       "                        <td> (32,) </td>\n",
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       "                        <td> 1 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "        <td>\n",
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       "                    <tr>\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>hFacC</span></div><div class='xr-var-dims'>(Z, YC, XC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32, 128, 64), meta=np.ndarray&gt;</div><input id='attrs-a905a625-30d9-4814-90ed-7af34bc72fc6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a905a625-30d9-4814-90ed-7af34bc72fc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3babfff3-8e6e-490d-afec-22d1d3f72911' class='xr-var-data-in' type='checkbox'><label for='data-3babfff3-8e6e-490d-afec-22d1d3f72911' 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>cell_vertical_fraction</dd><dt><span>long_name :</span></dt><dd>vertical fraction of open cell</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> (32, 128, 64) </td>\n",
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       "                        <th> Count </th>\n",
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       "                        <td> 1 Chunks </td>\n",
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       "                    <tr>\n",
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       "                    <td> >f4 </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyF</span></div><div class='xr-var-dims'>(YC, XC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-23c029a2-8dfe-4354-8a62-e6624c3dae60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23c029a2-8dfe-4354-8a62-e6624c3dae60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eff10723-cd87-4068-a4dc-ab046205ee1e' class='xr-var-data-in' type='checkbox'><label for='data-eff10723-cd87-4068-a4dc-ab046205ee1e' 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>cell_y_size_at_t_location</dd><dt><span>long_name :</span></dt><dd>cell y size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>YC XC</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxF</span></div><div class='xr-var-dims'>(YC, XC)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-246d495b-5fa3-45f6-9368-7ca2909d06a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-246d495b-5fa3-45f6-9368-7ca2909d06a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e26453f1-4816-4ae2-9f3e-1813690213d3' class='xr-var-data-in' type='checkbox'><label for='data-e26453f1-4816-4ae2-9f3e-1813690213d3' 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>cell_x_size_at_t_location</dd><dt><span>long_name :</span></dt><dd>cell x size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>YC XC</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dyU</span></div><div class='xr-var-dims'>(YG, XG)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-a099612e-1aba-4d46-8fc1-a4dc560c50ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a099612e-1aba-4d46-8fc1-a4dc560c50ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4b39913-9571-40d6-bae6-c2f4abb2d530' class='xr-var-data-in' type='checkbox'><label for='data-f4b39913-9571-40d6-bae6-c2f4abb2d530' 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>cell_y_size_at_f_location</dd><dt><span>long_name :</span></dt><dd>cell y size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>YG XG</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxV</span></div><div class='xr-var-dims'>(YG, XG)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(128, 64), meta=np.ndarray&gt;</div><input id='attrs-9f7f1ed5-a665-4ee2-b928-8981008d1153' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f7f1ed5-a665-4ee2-b928-8981008d1153' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-516b787b-2c96-4103-85cc-5a264aee3e1c' class='xr-var-data-in' type='checkbox'><label for='data-516b787b-2c96-4103-85cc-5a264aee3e1c' 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>cell_x_size_at_f_location</dd><dt><span>long_name :</span></dt><dd>cell x size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>coordinate :</span></dt><dd>YG XG</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> 32.00 kiB </td>\n",
       "                        <td> 32.00 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (128, 64) </td>\n",
       "                        <td> (128, 64) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 3 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rhoRef</span></div><div class='xr-var-dims'>(Z)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(32,), meta=np.ndarray&gt;</div><input id='attrs-83ae3bfb-bba9-4b83-820f-fbde90237425' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83ae3bfb-bba9-4b83-820f-fbde90237425' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0a9de77-6ae9-443d-b827-8c2fb3cc1ea9' class='xr-var-data-in' type='checkbox'><label for='data-b0a9de77-6ae9-443d-b827-8c2fb3cc1ea9' 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>reference_density_profile</dd><dt><span>long_name :</span></dt><dd>1D, vertical reference density profile</dd><dt><span>coordinate :</span></dt><dd>Z</dd><dt><span>units :</span></dt><dd>kg m-3</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> 128 B </td>\n",
       "                        <td> 128 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (32,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 1 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> >f4 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "            </table>\n",
       "        </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>layer_1RHO_bounds</span></div><div class='xr-var-dims'>(layer_1RHO_bounds)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>28.0 29.0 29.5 ... 34.4 34.45 34.5</div><input id='attrs-0a749134-0c9a-458e-a54b-30028ae53c7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a749134-0c9a-458e-a54b-30028ae53c7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5147e56-f291-4cb6-b1c9-e45b706348db' class='xr-var-data-in' type='checkbox'><label for='data-e5147e56-f291-4cb6-b1c9-e45b706348db' 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>ocean_layer_coordinate_1RHO_bounds</dd><dt><span>long_name :</span></dt><dd>boundaries points of layer 1RHO</dd><dt><span>axis :</span></dt><dd>1RHO</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd></dl></div><div class='xr-var-data'><pre>array([28.  , 29.  , 29.5 , 30.  , 30.3 , 30.6 , 30.9 , 31.2 , 31.5 , 31.7 ,\n",
       "       31.9 , 32.1 , 32.3 , 32.5 , 32.7 , 32.9 , 33.1 , 33.3 , 33.5 , 33.7 ,\n",
       "       34.  , 34.1 , 34.2 , 34.21, 34.22, 34.23, 34.24, 34.26, 34.28, 34.3 ,\n",
       "       34.32, 34.34, 34.36, 34.38, 34.4 , 34.45, 34.5 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>layer_1RHO_center</span></div><div class='xr-var-dims'>(layer_1RHO_center)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>28.5 29.25 29.75 ... 34.43 34.47</div><input id='attrs-55c56fdd-e10e-49e4-aa63-d6b6ce4a664a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55c56fdd-e10e-49e4-aa63-d6b6ce4a664a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bd6d5e7-8a5f-4ac9-adf1-5878b018698a' class='xr-var-data-in' type='checkbox'><label for='data-7bd6d5e7-8a5f-4ac9-adf1-5878b018698a' 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>ocean_layer_coordinate_1RHO_center</dd><dt><span>long_name :</span></dt><dd>center points of layer 1RHO</dd><dt><span>axis :</span></dt><dd>1RHO</dd></dl></div><div class='xr-var-data'><pre>array([28.5     , 29.25    , 29.75    , 30.15    , 30.45    , 30.75    ,\n",
       "       31.05    , 31.35    , 31.6     , 31.8     , 32.      , 32.199997,\n",
       "       32.4     , 32.6     , 32.800003, 33.      , 33.199997, 33.4     ,\n",
       "       33.6     , 33.85    , 34.05    , 34.15    , 34.205   , 34.215   ,\n",
       "       34.225   , 34.235   , 34.25    , 34.269997, 34.29    , 34.309998,\n",
       "       34.33    , 34.35    , 34.370003, 34.39    , 34.425003, 34.475   ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>layer_1RHO_interface</span></div><div class='xr-var-dims'>(layer_1RHO_interface)</div><div class='xr-var-dtype'>&gt;f4</div><div class='xr-var-preview xr-preview'>29.0 29.5 30.0 ... 34.38 34.4 34.45</div><input id='attrs-e64b5d7e-c51f-4c0b-a981-1d3cea27facf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e64b5d7e-c51f-4c0b-a981-1d3cea27facf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1fb5a4e-e2f6-4792-91a2-d62c40b7702b' class='xr-var-data-in' type='checkbox'><label for='data-e1fb5a4e-e2f6-4792-91a2-d62c40b7702b' 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>ocean_layer_coordinate_1RHO_interface</dd><dt><span>long_name :</span></dt><dd>interface points of layer 1RHO</dd><dt><span>axis :</span></dt><dd>1RHO</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd></dl></div><div class='xr-var-data'><pre>array([29.  , 29.5 , 30.  , 30.3 , 30.6 , 30.9 , 31.2 , 31.5 , 31.7 , 31.9 ,\n",
       "       32.1 , 32.3 , 32.5 , 32.7 , 32.9 , 33.1 , 33.3 , 33.5 , 33.7 , 34.  ,\n",
       "       34.1 , 34.2 , 34.21, 34.22, 34.23, 34.24, 34.26, 34.28, 34.3 , 34.32,\n",
       "       34.34, 34.36, 34.38, 34.4 , 34.45], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1a897c9f-8b35-45c5-a5be-5ead2f045624' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1a897c9f-8b35-45c5-a5be-5ead2f045624' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>UVEL</span></div><div class='xr-var-dims'>(time, Z, YC, XG)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 32, 128, 64), meta=np.ndarray&gt;</div><input id='attrs-ca073e35-e7d1-4a98-adb6-2e803b525fbb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca073e35-e7d1-4a98-adb6-2e803b525fbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e543934-ff1f-4d2e-ac87-1cfd086ec58b' class='xr-var-data-in' type='checkbox'><label for='data-8e543934-ff1f-4d2e-ac87-1cfd086ec58b' 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>UVEL</dd><dt><span>long_name :</span></dt><dd>Zonal Component of Velocity (m/s)</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>mate :</span></dt><dd>VVEL</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 580.00 MiB </td>\n",
       "                        <td> 1.00 MiB </td>\n",
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       "                        <th> Shape </th>\n",
       "                        <td> (580, 32, 128, 64) </td>\n",
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       "                    <tr>\n",
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       "                        <td> 2900 Tasks </td>\n",
       "                        <td> 580 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>VVEL</span></div><div class='xr-var-dims'>(time, Z, YG, XC)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 32, 128, 64), meta=np.ndarray&gt;</div><input id='attrs-14c08019-861d-4763-9452-cff83c38cacf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14c08019-861d-4763-9452-cff83c38cacf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a9a1ba0-17eb-48c5-9f35-614370ea3b0f' class='xr-var-data-in' type='checkbox'><label for='data-6a9a1ba0-17eb-48c5-9f35-614370ea3b0f' 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>VVEL</dd><dt><span>long_name :</span></dt><dd>Meridional Component of Velocity (m/s)</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>mate :</span></dt><dd>UVEL</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> 580.00 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WVEL</span></div><div class='xr-var-dims'>(time, Zl, YC, XC)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 32, 128, 64), meta=np.ndarray&gt;</div><input id='attrs-3b6a83ef-f05a-4899-b80d-567d15dfc8e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b6a83ef-f05a-4899-b80d-567d15dfc8e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3125a42-a6d2-4fc7-869d-ba6c0cf3ff52' class='xr-var-data-in' type='checkbox'><label for='data-d3125a42-a6d2-4fc7-869d-ba6c0cf3ff52' 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>WVEL</dd><dt><span>long_name :</span></dt><dd>Vertical Component of Velocity (r_units/s)</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><table>\n",
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       "<xarray.Dataset>\n",
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       "Coordinates: (12/37)\n",
       "    iter                  (time) int64 dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "  * time                  (time) timedelta64[ns] 0 days 04:10:00 ... 100 days...\n",
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       "  * YG                    (YG) >f4 -65.0 -63.98 -62.95 ... 62.95 63.98 65.0\n",
       "    ...                    ...\n",
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       "    dxV                   (YG, XG) >f4 dask.array<chunksize=(128, 64), meta=np.ndarray>\n",
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       "  * layer_1RHO_center     (layer_1RHO_center) float32 28.5 29.25 ... 34.43 34.47\n",
       "  * layer_1RHO_interface  (layer_1RHO_interface) >f4 29.0 29.5 ... 34.4 34.45\n",
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       "    CONVADJ               (time, Zl, YC, XC) float32 dask.array<chunksize=(1, 32, 128, 64), meta=np.ndarray>\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    title:        netCDF wrapper of MITgcm MDS binary data\n",
       "    source:       MITgcm\n",
       "    history:      Created by calling `open_mdsdataset(grid_dir=None, iters=No..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = xmitgcm.open_mdsdataset('/scratch/user/spencerjones/deep_ekman/run/',prefix=['dyn'])\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bfa7d8a",
   "metadata": {},
   "source": [
    "Salinity in should be equal to salinity out so let's check that the salt drift is small"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d6636134",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2ad72e2e50d0>]"
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     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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7SysY0CeF5VsPc8XU4fzbjdNiGGHvpqQhInFlXZM7on7656389M9bGz6fkasH9WJJNzCLSFyJThoXnz6U7147pWG4j9SkhIZLVRIbOtMQkZjbV1LBqh1HOHSsijc3HWgovzEvl7mTh5GSmMAbmw5w7oTBpKfq11Ys6eiLSMzN+8lb7C2paPg8LTeTrQePMX10FgCzxw0EaDZvt3Q9JQ0RibnohAFw13mncMXUYQ23044elM72hVfGIjRpQklDRDrd2sJins3fyb9cM5nH/rqN5ETjzc0HKKuqbbH+5BEZev4iTilpiEinu+uX+ewprmD+x0bzvZfebyifMTqL5ETjnPGDqKl1/u6sHDbuLWX0oL4xjFbaoqQhIp1uT3Hk8tMf/raroSwlKYFnv3A2iQk6o+hOdMutiHSqX7x1fNrV/3pzS8PyKdn9lDC6IZ1piEineqvgIAAP3nIWRWVVpKckUVvnnDVqQGwDk5OipCEiJ+R/PjjArLEDSU1KbFReVVPH8+/tIsGMGaOzKNh/lD0lFazaUcS1Z47gGg1Z3iMoaYhIaBv3lnDbYyu4bc5ovnPtlEbrlm7Y2+rUq2efMqgrwpMuoKQhIqEdragBaHHGvLWFzctmjM7iZ7fnMTA9pdNjk66hpCEiodU/V/HeziJu/flyKqrr6JuSSM6APmw9cIypOZnsLangQGklAFl9k5UwehglDREJrbi8umH5rYJDzdbfMmsUt8waxXOrCkkw4/6rJnVleNIFlDREJLTopDE0I5V9JZWN1k/JyeBTs0fxqdkaI6qn0nMaIhJadNK4Ka/5rHln5AzowmgkFnSmISKhlVREksZ3rp3CNWeM4OxTBlNcXk1VbR01tXVMycmIcYTS2ZQ0RKRV1bV1vL3lEJ84NZutB47y3o4isvunctuc0YBupe2NdHlKRFr1n38qYP7jK1i25RDfeG4d72w7zNhB6bEOS2JISUNEWlU/9eoH+0tZu6uYG2bk8svPzYpxVBJLShoiwpL1e/nsEysp2H+0oezflm5i1Y4jADz0RgFHK2uYOab58CHSuyhpiAi/fmcHf9q4nxfX7AGgvKqWh94oID01iVOH9iNnQB/OGT+IT0zMjnGkEmuhOsLN7DLgP4BE4OfuvrDJegvWXwGUAZ9x97+11dbMBgK/AcYA24Eb3f2ImQ0CfgfMBJ5w97uj9vMmMBwoD4rmuvv+E/7WItJIUVkVAKsLiyitqGZtYTF1DvdfNYlLJw+LcXQST9pNGmaWCDwEXAIUAivNbLG7b4iqdjkwIXjNBh4GZrfTdgHwursvNLMFwed7gQrgfmBK8GrqVnfPP6lvKyLN3LUonzXBuFF/2rifqd9e2rBuSk5mrMKSOBXmTGMWUODuWwHM7BlgHhCdNOYBi9zdgeVmNsDMhhM5i2it7Tzg/KD9k8CbwL3ufgz4q5mN/2hfTUTCWLphHwBXTh3eaI6LYZlp5AzoE6OoJF6FSRo5wM6oz4VEzibaq5PTTtuh7r4HwN33mNmQkDH/wsxqgd8D3w0SlYicgHW7iik8UkZ2/7SGsow+yXzu3HExjEq6gzBJo6X5GJv+om6tTpi2J+JWd99lZv2JJI3bgEVNK5nZXcBdAKNGaQwckaY++fDbVNXUNSq7QJ3cEkKYu6cKgehBZnKB3SHrtNV2X3AJi+C93Q5td98VvJcCTxG5dNZSvUfdPc/d87Kz9YMgEu1AaWWjhHH9jFw2ffcy5qrDW0IIc6axEphgZmOBXcDNwKea1FkM3B30WcwGioNLTgfaaLsYmA8sDN6fbysIM0sCBrj7QTNLBq4CXgsRv0ivsa+kgm89v56y6lrcncQEo7q2jpTEBMqra0lPSeJIcKdUvXMnDNazFxJau0nD3WvM7G5gCZHbZh939/Vm9sVg/SPAS0Ruty0gcsvtHW21DTa9EHjWzO4EdgA31O/TzLYDGUCKmV0LzAU+BJYECSORSML42Uf69iI9zNtbDvLK+r0Nn7P6JnOkrLpRnWm5mVwwMZvJIzJ598MjfHz84K4OU7qxUM9puPtLRBJDdNkjUcsOfCVs26D8EHBRK23GtBLKjDDxivRGdXXO7qKKRmX/fNlp3PeHtY3Knr/7410ZlvQwGuVWpIf4u/96i9VN5uk+c+QAAC4+fQivvb+fM3L13IV8NEoaIj1AcXl1o4Tx8tfOpbbOOX14Bo98ejofn5BN/vbDTB6hpCEfjZKGSDd1+FgVe4rLmTwik/W7G59hnD78+GRIl00ZDsD5E8M+CiXSOg1YKNJN3fzoMq588K/U1NY1DGEOcM54TYwknUdnGiLd1OZ9kWHMtx48xrpdJYzITOPNr19AYkJLz9SKdAwlDZFuorismm8+v47yqhqiB8/5+m9Xs+3gMeaMG0RKki4eSOdS0hDpJvI/PMwfVzcejCFnQB9q3Rk9KJ3rZuTGKDLpTZQ0RLqJ/aWVjT5/7JRBPPX5OTGKRnorJQ2RODbre6+xv7SSqTmZrN3V+A6p8UP6xSgq6c2UNETi1P6Sioazi+iE8eObzqS2zrli6vBYhSa9mJKGSBxase0wf97c8sDP156V08XRiBynpCESZ4rLqrn50WXUtTDzzARdkpIYU9IQiTPrdhdT5/DAjdO4YOIQUpISKCqvZkCfZN1SKzGnpCESByqqa/nuixvYV1LJriPlAFwwcQhZ6SkApKfqR1Xig/4nisSBl9ft4VfLdwAwelBfrpue25AwROKJkoZIDLg77pCQYNTVOTsPlzese/YLZzM0Iy2G0Ym0TklDpAu5OzO/9zoHj1a2WkcJQ+KZkoZIFyo8Ut5iwvjqheMZkpGmu6Mk7ilpiHSRFdsO8/rGfS2u+8e5E7s4GpGTo6Qh0gWKyqq46dFljUanrTd5REbzQpE4paQh0gX2FFfgDt+6ehLXTBtBclICSQlGTZ2TqmcvpBtR0hDpRK+s28MLa/bw9pZDAEzNyWRQv9QYRyVy8pQ0RDrRD1/ZxNaDxxo+D+mvO6Oke9N5sUgnqa6to/BIeaOyIRk6y5DuTWcaIh3knIV/4qaZIzn7lEHc8MiyFuukJSd2cVQiHUtJQ6QDVFTXsquonAde3cylu4c2lP/TJady/sQhrNtdTM6APjGMUKRjhLo8ZWaXmdkmMyswswUtrDczezBYv8bMprfX1swGmtmrZvZB8J4VlA8yszfM7KiZ/aTJfmaY2dpgWw+amZ38Vxf56I4cq2Lp+r0s3XD8+Yu9Jccf3rvnoglMzc3kllmjOO/U7FiEKNKh2k0aZpYIPARcDkwCbjGzSU2qXQ5MCF53AQ+HaLsAeN3dJwCvB58BKoD7gf/VQjgPB9uv39dlob6lSCf54ZKN3PXLd/nq06saylbvLAI094X0TGHONGYBBe6+1d2rgGeAeU3qzAMWecRyYICZDW+n7TzgyWD5SeBaAHc/5u5/JZI8GgTby3D3Ze7uwKL6NiKxsnpncYvl/3Dxqfzxno93cTQinS9M0sgBdkZ9LgzKwtRpq+1Qd98DELwPCRFHYTtxiHSJP28+wG9W7mDzvtJG5eMGpwNwxshMdXpLjxSmI7ylfoOmgyG0VidM27BCb8vM7iJyGYtRo0ad5O5EWjf/8RUNy9dNz+WtgoPkjcniy+eP54dLNjJ77MAYRifSecIkjUJgZNTnXGB3yDopbbTdZ2bD3X1PcOlpf4g4ctuJAwB3fxR4FCAvL+9kk5RIKF+7aAL/duO0hs9P3DErhtGIdK4wl6dWAhPMbKyZpQA3A4ub1FkM3B7cRTUHKA4uObXVdjEwP1ieDzzfVhDB9krNbE5w19Tt7bUR6UifX5TPmAUvMmbBi43KRw7UrbTSe7R7puHuNWZ2N7AESAQed/f1ZvbFYP0jwEvAFUABUAbc0VbbYNMLgWfN7E5gB3BD/T7NbDuQAaSY2bXAXHffAHwJeALoA7wcvEQ6XWVNLa9uaDys+YC+yfzr9dPQnd/Sm5i3NFZzD5KXl+f5+fmxDkPi3N7iChISImNDrdh2mKOV1WT3S6Oqto6DRyvZU1TOt/+4oVGbH1w3lZtmqs9MeiYze9fd85qW64lwEWDO/3sdgL98/QJu/GnLQ4AkGNRF/Y01ZlB6V4QmEleUNESiFB4pa1b2rasnMWvsQDL7JJPVN4Xy6lpKyqsZO1hJQ3ofJQ3p9eqiTh/2lzafv3vu5GGNxo1KT01isObEkF5KQ6NLr3ekrKphecfhyJnGwk9OZXC/FK46YzgjMjUHhkg9nWlIrxd9drFuVzF9khO5aeZIbp6lTm6RppQ0pFe6+j//yqa9kSFAqmrrGsqXbtjHmEF9dRutSCuUNKTXqaiuZe2uYuaMG8jWA8fYX1pJgsFXL5pAZU0ds8ZoCBCR1ihpSK9TUl4NwJVnjGDp+r3sL63k7gvG8/cXnxrjyETinzrCpdcpDpJGZp9kEoLLUNkZ6uwWCUNJQ3qdkorjSaNedr+UWIUj0q3o8pT0aK9t2MdfCw5SXVtHTa1TXVvHXz44CESSRn1/d1KC/n4SCUNJQ3q0zy1qfdyxzD7JLLj8NIrKqpk9Tp3fImEoaUivldknmYHp6fz3V86JdSgi3YaShvQY7s61//U2q3cWkZqUQEZUn0W0/mlJlFbU0D9N//1FTpR+aqTHKDxSzuqdRQBU1tRxIHjSe9zgdG6ZNYq8MVkcPFrF6cP787cdRSQnqh9D5EQpaUi3VlxWTVl1DZl9knll3d4W69x7+WlcOnlYo7LcrL5dEZ5Ij6OkId3aFQ/+D7uKyjln/CDeKjjUUH7uhMHsOFzGh4fKNO+FSAdS0pBubVdROUBDwkgwyP/mJfRNSaSsqpbDxyoZP6R/LEMU6VGUNKRbeHrFDs4cOYDTh2dQXF7NA0s3cayqtsW6A9MjD+qlJSc2LItIx1DSkLhXW+fc94e1AGxfeCWvv7+PJ5d9yJD+qWT3T6WorIoh/dM4dKySRz49I8bRivRsShoS9w4dazyb3tpdxaQlJ/D2ggtJ0h1QIl1KSUPi0rHKGi554M98/5NT+cwvVjaUT/nWEsqrazkjN1MJQyQGlDQkLm05cJTdxRXc/dSqhrJZYwcyNScTgLmThsYqNJFeTUlD4tLK7UcAOFpZ01D27zedSc6APrEKSUTQ0OgSh9YWFvOdFzY0K8/ulxqDaEQkmpKGxJ31u4ublf3ui2eTkqT/riKxFuqn0MwuM7NNZlZgZgtaWG9m9mCwfo2ZTW+vrZkNNLNXzeyD4D0rat19Qf1NZnZpVPmbQdl7wWvIyX91iSelFdX8aMlGHli6ifeC8aOiTQn6MkQkttrt0zCzROAh4BKgEFhpZovdPfr6weXAhOA1G3gYmN1O2wXA6+6+MEgmC4B7zWwScDMwGRgBvGZmp7p7/ZNct7p765MkSLf0yJ+38NAbWxqV3ZQ3krNPGcQfV+8mLTkxRpGJSLQwHeGzgAJ33wpgZs8A84DopDEPWOTuDiw3swFmNhwY00bbecD5QfsngTeBe4PyZ9y9EthmZgVBDMtO/mtKd3PHOWP41tWTAbj2rJwYRyMi9cIkjRxgZ9TnQiJnE+3VyWmn7VB33wPg7nuiLjXlAMtb2Fa9X5hZLfB74LtBopJupn7ui1MGp/PnzQc4dKyq0fopI3Q5SiQehUka1kJZ01/UrdUJ0/ZE9neru+8ys/5EksZtwKJmGzC7C7gLYNSoUe3sTmKhpLyG1TuLGua/qHfPheOpqq1j7mQ9hyESj8J0hBcCI6M+5wK7Q9Zpq+2+4BIWwfv+9vbn7ruC91LgKSKXrZpx90fdPc/d87Kzs0N8RelKxypreGHt8f9CE4ceH4X2n+ZO5L7LT6d/Wsuz7olIbIVJGiuBCWY21sxSiHRSL25SZzFwe3AX1RygOLj01FbbxcD8YHk+8HxU+c1mlmpmY4l0rq8wsyQzGwxgZsnAVcC6k/jOEmM/WrKJbzx3/J/uvFMHAzB+SL9YhSQiIbV7ecrda8zsbmAJkAg87u7rzeyLwfpHgJeAK4ACoAy4o622waYXAs+a2Z3ADuCGoM16M3uWSGd5DfAVd681s3RgSZAwEoHXgJ91xEGQrrUq6pLUv94wjSunDudL54/Xcxgi3YD19H7kvLw8z8/XHbrxYNmWQ7y4djfP5hdSVVMHwLp/uZR+qRrNRiTemNm77p7XtFw/rdJl/v3VzazaeYSB6SlcMHEIOw6XKWGIdDP6iZUuUVfnrN9dzC2zRvF/502JdTgicpKUNKRDvbJuL1/69bu4Q1bfZMwid1DXuXOsqlbPX4h0c0oa0qFeWLOb+m6yI2XV3DZndMO6tOQELp0yLEaRiUhHUNKQDrHjUBlmsKaw8Qi137lWl6JEehIlDfnICvaXcvEDf2lWfs74QTGIRkQ6k26Ml49s3a6SFst/fvvMLo5ERDqbzjTkpLyybg/LthwiLSWRd7YebrFOnxQNZy7S0yhpyEn51uL17CupBCA58fgYk+dOGMzhY1Xccc7YWIUmIp1ISUNO2P7SCvaVVJKSmEBVbR23zh7Nt6+ZHOuwRKQLqE9DQnur4CA3/XQZq3YUAXDxpMgUKEMyUmMYlYh0JZ1pSGh3P/U3jpRVk9EnMmz5d+ZN4fRhGdzxMV2KEuktlDSkTeVVtRwpi8yqd6SsGoA/bdzPuMHpDOqXyj0XTYhleCLSxZQ0pE03Pbqs2QN7tXXOlBwNByLSG6lPQ9rUNGFMGzkAgCk5GTGIRkRiTWca0qJ3PzzMGxsPNCpLTDBmjcli9c4iDTwo0kspaUiLrnt4WbOy/7zlLLL7p7Js6yHOCM44RKR3UdKQZmpq6xqWh2WksbekglED+3LF1OEAvHDPubEKTURiTElDGnzzv9fy9Iqd1NYdnwJ44rD+7C2pYHC/lBhGJiLxQklDAKiqqeNXy3c0Krt62gi+O28Kv313J1eeMTxGkYlIPFHS6MV2HCoD4EhZFdsPHWu2/sc3nUligvG5c8d1dWgiEqeUNHqporIqzvvRG23WSUywNteLSO+jpNFLrd3V+PmLJ+6YSVbfFPqmJJKVrv4LEWmZkkYvUVFdyy+XfUhNnVNWVcNfNjd+BuP8iUNiFJmIdCdKGr3EE29vZ+HLGxuVjchMo39aMl++4JQYRSUi3Y2SRi+xu6i8WVlWegovflXPXIhIeKHGnjKzy8xsk5kVmNmCFtabmT0YrF9jZtPba2tmA83sVTP7IHjPilp3X1B/k5ldGlU+w8zWBuseNDP11Lbhna2HOP9Hb3Da/S/z2/zCZuuHZaTFICoR6c7aPdMws0TgIeASoBBYaWaL3X1DVLXLgQnBazbwMDC7nbYLgNfdfWGQTBYA95rZJOBmYDIwAnjNzE5199pgu3cBy4GXgMuAlz/qQeiplqzfx/bgttpTstM5+5RBJCUkMGN0FtsPHuPGmSNjHKGIdDdhLk/NAgrcfSuAmT0DzAOik8Y8YJG7O7DczAaY2XBgTBtt5wHnB+2fBN4E7g3Kn3H3SmCbmRUAs8xsO5Dh7suCbS0CrkVJo0V7ist598PDDZ+vPGME/3jJqTGMSER6gjBJIwfYGfW5kMjZRHt1ctppO9Td9wC4+x4zq799J4fImUTTbVUHy03LpYnKmloueeAvHK2saSgbqilZRaQDhOnTaKnfwEPWCdM27P5Cb8vM7jKzfDPLP3DgQEtVerTNe49ytLKGr140oWHeiyH91X8hIh9dmDONQiD64ncusDtknZQ22u4zs+HBWcZwYH872yoMltuKAwB3fxR4FCAvL6+9JNUj1NU5T63YweFjVawpLALg+um5rNh2CIC0ZM23JSIfXZjfJCuBCWY21sxSiHRSL25SZzFwe3AX1RygOLj01FbbxcD8YHk+8HxU+c1mlmpmY4l0rq8ItldqZnOCu6Zuj2rT67215SDf/O91PPDqZt7cdIDJIzIYObAP91w4gZTEBE2aJCIdot0zDXevMbO7gSVAIvC4u683sy8G6x8hcifTFUABUAbc0VbbYNMLgWfN7E5gB3BD0Ga9mT1LpLO8BvhKcOcUwJeAJ4A+RDrA1Qke2Hrg+ICDL3/tXCYM7Q/AOeMHs/l7l8cqLBHpYSxyw1PPlZeX5/n5+Sfc7rbH3mHc4HT+Zd6UTojqo3lvZxEPvLqZsYP68sc1e6gOJk0qrYh0fG/5/hUabFBEPhIze9fd85qW64nwVhytrGHLgebDhceDr/92NR/sP8pfospGD+rLZZOHMXPsQCUMEek0ShqtGNI/lW0HY580yqtqKTxSRlZ6CgZU1zrHom6lrXfF1OHce9lpXR+giPQqShqtGNI/jeVbD7dfsZN9/XereWHNnnbrqaNbRLqCkkYrhmakUlxeTUV1LWnJiTGLY9WOomZlXz7/FC6ZNJTqWqdvSiLuNDyPISLSmZQ0WlH/MNzClzeSnhpJGtNyBzB38rAO24e786vlH7K3pIIEM66fkcvmfUd5b+cRAOocdrUwOu31M3IZl92vw+IQEQlLSaMVU3Iy6Z+axK+WfwhArTv9UpNYM2koHTW47oeHyrj/+fUkWCRBHDxayYtr9lBaWUNisI/0lETmjBvE6xsjzz6OHNiHMYPSO2T/IiInSkmjFZNGZLD2XxpGZefpFTu47w9r2XG4jNEd9Eu7fsrVxXd/nO+9+D4vrd1LSUUN3/+7qXxq9qgO2YeISEdS0ghpak6ko/kTP3qToRmpTB+VxU8+NZ3EBOPHr20GYMW2w/zgujMYObBvq9s5dLSSrz6zimm5A3hm5U5SEhM4dWh/puZmsmzroUb7EhGJN0oaIZ0+PIOcAX3YVVTOvpJKXl63l20Hj3JKdj+eeHs7RWXVACx8ZSMPfWp6q9t5ad1e3io4xFsFhxiWkca9l59GSlICN+aN5EBpJVl9U5g0Qp3aIhKflDRCSkwwvv/Jqcx/fEVD2evv7+dIWXVDwgB4Z+thqmrqqKyppW9KEkcra0gwqKyp4+DRSvYWH+/YvnracO78+FgAxg/px7/fdGaXfR8RkZOhpHECpjQ5A/h/L29sVufg0UqmfnsJlTV1fPacsTz+1rZWtzdt5ICODlFEpFMpaZyAQf1Seflr51JT61TW1PLeziK+++L7zepV1kTGgmqaMC6dPJQl6/dF1n0mj/MmZHd+0CIiHUiTLJyg04dnMDU3k7wxA/n0nNHN1ie1Me7TjXnHpwm58LShJCXq8ItI96IzjY8gLTmRWWMHUlldy+rCyO2zQ/qnsru4AqDh+Yt600dlcdFpQ+ibqsMuIt2Tfnt9RM9+4WyOVdYw+VtLAMjOSGN3cQWv/9MnOKWFp7Yf+8zMrg5RRKTD6PpIB0iPOnMY0j+V9JRExuqpbRHpgXSm0UEe+fR03CGzTzIXnTaEBM1pISI9kJJGB7lsyvCG5Y/FMA4Rkc6ky1MiIhKakoaIiISmpCEiIqEpaYiISGhKGiIiEpqShoiIhKakISIioSlpiIhIaObu7dfqxszsAPDhSTQdDBzs4HB6Ah2X1unYtEzHpWXxflxGu3uz+Rt6fNI4WWaW7+55sY4j3ui4tE7HpmU6Li3rrsdFl6dERCQ0JQ0REQlNSaN1j8Y6gDil49I6HZuW6bi0rFseF/VpiIhIaDrTEBGR0JQ0REQkNCWNFpjZZWa2ycwKzGxBrOOJB2Y20szeMLP3zWy9mX0t1jHFEzNLNLNVZvZCrGOJF2Y2wMx+Z2Ybg/83Z8c6pnhgZv8Q/AytM7OnzSwt1jGdCCWNJswsEXgIuByYBNxiZpNiG1VcqAH+yd1PB+YAX9FxaeRrwPuxDiLO/AfwirufBkxDxwczywG+CuS5+xQgEbg5tlGdGCWN5mYBBe6+1d2rgGeAeTGOKebcfY+7/y1YLiXyCyAntlHFBzPLBa4Efh7rWOKFmWUA5wGPAbh7lbsXxTSo+JEE9DGzJKAvsDvG8ZwQJY3mcoCdUZ8L0S/HRsxsDHAW8E6MQ4kXPwb+GaiLcRzxZBxwAPhFcNnu52aWHuugYs3ddwH/CuwA9gDF7r40tlGdGCWN5qyFMt2XHDCzfsDvgb9395JYxxNrZnYVsN/d3411LHEmCZgOPOzuZwHHgF7fP2hmWUSuXIwFRgDpZvbp2EZ1YpQ0misERkZ9zqWbnT52FjNLJpIwfu3uf4h1PHHiHOAaM9tO5FLmhWb2q9iGFBcKgUJ3rz8b/R2RJNLbXQxsc/cD7l4N/AH4WIxjOiFKGs2tBCaY2VgzSyHSSbU4xjHFnJkZkevT77v7A7GOJ164+33unuvuY4j8X/mTu3ervxw7g7vvBXaa2cSg6CJgQwxDihc7gDlm1jf4mbqIbnaDQFKsA4g37l5jZncDS4jc2fC4u6+PcVjx4BzgNmCtmb0XlP1vd38pdiFJnLsH+HXwx9dW4I4YxxNz7v6Omf0O+BuROxJX0c2GE9EwIiIiEpouT4mISGhKGiIiEpqShoiIhKakISIioSlpiIh0M2b2uJntN7N1IeqeZ2Z/M7MaM7u+ybpaM3sveIV6tEBJQ6SDmNmgqB/AvWa2K1g+amb/Fev4pEd5ArgsZN0dwGeAp1pYV+7uZwava8JsTM9piHQQdz8EnAlgZt8Gjrr7v8YyJumZ3P0vwRhwDczsFCIjdGcDZcDn3X2ju28P1nfI2Gg60xDpZGZ2fv08G2b2bTN70syWmtl2M/ukmf3QzNaa2SvBUC2Y2Qwz+7OZvWtmS8xseGy/hXQDjwL3uPsM4H8BYc5u08ws38yWm9m1YXaiMw2RrncKcAGR+VqWAde5+z+b2XPAlWb2IvCfwDx3P2BmNwHfAz4bs4glrgUDiX4M+G1kdBIAUkM0HeXuu81sHPAnM1vr7lvaaqCkIdL1Xnb3ajNbS2SomleC8rXAGGAiMAV4NfgFkEhkGG2R1iQARe5+5ok0cvfdwftWM3uTyJQHbSYNXZ4S6XqVAO5eB1T78bF86oj8IWfA+qgOyqnuPjdGsUo3EExTsM3MboDIAKNmNq2tNmaWZWapwfJgIuPLtTuopJKGSPzZBGTXz6ltZslmNjnGMUkcMbOniVzanGhmhWZ2J3ArcKeZrQbWE8w4amYzzawQuAH4qZnVD8B6OpAf1H8DWOju7SYNXZ4SiTPuXhXcT/+gmWUS+Tn9MZFfBCK4+y2trGp2G667ryQyL1DT8reBqSe6b41yKyIioenylIiIhKakISIioSlpiIhIaEoaIiISmpKGiIiEpqQhIiKhKWmIiEho/x9HD2T/NVPplgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(((ds.SALT*ds.rA*ds.drF*ds.hFacC).sum(['XC','YC','Z']))/(ds.rA*ds.drF*ds.hFacC).sum(['XC','YC','Z'])).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "873f073c",
   "metadata": {},
   "source": [
    "Now we want to know: is the ocean in equilibrium? We can plot a few things to help with this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4b19ac38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2ad72ea2eca0>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#the mean temperature\n",
    "(((ds.THETA*ds.rA*ds.drF*ds.hFacC).sum(['XC','YC','Z']))/(ds.rA*ds.drF*ds.hFacC).sum(['XC','YC','Z'])).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "34f0d8df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2ad72ecd3f10>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#the mean temperature in the bottom level\n",
    "(((ds.THETA*ds.rA*ds.drF*ds.hFacC).isel(Z=-1).sum(['XC','YC']))/(ds.rA*ds.drF*ds.hFacC).isel(Z=-1).sum(['XC','YC'])).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10151174",
   "metadata": {},
   "source": [
    "Let's also just plot the temperature at the surface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a1e7c3c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ad72e2e2880>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.THETA.isel(time=-1,Z=0).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e50e58ef",
   "metadata": {},
   "source": [
    "Now let's plot the vertical velocity at the bottom:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1b6f770c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ad72ee6d670>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(ds.WVEL.isel(time=-1,Zl=-1)*10**6).plot(levels=np.arange(-1,1,0.1))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1284e0fc",
   "metadata": {},
   "source": [
    "Now we're going to plot the streamfunction of the Meridional Overturning Circulation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "97d1ce79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ad72ea0f700>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "((ds.VVEL*ds.dxG*ds.drF).isel(time=-1).sum('XC')/10**6).plot(levels=np.arange(-2,2,0.1))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60d1e250",
   "metadata": {},
   "source": [
    "I often find it quite useful to look at how this is changing too:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "52094dea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x2ad72eb33430>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "((ds.VVEL*ds.dxG*ds.drF).isel(time=-1).sum('XC')/10**6-(ds.VVEL*ds.dxG*ds.drF).isel(time=-70).sum('XC')/10**6).plot(levels=np.arange(-2,2,0.1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "56b30f0f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}